Engineering Geology of the Patonga Claystone, Central Coast, New South Wales, with Particular Reference to Slaking Behaviour

THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF BIOLOGICAL, EARTH AND ENVIRONMENTAL SCIENCES

ENGINEERING GEOLOGY OF THE PATONGA CLAYSTONE, CENTRAL COAST, NEW SOUTH WALES, WITH PARTICULAR REFERENCE TO SLAKING BEHAVIOUR

Sorawit Nunt-jaruwong (M.App.Sc. University of New South Wales)

A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy May 2006

ABSTRACT

The Patonga Claystone, a red bed facies in the Narrabeen Group of the Sydney Basin, is one of the most unfavorable rock units in the basin from a geotechnical point of view. This rock unit is composed of sandstone, siltstone, mudstone and claystone. One of the unfavorable characteristics is the low shear strength, which causes instability of cut slopes; another is its slaking-prone behaviour.

Numerous measurements of geotechnical properties, along with extensive mineralogical and geochemical determinations, were carried out to identify cause of this slaking behaviour. Key techniques were the use of quantitative X-ray diffractometry for mineralogical analysis, and the determination of slake durability index and related properties to evaluate the slaking behaviour under both standard and more extended conditions.

Standard (two cycle) slake durability test results indicate a range from low to high slake durability index values, with some mudstone samples having very low durability and some sandstones having very high slake durability indices. Jar slake test results indicate that the rock samples break rapidly and/or develop several fractures (Ij = 4) in an as-received state, but degrade to a pile of flakes or mud (Ij = 1) if the samples are oven dried before testing. The results for jar slake testing of oven-dried material are comparable, for individual samples, to those obtained from the more comprehensive slake durability tests.

The mineralogy of the samples was evaluated by quantitative X-ray diffraction techniques using the Rietveld-based Siroquant processing system. Comparison to independent chemical data show a generally good level of agreement, suggesting that the mineralogical analysis ii

results are consistent with the chemical composition of the individual rock samples. Good correlations were also obtained between clay mineralogy determined from oriented- aggregate XRD analysis of the <2 micron fraction and the results from powder diffractometry and Siroquant analysis of the whole-rock samples.

Evaluation of the slake durability characteristics and other geotechnical properties in relation to the quantitative mineralogy suggests that quartz and feldspar form a rigid framework in the rocks that resists the disruptive pressures that cause slaking. Expansion of the clay minerals by various processes, including the incorporation of water into the interlayer spaces of illite/smectite as well as changes in pore pressures associated with entry of water into micro-fractures in the clay matrix, are thought to produce the disruptions that cause slaking and degradation. An abundant clay matrix also reduces the strength of the rock materials, probably because of the less rigid nature of the clay minerals relative to the quartz and feldspar particles.

As well as the mineralogy, the loss on ignition (LOI) and water absorption percentage were found to provide good indicators of longer-term slaking behaviour. Both properties are also related to the overall clay content. Rock samples with water absorption values of <10, 10-15 and >15% behave as highly durable, intermediate and less durable materials respectively. Rocks with LOI values of greater than 5% by weight behave as less durable rock materials, at least for the strata encompassed by the present study. The water absorption and LOI values were also used to develop a predictive model of slake durability characteristics for the different rock materials in the Patonga Claystone, providing a relatively simple basis for predicting longer-term stability in a range of geotechnical studies. iii

ACKNOWLEDGEMENTS

First and foremost I thank my supervisors Dr Colin Ward and Greg McNally for setting up the topic, encouraging, understanding, and editing the report. Advice, help, and interest from many other staff members are gratefully acknowledged, in particular Michael de Mol and Rad Flossman with the sample preparation, Irene Wainwright for assistance with the XRF and CEC analyses, and Dr Ervin Slansky and Jaine Steer for the XRD analysis.

The National Energy Petroleum Organization (Thailand) is gratefully thanked for their financial support during the study. My colleagues in Engineering Geology Section, Department of Energy Development and Promotion (DEDP) Thailand, are also thanked for their support, and for looking after my duties during my absence from the office.

The Schools of Mining Engineering and Civil Engineering, and also the Electron Microscopy Unit at the University of New South Wales, are also thanked for access to laboratory facilities.

Sincere thanks are also extended to Kwea Htay and his family, for their kind and unforgettable friendship. Thank you very much, my best friends.

I also thank Coal Operations Australia Limited (COAL) for supplying borehole information and core samples for XRD analysis and geotechnical testing. Thanks are also given to Chris Herbert and his colleagues at Mining Exploration Geology Services Pty Limited (MEGS) for their kind and valuable discussions and their ready supply of useful information.

Finally, I would like to thank my family for their support and encouragement throughout my student years.

TABLE OF CONTENTS

ABSTRACT i ACKNOWLEDGEMENTS iii LIST OF FIGURES viii LIST OF TABLES xiii

CHAPTER 1: Introduction 1 1.1 Geology of the Sydney Basin 1 1.2 Geology and Geotechnical Problems of 6 Patonga Claystone 1.3 Problems Encountered in Patonga Claystone 7 1.3.1 F3 Freeway slope failure 7 1.3.2 Slump in Woolworths Carpark basement 9 1.3.3 Surficial sliding Toowoon Bay 10 Caravan Park 1.3.4 Sewage Treatment Works, Charmhaven 10 1.4 Aims of study 11 1.5 Research Design 12 1.5.1 Literature review 12 1.5.2 Sampling program 13 1.5.3 Mineral composition 13 1.5.4 Geotechnical properties 17 1.5.5 Data evaluation 17

CHAPTER 2: Geology and Sedimentology 18 2.1 Introduction 18 2.2 Regional Geology 18 2.3 Geology of the Study Area 24 2.4 Sedimentology and depositional Environment of 33 the Patonga Claystone

CHAPTER 3: Mineralogical and Chemical Analysis 41 3.1 Introduction 41 3.2 Clay and the Clay Minerals 44 3.2.1 Definitions 44 3.2.2 Classification of the Clay Minerals 46 3.2.3 Interstratified or Mixed-layer Clay Minerals 51 3.2.4 Geotechnical Properties and Clays 54 3.3 X-ray Diffraction Techniques 59 3.3.1 Background Theory 59 3.3.2 XRD Equipment and Setting 62 3.3.3 Sample preparation 63 3.4 Mineral Identification from Powder XRD Data 66 3.4.1 Using Philips APD Software 66 3.4.2 Using XPlot for Windows 69 3.5 Clay Mineral Characteristics from Oriented 70 Aggregate X-ray Diffractrometry 3.5.1 Clay Mineral Identification 70 3.5.2 The Nature of the XRD patterns from 73 the oriented aggregate samples studied 3.5.3 Qualitative interpretation 74 3.5.4 Estimation of illite and smectite 78 proportions in mixed layer clay minerals 3.5.5 Compare I/S proportion to Newmod 82 v

3.5.6 Quantitative Interpretation of Oriented 86 Aggregates 3.5.6.1 Quantitative assessment of clay 86 mineral proportions 3.5.6.2 Clay minerals percentages from 89 oriented aggregates in the present study 3.6 Chemical Analysis 93 3.6.1 X-ray Fluorescence Spectrometry 94 3.6.1.1 Methodology 94 3.6.1.2 Results 96 3.6.2 Organic Matter Content 99 3.6.2.1 Methodology 99 3.6.2.2 Results 102 3.7 Quantitative Whole-rock Mineralogical 103 Analysis Using Siroquant 3.7.1 Previous Methods 103 3.7.2 Using Siroquant 105 3.7.3 Problems with Siroquant 109 3.7.4 Results 110 3.7.5 Comparison of Siroquant Mineralogy to 114 Chemical Composition 3.7.6 Comparison of Powder and Oriented 119 Aggregate XRD Data 3.7.7 Relationship between LOI and mineralogy 122 3.8 Cation Exchange Capacity 123 3.8.1 Methodology 124 3.8.2 Results 126 3.8.3 Relation of CEC to Clay Content 128 3.9 Comparison to Thin Section Studies 131 3.10 Concluding Summary 133

CHAPTER 4.1: Mudrock Durability 137 4.1.1 Introduction 137 4.1.2 Slaking Mechanisms 138 4.1.3 Causes of Mudrock Deterioration 142 4.1.4 Slake Durability Testing 148 4.1.5 Relevance of Tests to Deterioration in 159 Natural Exposures 4.1.6 Slake Durability Classification 161 4.1.7 Some Previous Studies of Slaking Behaviour 169 4.1.8 Tests Used in this Study 174 4.1.8.1 Jar slake test 175 4.1.8.2 Slake durability test 176 4.1.8.3 Water adsorption 177 4.1.8.4 Water absorption 178 4.1.8.5 Other tests not used 179

CHAPTER 4.2: Durability Test Results 181 4.2.1 Moisture content 181 4.2.2 Jar slake testing 182 4.2.3 Slake durability test 192 4.2.3.1 Slake durability test results 192 4.2.3.2 Rock characteristics after testing 195 4.2.3.3 Rock types and slake durability 199 4.2.4 Water adsorption 202 vi

4.2.5 Water absorption 202 4.2.6 Relations of other parameters to slake 204 durability index 4.2.6.1 Moisture content and slake durability 205 4.2.6.2 Jar slake index against slake durability 207 4.2.6.3 Water adsorption and slake durability 211 4.2.6.4 Water absorption and slake durability 215 4.2.6.5 Slake durability decay index 219 4.2.7 Concluding Summary 221

CHAPTER 5: Other Geotechnical Properties 224 5.1 Introduction 224 5.2 Previous Studies 224 5.3 Tests Used in the Present Study 237 5.3.1 Specific gravity, density and porosity 239 5.3.2 Indirect tensile strength 245 5.3.3 Uniaxial compressive strength 248 5.3.4 Ultrasonic velocity 253 5.3.5 Point load strength 258 5.4 Relationships to Mineralogy and Slaking 266 Characteristics 5.4.1 Moisture content 266 5.4.2 Water absorption 268 5.4.3 Mineralogy 270 5.4.4 Seismic velocity 275 5.4.5 Slake durability 277 5.5 Keuper Marl 279 5.5.1 Geology and Mineralogy of Keuper Marl 279 5.5.2 Geotechnical Properties of the Keuper Marl 282 5.5.3 Comparison to the Patonga Claystone 284 5.5.3.1 Mineralogy 284 5.5.3.2 Engineering Properties 284 5.6 Concluding Summary 287

CHAPTER 6: Results of the Study 292 6.1 Introduction 292 6.2 Relation of Rock Mineralogy to Slake Durability 293 6.2.1 Kaolinite and slake durability 294 6.2.2 Illite and slake durability index 297 6.2.3 Mixed layer clay and slake durability index 297 6.2.4 Quartz and slake durability 300 6.2.5 Quartz plus feldspar and slake durability 300 6.2.6 Total clay minerals and slake durability 303 6.3 Chemical Composition 305 6.3.1 SiO2 and slake durability 306 6.3.2 Al2O3 and slake durability 307 6.3.3 Fe2O3 and slake durability 310 6.3.4 K2O and slake durability 311 6.3.5 SiO2+Al2O3 and slake durability 313 6.3.6 SiO2+Al2O3+Fe2O3 and slake durability 315 6.3.7 Loss on ignition and slake durability 316 6.4 Cation Exchange Capacity 320 6.4.1 Relation of clay minerals and CEC 320 6.4.2 Dispersion potential 321 6.4.3 Cation exchange capacity against slake 323 durability vii

6.4.4 Relation of exchangeable Na and Ca to 326 slake durability 6.4.5 [Ca+Na+Mg]/TEC against slake durability 326 6.5 Behaviour of Different Rock Types 329 6.6 Fracture and Durability 337 6.7 Multiple Regression Analysis 339 6.8 Concluding Summary 344

CHAPTER 7: Conclusions 348 7.1 Mineralogical and Chemical Characteristics 349 7.2 Slaking and Durability 352 7.3 Effect on Other Geotechnical Properties 355 7.4 Relation of mineralogy to Rock Durability 357 7.5 Slaking Mechanisms 359

CHAPTER 8: References 361

Addendum A-1

List of Editorial Corrections B-1

APPENDIX A – Petrological Studies

APPENDIX B – X-ray Diffractogram & Siroquant Results

APPENDIX C – Geotechnical results

viii

LIST OF FIGURES

1.1 Location of Sydney – Bowen Basin 2 1.2 The Sydney – Bowen Basin in New South Wales 3 1.3 Stratigraphic sequence in the Sydney Basin 6 1.4 Location map and problem areas 9 1.5 Location of drill holes and core samples and outcrop 14 samples

2.1 Outcrop Distribution of the Narrabeen Group (stipples) 19 and associated rock units in the main part of the Sydney Basin 2.2 Outcrops of the Hawkesbury Sandstone (top), Narrabeen 20 Group (middle) and Illawarra Coal Measures (bottom) at Stanwall Park, north of Wollongong 2.3 Location of boreholes sampled and geologic cross 22 section line used in the study of Narrabeen Group correlation by Ward (1971b) 2.4 Stratigraphic cross section of the Narrabeen Group 23 from Dapto in the South (Huntley DDH 8) to Wyong in the north (Qurimbah Creek DDH 5), showing correlation based on mineralogical markers 2.5 Distribution of formations within the Narrabeen Group 28 in the Central Coast area 2.6 General view of the Patonga Claystone exposed on the 30 coast at Forresters Beach in the Central Coast area 2.7 Interbedded sandstone (light) and mudstone (dark) in 31 the Patonga Claystone at Forresters Beach 2.8 Interbedded sandstone (strongly outcropping bands) and 31 mudstone in the Patonga Claystone at Forresters Beach 2.9 Weathering of siltstone in the Patonga Claystone 32 2.10 Root remnant in sandstone of the Patonga Claystone 32 2.11 Colour mottling in sandstone of the Patonga 35 Claystone, Forresters Beach, NSW 2.12 Plant remains in the Patonga Claystone, Forresters 37 Beach 2.13 Thin section of sandstone from the Patonga 39 Claystone, showing chlorite, altered feldspar, and opaque minerals 2.14 X-ray diffractograms of greenish grey (top) and red 40 brown (bottom) mudstone samples from the Patonga Claystone, Forresters Beach, Central Coast - NSW

3.1 a) single tetrahedron and b) sheet structure of 47 tetrahedrons arranged in a hexagonal network 3.2 a) single octahedral unit and b) sheet structure 48 of the octahedral units 3.3 Kaolinite (left) and mica/illite (right) structures 50 3.4 Chlorite (left) and smectite (right) structures 51 3.5 Schematic representation of the geometry of an X-ray 59 diffractometer 3.6 An illustration of Bragg’s Law 61 3.7 Philips PW 3710 X-ray diffractometer used for the 62 present study 3.8 Peak positions and peak intensities used in 67 identifying of mineral content ix

3.9 XPlot for Windows screen showing mineral 70 identification output 3.10 Equidistance of basal (001) peaks 71 3.11 Variation in clay mineral XRD traces 74 encountered in this study in a) glycolated and b) heated conditions 3.12 Diffractogram of preferred oriented aggregate, 75 sample number 511, as air-dried (bottom), glycolate (middle), and heated (top) conditions 3.13 Kaolinite and high Fe-chlorite 78 3.14 Glycol patterns of randomly interstratified (a) and 79 ordered (b) mixed layer (I/S) with a range of interstratified illite/smectite percentages, CuKα radiation 3.15 Graphical method for estimating illite content 81 of mixed layer I/S with random (a) and ordered interstratification (b), using CuKα radiation 3.16 Illite (top) and glycolated smectite (bottom), 82 modified from Newmod software 3.17 Various proportions of illite in mixed layer I/S 84 (glycolated pattern) from Newmod 3.18 Typical glycolated (bottom) and heated (top) 85 diffractograms of rock samples from the study area used in defining the proportion of individual clay mineral in mixed layer I/S 3.19 Typical glycolated diffractograms of rock samples 86 from the study area, showing variation of illite percentage in the mixed layer I/S 3.20 Trace of the d(004) chlorite XRD peak at 3.54 Å 90 and d(002) kaolinite peak at 3.57 Å 3.21 Schematic diagram of unit for measuring X-ray 95 Fluorescence 3.22 Philips PW 2400 XRF analyzer with PW 2150 sample 96 changer, used in the present study 3.23 LECO CNS elemental analyzer used for carbon, sulfur 100 and nitrogen determination 3.24 Operation of Siroquant software for quantitative 106 XRD analysis. Top panel shows the fit of observed and calculate patterns while the bottom panel indicates the difference between these two patterns 3.25 Refining parameters for Siroquant. ‘-‘ and ‘x’ 106 indicate the variables that are refinable and fixed respectively for the analysis run in question 3.26 Graphic output from Siroquant showing the observed 107 trace (top), calculated trace (middle) and the difference between these two traces (bottom) 3.27 Tabulated Siroquant results with global chi2 107 value also indicated 3.28 Comparision of oxide percentage from Siroquant 115 and XRF 3.29 Plots of clay mineral percentages determined 120 from oriented aggregate data against normalized percentages of the same minerals from Siroquant: a) Kaolinite and Chlorite, b) Illite and c) Mixed layer clay minerals x

3.30 Relationships between loss on ignition and 123 total clays (a) and quartz plus feldspar (b) 3.31 Sample preparation for CEC determination 125 3.32 Plot of total clay mineral content (from Siroquant) 129 against CEC value 3.33 Plots of individual clay types against CEC 130 value: illite (a), illite plus mixed layer I/S (b), mixed layer I/S (c), and kaolinite (d) 3.34 Mudstone (sample number 613) under optical 132 microscopy (x50) 3.35 Sandstone (sample number 504) under optical 133 microscopy (x50)

4.1.1 Processes involved in slaking: (a) shale sample; 140 (b) macropore with water and air pressure; (c) air and water forces at the air-water interface in a macropore 4.1.2 Determining class numbers of aggregates from the 151 Emerson Crumb test 4.1.3 Slake durability equipment and its dimension 157 4.1.4 Gamble’s slake durability classification 162 4.1.5 Slake durability classification 165

4.2.1 Photographs illustrating rock behaviour in 183 the jar slake index test. Top: Ij = 1 – degrades to a pile of flakes or mud; Middle: Ij = 2 – breaks rapidly and forms many chips; Bottom: Ij = 6 – no change 4.2.2 Bar graph showing the number of samples in each 188 category from the Jar Slake Test, based on the overall rock sample 4.2.3 Bar graph showing the number of samples in each 190 category for jar slake tests of mudstone (a) and sandstone samples (b) 4.2.4 Plot illustrating the range of slake durability 193 index results with different numbers of tested cycles 4.2.5 Illustration of fragment types retained during 196 slake durability testing: Top: Type 1; Middle: Type 2; Bottom: Type 3 4.2.6 Bar graph showing the distribution of 197 disintegration types for each slake durability cycle 4.2.7 Changes in the percentage of cases with 198 different disintegration types during the slake durability test 4.2.8 Moisture contents plot against slake durability 206 index as 2nd cycle (a), 3rd cycle (b), and 5th cycle (c) 4.2.9 Oven dried jar slake index plotted against 2nd 208 cycle (a), 3rd cycle (b), and 5th cycle (c) slake durability data 4.2.10 Air dried jar slake index plotted against 2nd 209 cycle (a), 3rd cycle (b), and 5th cycle (c) slake durability data

4.2.11 Plot of water adsorption for all samples 212 against slake durability index. Top: 2nd cycle, Middle: 3rd cycle, Bottom: 5th cycle 4.2.12 Water adsorption against slake durability in 214 mudstone samples, a) 2nd cycle, b) 3rd cycle, c) 5th cycle, and sandstone samples, d) 2nd cycle, e) 3rd cycle, f) 5th cycle 4.2.13 Plots of water absorption against slake durability 217 index. Top: 2nd cycle, Middle: 3rd cycle, Bottom: 5th cycle 4.2.14 Water absorption against slake durability in 218 mudstone samples, a) 2nd cycle, b) 3rd cycle, c) 5th cycle, and sandstone samples, d) 2nd cycle, e) 3rd cycle, f) 5th cycle 4.2.15 Decay curve – slake durability index against 220 time, sample number 708 is shown here 4.2.16 Slake durability decay index and water absorption 220

5.1 Location map showing areas of previous study 225 5.2 Typical stress-strain curves in compression test 232 5.3 Slope stabilization for Sydney Newcastle Freeway at 236 Hue Hue Road 5.4 Remedial work for Sydney Newcastle Freeway at 237 Hue Hue Road 5.5 Higher porosity caused by rock fractures 245 5.6 Indirect (Brazilian) tensile strength test 246 5.7 Indirect Tensile Testing (Brazilian Test) 247 5.8 Equipment set up for Young’s modulus determination 250 5.9 Stress-Strain curves of typical rock samples 251 5.10 Mode of failure of sandstone sample (left) and 253 mudstone sample (right) 5.11 Position of transmitter and receiver for ultrasonic 254 velocity determination 5.12 Type of point load test with the geometry of the 259 sample : diametral test (left); axial test (middle) and irregular lump test (right) 5.13 Correcting chart for Point Load Strength Index 261 5.14 Histogram showing point load strength index for 265 the present study 5.15 Relationship between point load strength index 267 (Is50) and moisture content of a) mudstone and b) sandstone 5.16 Water absorption percentage plotted against Is50 as 268 a) mudstone and b) sandstone 5.17 Relationship between moisture content and water 270 absorption of mudstone 5.18 Relationship between key minerals and Uniaxial 271 Compressive Strength 5.19 Relationship between key minerals and water 273 absorption percentage 5.20 Relationship between key minerals and moisture 274 content 5.21 Inverse relation between unit weight and velocity 275 5.22 Relation of UCS and P-wave velocity 276 5.23 Relationship between UCS and (a) 2nd cycle, (b) 278 3rd cycle and (c) 5th cycle slake durability index xii

5.24 Exposure of the Keuper Marl 280

6.1 Plots of kaolinite percentage against slake 296 durability Id2, Id3 and Id5 6.2 Plot of the illite percentage against slake 298 durability Id2, Id3 and Id5 6.3 Plot of the mixed layer clay mineral content 299 against slake durability Id2, Id3 and Id5 6.4 Plot of total quartz percentage against slake 301 durability index (Id2, Id3 and Id5) 6.5 Plot of quartz plus feldspar against slake 302 durability index (Id2, Id3 and Id5) 6.6 Plot of total clay content against slake 304 durability index (Id2, Id3 and Id5) 6.7 Plots of SiO2 from XRF analysis against slake 308 durability index (Id2, Id3 and Id5) 6.8 Plots of total Al2O3 content from XRF analysis 309 against slake durability index (Id2, Id3 Id5) 6.9 Plots of total Fe2O3 content from XRF analysis 310 against slake durability index (Id2, Id3 Id5) 6.10 Plots of total K2O from XRF analysis against 312 slake durability index (Id2, Id3 Id5) 6.11 Plot of SiO2 and Al2O3 from XRF analysis against 314 slake durability index (Id2, Id3 Id5) 6.12 Plot of SiO2+Al2O3+Fe2O3 from XRF analysis against 315 slake durability index (Id2, Id3 Id5) 6.13 Plot of loss on ignition against slake durability 317 index (Id2, Id3 Id5) for samples studied by XRF analysis 6.14 Plot of LOI for full range of samples against 318 slake durability index (Id2, Id3 Id5) 6.15 Plot of CEC against total clay minerals 321 6.16 Dispersion potential of Patonga Claystone samples 322 6.17 Plots of ratio of Na/CEC against 2nd cycle slake 323 durability index 6.18 Plot of Cation Exchange Capacity against slake 325 durability index (Id2, Id3 Id5) 6.19 Plot of [Na+Ca]/TEC against slake durability 327 index (Id2, Id3 Id5) 6.20 Plot of [Na+Ca+Mg]/TEC against slake durability 328 index (Id2, Id3 Id5) 6.21 Plots showing percentage of kaolinite against 331 slake durability indices for mudstone (left) and sandstone (right) 6.22 Plot showing percentage of mixed layer clay 332 minerals against slake durability indices for mudstone (left) and sandstone (right) 6.23 Plots showing percentage of quartz against slake 333 durability indices for mudstone (left) and sandstone (right) 6.24 Plots showing percentage of quartz plus feldspar 334 against slake durability indices for mudstone (left) and sandstone (right) 6.25 Plots showing loss on ignition against slake 335 durability indices for mudstone (left) and sandstone (right) xiii

6.26 Scanning electron micrograph of a low durability 338 rock sample (sample 310) 6.27 Scanning electron micrograph of a high durability 338 rock sample (sample 504) 6.28 Plots of predicted 2nd slake durability index 344 against observed values

LIST OF TABLES

1.1 Sedimentary rock succession in the Sydney Basin 4 1.2 Stratigraphic nomenclature of the Narrabeen Group 5 in three separate areas 1.3 Source and description of rock samples used in 15 the present study

2.1 Rock units of the Narrabeen Group in the three 24 different parts of the Sydney Basin 2.2 Type section of the Patonga Claystone in Windeyer’s 26 Hawkesbury River Bore, from 776’0” to 1,224’6” (234.98 to 370.77 m)

3.1 Classification of layered clay minerals 53 3.2 Plastic limit and liquid limit of pure clay 55 minerals and mixtures 3.3 Basal crystallographic (d{00l}) spacing of 72 principal clay minerals after various treatments 3.4 Determining the composition of mixed layer (I/S) 80 from the d(002) peak 3.5 Percentages of clay minerals in <2 µm fraction 91 by method of Griffin (1971) 3.6 Statistical values of clay mineral content in 92 studied samples 3.7 Clay mineral contents based on rock type 92 3.8 Chemical analysis of selected rock samples by 97 XRF methods 3.9 Statistical evaluation of chemical composition 98 determined by XRF of selected samples 3.10 Chemical composition based on rock type 99 3.11 Determination of carbon content of selected 102 rock samples 3.12 Mineral percentages of samples as determined 110 by Siroquant 3.13 Statistical analysis on mineral content of the 112 samples studied, based on Siroquant data 3.14 Minerals proportions in mudstone and sandstone 113 samples based on Siroquant data 3.15 Chemical composition of samples in Table 3.12, 114 interpreted from Siroquant data 3.16 Linear regression equation and R2 for inferred 116 chemical composition from Siroquant and actual chemistry – XRF method 3.17 Linear regression equations and R2 for clay 121 minerals xiv

3.18 CEC results for rock samples studied 127 3.19 Statistical analyses of cation exchange capacity 127 3.20 Coefficient of determinations between CEC and clay 128 minerals

4.1.1 Jar slake ranking 149 4.1.2 Gamble’s slake durability classification 161 4.1.3 Description of the degree of slaking 163 4.1.4 Description of rate of slaking 164 4.1.5 Mudrock durability classification system 168 propose by Dick et al (1994)

4.2.1 Statistical summary of moisture content for 182 the rock samples studied 4.2.2 Results of moisture content determinations, jar 184 slake index tests and slake durability index tests 4.2.3 Summary of jar slake test data 187 4.2.4 Statistical summary of the slake durability 194 test results 4.2.5 Percentage of samples with each type of 197 disintegration characteristics at each stage of the slake durability testing process 4.2.6 Slake durability classification for samples tested 199 4.2.7 Summary of slake durability and moisture data 200 based on lithological characteristics 4.2.8 Water adsorption and absorption testing 203 4.2.9 Water adsorption and absorption results based 204 on rock type 4.2.10 Durability classification based on 2nd slake 221 durability cycle and water absorption for the present study

5.1 Summary of mean point load and UCS test results 226 for rocks from the Patonga Claystone 5.2 Dispersion test results for Patonga Claystone samples 229 5.3 Change in plasticity index after change in wet and 230 dry cycles in ‘Shale test’ 5.4 Residual parameters from triaxial test on 231 Kincumber/Outfall Tunnel Project 5.5 Summary of previous UCS and related results 233 5.6 Shear strength parameters used in F3 Freeway at 235 Hue Hue Road original design 5.7 Back analysis results 236 5.8 Unit weight and dry unit weight of rock samples 243 5.9 Brazilian Test results 248 5.10 Various UCS strength classification systems 249 5.11 Uniaxial compressive strength and Young’s 251 modulus results 5.12 Primary and Secondary Wave velocity, Deformation 256 Modulus and Poisson’s ratio 5.13 Relation of RQD, fracture frequency and velocity 257 index 5.14 Point load strength classification 262 5.15 Results for point load strength index 263 5.16 Point load strength index of mudstone and 264 xv

sandstone samples 5.17 Keuper Marl – mineralogical composition of 281 whole material (percent) 5.18 Comparison of engineering properties 285

6.1 Coefficients of determination between key mineral 294 percentages and slake durability results 6.2 Slake durability and XRF results 306 6.3 Coefficients of determination between CEC and slake 324 durability results 6.4 Coefficients of determination between key parameters 329 and slake durability results based on rock types 6.5 Multiple regression analysis of tested results 341 6.6 Predicted and observed results for slake 343 durability tests on outcrop samples

CHAPTER 1 INTRODUCTION

This chapter deals with the geological setting of the Sydney Basin, including its location and a description of the rock units present. The geology of the formations relevant to the study will be briefly discussed, as well as the overall approach to the research program.

1.1 Geology of the Sydney Basin

The Sydney Basin is the southern part of the Sydney – Bowen Basin, a complex extending from Batemans Bay northwards to central Queensland (Figure 1.1).

The New South Wales portion of the basin is located between the Lachlan Fold Belt to the west and the New England Fold Belt to the east (Figure 1.2). The complex is divided into the Bowen Basin in the north and the Sydney and Gunnedah Basins in the south by a transverse structural high near Narrabri. The Sydney Basin in the extreme south is then separated from the Gunnedah Basin in the north of this belt by the Mount Coricudgy Anticline (Figure 1.2). 2

Figure 1.1: Location of Sydney – Bowen Basin (modified from Herbert, 1980).

The strata filling the Sydney Basin range in age from Carboniferous to Quaternary deposits (Bembrick et. al., 1980). The most significant rock units for the present study are the Newcastle and Illawarra Coal Measures, the Narrabeen Group and the Hawkesbury Sandstone, which form a sequence of Late Permian to Middle Triassic age near the top of the basin fill, outcropping in the Newcastle-Sydney- Wollongong area. 3

Figure 1.2: The Sydney – Bowen Basin in New South Wales (Bembrick et al., 1980).

Table 1.1: Sedimentary rock succession in the Sydney Basin (Ward, 1972).

Illawarra- Age Hunter Valley Lithgow Wianamatta Group

Triassic Hawkesbury Sandstone Narrabeen Group Newcastle Coal Singleton Illawarra Measures Coal Coal Tomago Measure Measures Coal Permian Measures Maitland Group Shoalhaven Greta Coal Measures Group Clyde Coal Dalwood Group Measures

The Narrabeen Group ranges in age from Late Permian to Middle Triassic (McNally, 1995). The base of the Narrabeen Group is arbitrarily taken as the top of the highest coal seam (the Wallarah seam, or one of its splits) within the Newcastle Coal Measures, making its lowest beds latest Permian rather than Triassic in age (McNally, 1995). It consists of up to 700 m of lithic conglomerate, quartz- lithic sandstone and red, green and light-grey shale. The overlying Hawkesbury Sandstone, with a maximum thickness of 290 m, is of Middle Triassic age, and consists dominantly of coarse quartz-sandstone with minor layers of dark grey shale. The Wianamatta Group is also of Middle Triassic age. The maximum thickness of this group is 300 m, but it is rarely more than 100 m thick. It consists mainly of grey shale with sporadic, thin lithic sandstone layers and rare thin coal seams (Branagan, 1985).

The Narrabeen Group has been subdivided into formations in three separate areas, the North Coast, the South Coast and Collaroy-Palm Beach area and the Western District (Table 1.2 and Figure 1.3). More details of the stratigraphic units in the Narrabeen Group will be discussed in Chapter 2.

Table 1.2: Stratigraphic nomenclature of the Narrabeen Group in three separate areas (Ward, 1971b).

A more comprehensive overview of the stratigraphic sequence in the Sydney Basin is shown in Figure 1.3.

Figure 1.3: Stratigraphic sequence in the Sydney Basin (Herbert, 1997).

1.2 Geology and Geotechnical Problems of Patonga Claystone

The Patonga Claystone is a Triassic red bed sequence that forms the top of the Clifton Sub-Group of the Narrabeen Group in the Central Coast area of the Sydney Basin, cropping out over an area of approximately 150 km2 in the Wyong and Gosford region. The Patonga Claystone has an average thickness of 137 m, with a maximum thickness of 167 m in the type section in the Windeyer’s Hawkesbury River Bore, south of Gosford (Hanlon, et al, 1953). It retains a constant thickness towards the north, being 140 m thick at Wyong (McNally, 1995).

The Patonga Claystone consists primarily of red-brown mudstone with lesser proportions of siltstone and 7

sandstone. The colour of the mudstone units varies from predominantly red-brown (chocolate) to green-grey. Fresh sandstone and siltstone units are green-grey in colour while weathered beds of these units are pale brown in colour.

The Patonga Claystone is probably the most undesirable rock for foundations in the Narrabeen Group of the Central Coast area. It has a low shear strength, is slaking prone, and has erosive properties. These properties make it unfavorable when exposed on slopes, in cuttings, or as a building foundation.

Dispersive properties have been reported from tests of completely weathered mudstone (ECNSW, 1983a). The rock appears to be dispersive and non-dispersive in fresh water but non-dispersive in sea water (ECNSW, 1983a).

The unfavorable geotechnical properties, the widespread nature of the Patonga Claystone, and the rapid growth of urban development in the Gosford area, combine to produce geotechnical problems in a variety of construction projects. One of these geotechnical problems, for example, is the rapid weathering of the claystone; another problem is the low shear strength of the weathered rock, which causes slope instability (Fell et al., 1987).

1.3 Problems encountered in the Patonga Claystone

Some of the geotechnical problems related to the Patonga Claystone in the Gosford-Wyong area (Figure 1.4) are briefly discussed below.

1.3.1 F3 Freeway slope failure

A major landslide occurred occurred on the Sydney– Newcastle (F3) Freeway in 1983, at the Hue Hue Road overpass outside Wyong (Figure 1.4). This slope failure cost $3 million to repair (Fell et al., 1987). A cutting about 600 m long, with a maximum depth of 20 m, had been excavated through a completely to highly weathered exposure of the Patonga Claystone. Three years after the construction, due to heavy rainfall, the cutting collapsed due to a landslide on a low-strength bedding plane.

The remedial work following the failure involved removal of the entire disturbed material to below the level of the siltstone-claystone crush zone, construction of a drainage trench, and placement of free-draining rock fill. Ripped sandstones were placed on top of the free-draining rock fill and covered by topsoil (more details in Chapter 5).

Figure 1.4: Location map and problem areas.

1.3.2 Slump in Woolworths carpark basement

A basement excavation was made in 1974 for a major shopping centre development scheme on Alison Road, Wyong (Figure 1.4). The vertical cut, down to 12 metres in depth, revealed weathered claystone in the upper 6 metres. This weathered claystone was unstable in a vertical cut of that height.

The slope instability was remedied by placement of concrete slabs, secured with 10 metre long rock anchors founded into bedrock of fresh Patonga Claystone.

1.3.3 Surficial sliding, Toowoon Bay Caravan Park

Another slope instability problem related to the Patonga Claystone occurred in the Toowoon Bay Caravan Park (Figure 1.4). This caravan park is located where the Patonga Claystone is exposed along the coast. The Patonga Claystone is overlain at the site by a layer of dune sand of variable thickness.

The natural slope angle of the rock exposure is about 26˚ from the horizontal. This slope angle may be just about stable. Dumping of waste materials over the crest of the slope, however, resulted in movement of both the fill and dune sand material.

1.3.4 Sewage treatment works, Charmhaven

Aeration ponds for sewage treatment at Charmhaven (Figure 1.4) were constructed in 1988. The slope cut was excavated into clay soil of medium to high plasticity, with some weathered mudstones near the base. The slope face was designed to cut at 1.5H:1V (33.7˚ to the horizontal) with a height of approximately 4 metres.

The clay was highly fissured and appears to have been derived from the Patonga Claystone. The fissures had led to an overall reduction in the effective shear strength, and it was concluded that the remaining cut slope needed support. A stabilizing berm, approximately 4 metres in 11

width, with a subsoil drain, was designed to assist the stability of the cut slope.

Local or small landslides have occurred in the exposed Patonga Claystone in the past. Since the rock is slaking prone and readily erodible, it has a low-relief topographic expression. Natural slopes developed in extremely weathered Patonga Claystone are about 6˚ (McNally, 1998). These low relief areas have reduced the risk of slope instability as a result of natural equilibrium. Such natural slopes tend to be stable unless they are disturbed by human activity. Slope instability problems are expected to increase within this rock formation, however, as land use demands increase.

1.4 Aims of the study

The aims of this study have been set out as follows: 1. To determine the geotechnical properties of the Patonga Claystone, and to establish their relation to its mineral and chemical composition,

2. To identify the factors controlling the rapid slaking behaviour of this rock unit, compared to other rock units in the area,

3. To find suitable methods for evaluation of slaking prone materials, both within the Patonga Claystone and more generally for geotechnical purposes.

1.5 Research Design

To achieve these aims, the following work plan was developed:

1.5.1 Literature review

Documents on the stratigraphy, sedimentology and engineering geology of the Narrabeen Group, especially the Patonga Claystone, were studied to evaluate the geology of the unit and its related problems. Literature was also reviewed on rock slaking characteristics, including the causes of slaking and the various slake durability tests, as well as engineering geology theory and testing of rock properties in general. Clay mineralogy and the theory of X-day diffraction, including qualitative and quantitative methods, were also reviewed.

Extensive studies of any rock unit having similar geotechnical problems to the Patonga Claystone were reviewed. It was found that Keuper Marl, a Triassic red bed formation in England, has some characteristics in common with the Patonga Claystone, such as an overall red bed facies and similar geotechnical behaviour e.g. slaking characteristics (McNally and Whitehead, 1994). The geological background and geotechnical properties of the Keuper Marl (e.g. Dumbleton and West, 1966b, Chandler, 1969, Chandler and Davis, 1973, Little and Hatal, 1990) were studied in the hope that the extensive studies of Keuper Marl may aid in explaining the slaking behaviour of the Patonga Claystone.

1.5.2 Sampling program

Core samples of the Patonga Claystone from several coal exploration drill holes in the Wyong area (Figure 1.5) were used in the study, together with some outcrop samples from the nearby region.

The rock samples used in the study were grouped into mudstone and sandstone based on their grain size as seen in hand specimen. The sandstones were further classified as fine, very fine etc. using the categories defined by the Wentworth grade scale (Tucker, 2001). No further classification, however, other than by colour, was attempted for the mudstone samples.

The locations of the drill holes are shown in Figure 1.5, and outcrop samples collected from Bateau Bay (O3R) and Forresters Beach (1, 2, 3, 5R, 5G and 6) are shown in Figure 1.4.

1.5.3 Mineral composition

X-ray diffraction (XRD) and X-ray fluorescence (XRF) were used to provide qualitative and quantitative mineralogical and chemical composition data on the rock samples. Thin sections were also examined in the mineralogical study, and cation exchange capacity (CEC) was determined to provide additional data on the rock samples. Special attention was paid in the XRD study to detailed identification of the clay minerals in the rock samples. Scanning electron microscopy (SEM) was also used to identify textural and fabric features. Further details of sample preparation and instrument operating conditions are given in Chapter 3. Xplot for Windows (data display and 14

mineral identification software) and Siroquant (Rietveld- based software for quantitative mineralogical analysis) were used for the XRD studies, and Microsoft Excel was used in calculating, analyzing and evaluating the various results.

Figure 1.5: Location of drill holes and core samples and outcrop samples (modified from Coal Operations Australia Limited (COAL)).

Table 1.3: Source and description of rock samples used in the present study. See Figure 1.5 for drill hole and outcrop locations.

Hole and Sample Hole and Sample Description Description Depth(m) Number Depth(m) Number B250W300 36.6 205 F green Sandstone 165.7 130 Green VF Sandstone 39.2 211 Red Mudstone 166.4 131 Red Mudstone 40.8 212 Red Mudstone 172.2 132 Red Mudstone 44.7 213 Red Mudstone 177.3 133 Red Mudstone 51.2 214 Red Mudstone 182.8 134 Red Mudstone 55.8 215 Red Mudstone 187.9 135 Red Mudstone 58.6 216 Red Mudstone 199.4 136 Red Mudstone 62.9 217 Red Mudstone 201.6 137 Green-red Mudstone B800W300 207.8 138 F green Sandstone 6.6 310 Red Mudstone 212.6 139 Red Mudstone 13.4 311 Red Mudstone 215.3 140 Red Mudstone 14.1 312 Red Mudstone 219.7 141 Red Mudstone 19.2 313 Red Mudstone 226.8 142 Red Mudstone A800W100 238.9 143 Red Mudstone 71.2 409 Green Mudstone 246.9 144 Red Mudstone 92.2 414 Red Mudstone 251.8 145 Red Mudstone B150W400 254.6 146 Red Mudstone 156.7 501 Red Mudstone B600V900 159.5 502 Red Mudstone 39.5 203 Red Mudstone 166.4 504 F green Sandstone 16

Hole and Sample Hole and Sample Description Description Depth(m) Number Depth(m) Number 182.0 506 Red Mudstone 48.5 704 Red Mudstone 195.0 508 Red Mudstone 55.4 705 Red Mudstone 215.0 511 Red Mudstone 59.5 706 F green Sandstone 225.6 512 Red Mudstone 61.2 708 Red Mudstone 223.5 513 Red Mudstone B200W100 B200W500 31.6 801 F green Sandstone 168.7 602 Red Mudstone 58.3 809 F green Sandstone 178.7 605 VF green Sandstone 77.4 815 F green Sandstone 180.9 606 VF green Sandstone 89.9 820 F green Sandstone 186.0 607 Red Mudstone Outcrop 192.8 608 F green Sandstone Bateau Bay O3R Brown Mudstone 197.2 609 Red Mudstone Forresters Beach 1 Red Mudstone 209.4 612 F green Sandstone Forresters Beach 2 Red Mudstone 214.8 613 Red Mudstone Forresters Beach 3 Red Mudstone 226.3 615 Red-green Mudstone Forresters Beach 5R Red Mudstone B400V700 Forresters Beach 5G Green Mudstone 37.9 701 Red Mudstone Forresters Beach 6 Red Mudstone 40.7 702 M green Sandstone 44.3 703 Red Mudstone Note : Depth given represents the mid point of each sampled interval, VF – Very fine grained F – Fine grained M – Medium grained

1.5.4 Geotechnical properties

Physical properties, such as specific gravity, water absorption etc., were also used to aid the study. Slake durability tests (ISRM, 1979) and jar slaking tests (Vallejo et al., 1993) were carried out to determine the durability of the rock samples. Details of the procedures used are given in Chapter 4.1, and results are discussed in Chapter 4.2.

The uniaxial compressive strength and the indirect tensile strength (Brazilian method) were determined for the rock samples using standard methods on selected core specimens. Point load strength index tests (Standards Australia, 1993) were performed instead of uniaxial compressive tests in other cases. An ultrasonic velocity test (ISRM, 1979) was used to evaluate the elastic modulus. Testing procedures and results are discussed in Chapter 5.

1.5.5 Data evaluation

Linear regression analysis was used to search for correlations among the slaking behaviour, mineral content, chemical composition and geotechnical properties using functions embodied in the Microsoft Excel software. Qualitative relationships between clay minerals, microfabric and geotechnical properties were also evaluated, in order to develop a predictive model for slaking behaviour. The model was then compared to the observed data and checked for consistency (Chapter 6).

CHAPTER 2

GEOLOGY AND SEDIMENTOLOGY

2.1 Introduction

This chapter deals mostly with the geological setting of the Patonga Claystone exposed in the Central Coast area of New South Wales, with some details of the more general geology of the host Narrabeen Group in the Sydney Basin.

2.2 Regional Geology

The Narrabeen Group lies more or less conformably between the Permian Illawarra Coal Measures and the locally distinctive Hawkesbury Sandstone (Ward, 1971b).

Herbert (1980) has suggested that the stratigraphic sequence in the Sydney Basin accumulated by several processes of dominantly regressive sedimentation. Sedimentation in the Sydney Basin can be divided into many distinct depositional episodes, such as the Hunter Tectonic Stage, Hawkesbury Tectonic Stage, etc. The Narrabeen Group was deposited during the Hawkesbury Tectonic Stage (Herbert, 1980). It ranges in age from Late Permian to Middle Triassic, and comprises up to 800 metres of lithic conglomerate, quartz-lithic to quartzose sandstone, and red, green and grey shale.

The distribution of the Narrabeen Group, together with the Palaeozoic basement, the underlying Permian rock units and the other Triassic rock units, in the Sydney Basin is shown in Figure 2.1. Figure 2.2 shows the stratigraphic 19

sequence of the Hawkesbury Sandstone, Narrabeen Group and Illawarra Coal Measures in the South Coast area (c.f. Table 2.1).

Figure 2.1: Outcrop distribution of the Narrabeen Group (stippled) and associated rock units in the main part of the Sydney Basin (based on Ward, 1972)

Figure 2.2: Outcrops of the Hawkesbury Sandstone (top), Narrabeen Group (middle) and Illawarra Coal Measures (bottom) at Stanwell Park, north of Wollongong.

The sandstones of the Narrabeen Group consist mainly of quartz grains, rock fragments of various types, and interstitial clay, both detrital and authigenic in origin (Ward, 1971b). Small amounts of mica, siderite and feldspar are also present, the latter being particularly common in the Central Coast district (Ward, 1971b) including the main study area.

The Narrabeen Group has been subdivided differently in three separate areas, namely the Central (or North) Coast district, the Western or Blue Mountains district, and the South Coast or Illawarra district (e.g. Hanlon et al., 1953, Ward, 1971a and 1971b, Bembrick, 1983, Herbert, 1997).

Ward (1971a and 1971b) has used vertical profiles of the ratio between quartz grains and rock fragments in the 21

sandstones, based on petrographic point count techniques, as a basis for correlation of the Narrabeen Group units between these regions. Figure 2.3 shows the borehole locations used in that study, and Figure 2.4 shows a stratigraphic cross section of the Narrabeen Group between these borehole sections. The sandstones of the Narrabeen Group in the western part of the Sydney Basin and in the upper part of the sequence are mostly quartzose in composition and the ratio of quartz grains to rock fragments is high, usually exceeding 10:1. However, the Narrabeen Group sandstones in the eastern part of the basin, especially in the middle part of the sequence, have ratios between 1 and 3, dropping to less than 0.5 in the lowermost units. Ward (1971a) concluded that this lateral variation in composition is related to the provenance of the sediments, so that the gradation from west to east and north to south across the basin represents mixing of up to three different kinds of clastic debris (see Figure 1.3 and 2.4).

Figure 2.3: Location of boreholes sampled and geologic cross section line used in the study of Narrabeen Group correlation by Ward (1971b).

Figure 2.4: Stratigraphic cross section of the Narrabeen Group from Dapto in the south (Huntley DDH 8) to Wyong in the north (Ourimbah Creek DDH 5), showing correlation based on mineralogical markers (Ward, 1971b).

The Triassic rock units of the Sydney Basin, especially the Narrabeen Group, can be subdivided in the three principal outcrop areas as shown in Table 2.1. Although equivalents of both units have been referred to by earlier workers (e.g. Hanlon et al., 1953) as the Collaroy Claystone (see below), Figure 1.3, Figure 2.4 and Table 2.1 clearly show that the Bald Hill Claystone and the Patonga Claystone are quite different units occurring in different parts of the basin, and that the Bald Hill Claystone lies stratigraphically above the Patonga Claystone horizon.

Table 2.1: Rock units of the Narrabeen Group in the three different parts of the Sydney Basin (compiled from various authors).

Age Group North West South

Middle Hawkesbury Sandstone Triassic Burralow Formation Newport Upper Banks Formation Wall Terrigal Sandstone Garie Fm Formation Wentworth Falls Bald Hill Claystone Claystone Member

Patonga Lower Banks Early Claystone Wall Triassic Sandstone Bulgo Narrabeen Group Tuggerah Sandstone Formation Mount York Claystone Clifton Sub-Group Burra-Moko Stanwell Park Munmorah Head Claystone Conglomerate Sandstone Scarborough Sandstone Dooralong Caley Wombarra Shale Formation Shale Late Newcastle and Illawarra Coal Measures Permian

2.3 Geology of the Study Area

Patonga Claystone

The Patonga Claystone, forming the top of Clifton Sub- Group in Narrabeen Group (Figure 2.1), is a Triassic red bed sequence cropping out in the Central Coast New South Wales (Figure 2.5).

Despite its name, the unit contains very little claystone. It consists primarily of red brown mudstone with lesser amounts of siltstone and sandstone.

The formation now known as the Patonga Claystone was first described as the Collaroy Claystone by Hanlon et al. 25

(1953). It appears under this name in some early literature, leading to confusion between the red-brown claystones or ‘chocolate shales’ cropping out at Collaroy in the Pittwater area and the beds of the Patonga Claystone in the Central Coast or Gosford-Wyong district (e.g. Hanlon et al., 1953, Loughnan et al., 1964). The red-brown claystone outcrops at Collaroy are correlated with the Bald Hill Claystone of the Illawarra or South Coast district, rather than the Patonga Claystone (Herbert, 1970, Ward, 1971a and 1971b). In fact, the composition of the claystones at Collaroy (dominated by well-ordered kaolinite) is identical with that of the Bald Hill Claystone, and contrasts with the red-beds of the Wyong area (Patonga Claystone). The Patonga Claystone contains significant amounts of quartz, feldspar and rock fragments as well as illite, illite/smectite and kaolinite, whereas the Bald Hill Claystone is characterized by abundant well- ordered kaolinite and a marked deficiency of quartz (Loughnan et al., 1964; Ward, 1971a).

The first description of the unit now known as the Patonga Claystone is represented by the definition of the type section for the Collaroy Claystone by Hanlon et al. (1953) based on the strata encountered in the Windeyer’s Hawkesbury River Bore (Figure 1.4) at depth of 237 to 373 metres. Later correlations, however, recognized that this section was a stratigraphically lower unit to the claystone exposed at Collaroy, and the name Patonga Claystone was given to the unit in the Hawkesbury Bore by J. Stuntz (McElroy, 1969).

This description of the type section of the Patonga Claystone is reproduced in Table 2.2. Note that depths are 26

listed in feet as originally reported by Hanlon, et al. (1953).

Table 2.2: Type section of the Patonga Claystone in Windeyer’s Hawkesbury River Bore, from 776’0” to 1,224’6” (234.98 to 370.77 m) (Hanlon, et al.,1953).

Thickness Ft. In. ‘Chocolate’ and grey shale 26 0 ‘Chocolate’ shale 12 6 Grey shale 2 0 Shale and sandstone 5 6 Sandstone 4 10 ‘Chocolate’ shale 58 2 ‘Chocolate’ shale and sandstone 3 0 ‘Chocolate’ shale 7 0 Grey shale and sandstone 9 9 Sandstone 12 6 Soft grey shale 1 6 ‘Chocolate’ shale 13 0 ‘Chocolate’ shale and sandstone 7 6 ‘Chocolate’ shale 49 9 Grey shale 1 0 ‘Chocolate’ shale 13 0 Fine grey sandstone 2 0 ‘Chocolate’ shale 23 3 Sandstone 18 3 ‘Chocolate’ shale 12 6 ‘Chocolate’ and grey shale 8 9 Grey shale and sandstone 4 6 Sandstone 10 0 ‘Chocolate’ and grey shale 35 6 ‘Chocolate’ shale 1 0 Grey shale 3 6 Sandstone 10 0 ‘Chocolate’ and grey shale 14 0 Sandstone 1 6 Grey shale 9 9 Sandstone 14 9 ‘Chocolate’ shale 4 6 Grey shale and sandstone 15 0 Sandstone 10 0 Shale and sandstone 3 0 Sandstone 9 6 ‘Chocolate’ and grey shale and sandstone 10 3 448 6 Total 135.80 m

The Patonga Claystone comprises a red bed facies, up to 150 meters thick, consisting of siltstone, mudstone, claystone and fine sandstone. The sandstones are light grey-green to pale grey in colour on fresh surfaces and brown in colour on weathered surfaces. The sandstones are lithic in composition, and make up some 20% of the 27

formation thickness. The finer grained units are composed mainly of silt-sized quartz, with clay minerals, mainly kaolinite, illite, and mixed layer illite/smectite. The red colour is imparted by a relatively small proportion (2- 7%) of haematite.

Figure 2.5: Distribution of formations within the Narrabeen Group in the Central Coast area (based on Whitehead and McNally, 1995).

The Patonga Claystone consists essentially of four different rock types or lithofacies (ECNSW, 1983a, 1983b):

(i) Red brown mudstone. This is the most common rock type in the Patonga Claystone, and has variable proportions of clay and silt size particles.

(ii) Fine to medium grained sandstone. The colour of this sandstone varies from grey to green. The sand grains consist mainly of quartz and green rock fragments.

(iii) Grey to green mudstone – siltstone. This lithofacies is slightly coarser grained than the red brown mudstone described above. It characteristically has a gradational boundary with the grey green fine-grained sandstone, and may contain ‘clasts’ of red brown mudstone.

(iv) Finely interbedded siltstone/sandstone. This lithofacies or mixture of rock types is usually grey to green in colour.

Since the mudstone of the Patonga Claystone rapidly disintegrates when exposed to moisture change, it is difficult to observe any bedding or sedimentary structures within the mudstone outcrop. So, most information of this type reported in the literature refers to the sandstones of the unit instead. As a result of rapid disintegrate and weathering, the mudstones in turn become a soil cover to the Patonga Claystone, and outcrops are only well exposed along the coast.

Figures 2.6, 2.7 and 2.8 show the general features of the interbedded sandstones, siltstones and mudstones of the Patonga Claystone cropping out in the Central Coast area. 30

Figure 2.9 shows the weathering features and Figure 2.10 shows the presence of plant remnants in sandstone of the rock unit.

Mineralogically the formation consists of quartz, feldspar, haematite, chlorite, illite and kaolinite, with minor anatase and calcite occurring in some samples (Section 2.10). More details of the different rock types, based mainly on X-ray diffraction data, are given in Chapter 3.

0 10 20 30 cm

Figure 2.6: General view of the Patonga Claystone exposed on the coast at Forresters Beach in the Central Coast area.

Figure 2.7: Interbedded sandstone (light) and mudstone (dark) in the Patonga Claystone at Forresters Beach.

0 10 20 30 cm

Figure 2.8: Interbedded sandstone (strongly outcropping bands) and mudstone in the Patonga Claystone at Forresters Beach.

Figure 2.9: Weathering of siltstone in the Patonga Claystone.

Figure 2.10: Root remnant in sandstone of the Patonga Claystone.

2.4 Sedimentology and Depositional Environment of the Patonga Claystone

The major lithologies of the Patonga Claystone, sandstone and mudstone, represent differences in the mode of deposition. The coarser grained sediment was deposited by a more energetic flow, while the fine-grained sediment was deposited essentially from still water. The consistency in the mineral assemblage indicates the same basic source of sediments throughout the formation.

Palaeocurrent studies by Ward (1972) indicate that the river systems depositing the middle part of the Narrabeen Group in the Central Coast area flowed mainly from the north or northwest to the south or southeast. This includes data from the Tuggerah Formation at Toowoon Bay, immediately below the Patonga Claystone horizon. Similar studies by McDonnell (1980) also showed a south to southeasterly palaeocurrent trend in the lower part of the overlying Terrigal Formation.

Cross-beds in the Patonga Claystone itself also suggest that the streams flowed from the northwest and therefore probably had their source within more northwesterly parts of the New England Fold Belt (Uren, 1980). The general fining upwards sequence in the Narrabeen Group from the Munmorah Conglomerate to the Patonga Claystone may signify a decline in topographic relief within the source area, and reflect greater sediment transport distances as deposition continued (Uren, 1980).

Herbert (1993) describes the depositional environment of the Patonga Claystone as shallow marine, lagoonal and tidal deltaic. However, no marine fossils have been found 34

in the Patonga Claystone. Moreover, the red-brown colour in the Patonga Claystone indicates an oxidizing environment rather than a more reducing marine depositional environment. The shallow marine, lagoonal and tidal deltaic depositional conditions proposed by Herbert (1993) may therefore, as an alternative, be represented by a more lacustrine environment or an alluvial fan outwash plain, similar to that described for parts of the Triassic sequence in the adjoining Gunnedah Basin by Jian and Wars (1996).

Uren (1980) studied the deposition of the Clifton Sub- group. Because the colour mottles commonly cut across lithological boundaries, she suggested that the development of the red coloration post-dated the main sediment deposition processes.

Red brown is the dominant colour in mudstone with some green gray mudstone while green gray is dominant in sandstone unit. The red brown colour is caused by ferric iron (Fe3+) in hematite while the green gray colour is caused by ferrous iron (Fe2+) in illite and chlorite (Tucker, 1991; Boggs, 1992). The red colour may be original (e.g derived from the sediment source area) or it may have been developed by alteration after deposition. Tucker (1991) describes development of red colour (hematite) in sediments after deposition through an ageing process from a hydrated iron oxide precursor, and suggests that a green colour (illite, chlorite) may be originally developed (e.g. inherited from the sediment source) or developed later through reduction of hematite or its precursor. In the prevalence of reducing condition, the iron is present in the more soluble ferrous state and if 35

incorporated into clays, it will impart a green colour to parts of red bed sequences.

Field observation of outcrops and drill core samples in the present study commonly show colour transgressions across bedding planes, the presence of horizontal green gray colour changes in red brown mudstone (Figure 2.11), and colour changes along joint planes. These changes indicate the influence of post depositional processes in controlling the red or green colour of the sediment. It would seem to be that the Patonga Claystone was initially deposited in an oxidizing environment, resulting in the overall reddish colour. Later on the conditions changed to a reducing environment and, together with the bleaching effect of groundwater, the colour changed in places to green.

Figure 2.11: Colour mottling in sandstone of the Patonga Claystone, Forresters Beach, NSW.

The coarser grained materials in the Patonga Claystone are generally grey green colour, while the finer grained materials are red brown in colour. Colour mottling usually occurs along joint planes. In other words, the development of a grey green colour is related to higher permeability materials, while the red brown colour is related to less permeable rocks. The rock colour can thus be explained, at least partly, in terms of porosity and ground water flow. The post depositional colour change resulted from circulating fluids, i.e. in high porosity rock water could circulate easily, which reduced ferric iron (Fe3+) in the sediment to ferrous iron (Fe2+).

Boggs (1992) states that sediment deposited under reducing conditions should have a higher organic content, since organic matter is not destroyed so rapidly under reducing conditions. Plant remains (Figure 2.12) have been noticed in some beds of the Patonga Claystone. However, overall the organic content as determined in the sediments is quite low, in both the red and the green coloured units. The presence of plant remains in sediment with a low overall organic content further suggests that the bulk of the rock unit was originally deposited in oxidizing conditions.

Figure 2.12: Plant remains in the Patonga Claystone, Forresters Beach.

Thin sections were used for further evaluation of rock characteristics in the present study. Sandstone and mudstone samples were prepared with thicknesses of 0.03 mm as suggested by standard method (Tucker, 2001). As might be expected, it was found that the sandstones and mudstones differ from each other in terms of both grain size and mineral content. The sandstones studied contain fine sand with silt size particles, while the mudstones contain still finer grains. Both samples contain quartz, feldspar and clay minerals. However, chlorite is more abundant in the sandstones while iron oxide is dominant in the mudstones as a cementing material. Most of the grains are angular to sub-angular with poor sorting. Details of the thin sections studied are included in Appendix A.

Palaeocurrent studies suggest that the source of sediments was mainly to the northwest, most likely from the New England Fold Belt (Uren, 1980). Microscope studies suggest that the sediments supplied for the deposition of 38

the Patonga Claystone was derived mainly from igneous rocks, and that deposition was close to the sediment source. This is indicated by the presence of tourmaline, together with the angular to sub-angular grains in the sediments themselves.

The relative abundance of quartz and the mixture of different clay minerals in the mudstones of the Patonga Claystone distinguish the unit from the main red-brown claystone sequences of the Narrabeen Group in the South Coast area, the Stanwell Park Claystone and the Bald Hill Claystone (Table 2.1). As indicated by Loughnan et al. (1964) and Ward (1971a), the mudstones of the Stanwell Park and Bald Hill Claystones contain very little if any quartz, and are dominated respectively either by mixed-layer illite/smectite or by well-ordered kaolinite.

Palaeocurrent studies by Ward (1972) indicate that the Stanwell Park and Bald Hill units were derived from a localised source area rich in mafic to intermediate volcanics, located to the east of the present coastline south of Sydney. The Patonga Claystone, however, seems to have been derived from a source located to the northwest, probably representing the same source area in the New England Fold Belt that produced the other Narrabeen Group sediments in the northern part of the basin.

Figure 2.13: Thin section of sandstone from the Patonga Claystone, showing chlorite, altered feldspar, and opaque minerals (plane polars, left and crossed polars, right - 50x).

As discussed more fully in Chapter 3, X-ray diffraction analysis was performed on both red brown and greenish grey mudstone samples to confirm the existence of hematite in the red-brown materials (Figure 2.11). Diffractograms of selected samples are shown in Figure 2.14. The top diffractogram in Figure 2.14 represents greenish grey mudstone while the bottom one represents red brown mudstone. It is clear that the greenish grey sample (top in Figure 2.14) does not show any peaks due to hematite while the red brown mudstone (bottom in Figure 2.14) indicates the existence of hematite (H in the figure) in the sample. Other minerals contained in these Patonga Claystone samples are quartz, feldspar (albite), clay minerals (chlorite, illite, mixed layer illite-smectite and kaolinite), and anatase (as well possibly as zircon). More details of these mineralogical determinations are given in Chapter 3.

Cu K alpha radiation

Figure 2.14: X-ray diffractograms of greenish gray (top) and red brown (bottom) mudstone samples from the Patonga Claystone, Forresters Beach, Central Coast – NSW.

CHAPTER 3

MINERALOGICAL and CHEMICAL ANALYSIS

3.1 Introduction

Mineralogical analysis can be defined as the identification of minerals and determination of mineral proportions in rock materials. By contrast, chemical analysis is based on determining the composition of a rock material in terms of the chemical elements present.

Several techniques can be employed in mineralogical and chemical analysis. For example, optical methods (microscopy) in either transmitted or reflected light, X- ray diffraction, scanning electron microscopy and thermal analysis for mineralogical studies, and X-ray fluorescence spectrometry, atomic absorption spectrophotometry and electron probe microanalysis for chemical investigations.

Microscopic techniques involve identification of minerals based on their optical properties with the aid of polarized light. The rock sample is typically prepared in the form of a thin section with a thickness of 0.03 mm (30 µm) (Tucker, 2001), or in some cases as a polished section.

Electron probe microanalysis (EPMA) and scanning electron microscopy (SEM) techniques provide chemical composition data for very small volumes at the surface of polished thin sections of rock or mineral mounts (Long, 1967, Welton, 1984, Trewin, 1988, Velde, 1992).

Thermal analysis techniques involve monitoring the changes, either physical or chemical, that occur with increases in temperature (McLaughlin, 1967, Velde, 1992). Three types of analysis are used: differential thermal analysis (DTA), thermogravimetric analysis (TGA) and thermal dimensional analysis (TDA). The DTA technique monitors changes in temperature as heat is evolved or absorbed by a sample, compared with the temperature of an inert reference standard (McLaughlin, 1967, Velde, 1992). The thermo-gravimetric analysis (TGA) technique measures the weight change in a substance as it is being heated. The TDA technique determines change in length of a pressed sample as it is heated. Samples used in these analyses are in form of ground materials.

X-ray fluorescence spectrometry (XRF) provides data on the chemical composition of rock materials. The XRF process is based on the emission of secondary X-rays when a sample is bombarded with a primary X-ray beam. The wavelength and intensities of the emitted radiation depend on the elements present. The emitted energy at different wavelengths is detected and processed, and then recorded as intensities or pulses per second. The chemical composition of the rock substance is obtained, based on calibration against standards with known proportions of particular elements. Analysis can be performed on samples prepared either as pressed pellets or fused glass disks (Norrish and Chappell, 1967, Fairchild et al., 1988, Velde, 1992).

X-ray diffraction (XRD) is one of the main tools used in mineralogical analysis, especially of fine-grained materials. The process involves the constructive and destructive interference of x-rays when they are diffracted from the internal crystal planes of minerals (Eslinger and 43

Pevear, 1988, Hardy and Tucker, 1988, Moore and Reynolds, 1997). Each mineral has its own diffraction pattern, i.e. its own set of d-spacings between atomic layers, when analysed in this way. Rock samples exhibit a combination of diffraction patterns under XRD analysis, representing a blending of the individual patterns of the various minerals present. The d-spacings are used in identifying the minerals in the sample (qualitative analysis), or combined with peak intensities in some way to provide a more quantitative analysis.

The XRD technique is mostly used on randomly powdered samples. More specific information on the nature of the clay minerals, however, can be achieved from oriented aggregates of the isolated clay fraction. A sedimentation technique is used to separate the powdered rock particles on the basis of their effective size (settling velocity), to achieve concentration of the clay (< 2 µm) size fraction (Hardy and Tucker, 1988, Velde, 1992, Moore and Reynolds, 1997). The concentrated clay fraction is then prepared as an oriented film by one of several techniques, and the oriented clay aggregate is subjected to additional XRD studies after various treatment processes (Hardy and Tucker, 1988, Moore and Reynolds, 1997).

Selection of the method or combination of methods to be used depends on the type of information required (e.g. chemical or mineralogical analysis). Methods based on powdered samples, such as XRD, XRF etc, often have an advantage over rock thin sections because a representative sample of a larger mass can be more easily obtained.

Mineralogical analysis is important in a number of different types of geological studies, including 44

geotechnical applications (Jumikis, 1979, Attewell and Farmer, 1982, Grainger, 1984, Franklin, 1989, Moore, 1991, Bell, 1992b, Tugrul and Zarif, 1999). One of the main aims of the present study was to evaluate the factors controlling slaking behaviour in the Patonga Claystone. Chemical and mineralogical analyses, especially the latter, are important tools in such an evaluation.

3.2 Clay and the Clay Minerals

3.2.1 Definitions

The word ‘clay’ is used as a lithological term, and also as a particle-size term in the mechanical analysis and description of sedimentary rocks and soils. As a lithological term ‘clay’ is difficult to define precisely, because of the wide variety of materials that have been called clays. In ceramics, clay is defined as a substance that characteristically becomes plastic when wet or when it contains a certain amount of water. In the engineering sense the term ‘clay’ also implies a natural, earthy, fine- grained material that develops plasticity when mixed with a limited amount of water. The plasticity index, representing the range of moisture contents over which a soil displays plastic properties, is a significant property in civil engineering and soil mechanics, and is widely used in soil classification for engineering purposes.

“Clay minerals” are a group of hydrous aluminosilicate minerals formed by weathering, diagenesis or hydrothermal processes. Minerals of this group are the key components of many fine-grained natural substances, and typically give the materials their plastic properties when wet. 45

“Clay substance” is defined as a material made up of both clay and non-clay mineral components, but where the clay minerals are important in determining its overall characteristics. Clay substance, defined in this way, has a similar meaning in both ceramics and civil engineering contexts. It is the clay minerals within these substances that mainly control their particle size, plasticity and other characteristics.

As a particle-size term, there is some degree of conflict about the upper limit of the “clay” size. In geological terms, clay sized sediment is defined as the material finer than 1/256 mm (approximately 4 µm), following the Wentworth scale (Grainger, 1984, Graham, 1988), whereas in soil mechanics and geotechnics, the tendency is to use 2 µm as the upper limit of the “clay” size grade (Bowles, 1978 and Truitt, 1983). An upper limit of 2 µm is frequently about the optimum size for separating the clay and non-clay minerals in natural materials (Grim, 1968, Velde, 1992, Moore and Reynolds, 1997). Following geotechnical rather than sedimentological practice, upper limit of 2 µm is used in this study for the clay grade, unless otherwise specified.

An understanding of clay mineralogy is important in the understanding of processes such as chemical weathering, sediment diagenesis and hydrothermal alteration. In the engineering geology field, clay minerals can determine the characteristics of soil, weathered rock and other materials. Some geological features, such as joint filling material, can affect particular engineering projects. This material may be of relatively minor significance in the geological sense, but quite important in engineering geology. For example, if joint filling material contains 46

expandable clay minerals and is exposed to moisture, it may cause problems in slope stability or stability of an excavation. The nature of the infill material may also affect the shear strength. Joints or fractures filled with chlorite, for example, have relatively low friction angles and shear strength compared to joints filled with quartz (Brady and Brown, 1985).

The purpose of the present study was to investigate the influence of mineralogical factors on the slaking characteristics of a particular fine-grained sedimentary rock unit. The clay and non-clay minerals making up the different lithologies of the Patonga Claystone were therefore determined as a major part of the thesis study. Qualitative and quantitative interpretation of these minerals using X-ray diffraction was an important part of the investigation, although other methods, such as chemical analysis and cation exchange studies, were also used.

3.2.2 Classification of the Clay Minerals

Two basic types of atomic structures, tetrahedral and octahedral molecular units, are represented in the crystalline clay minerals (Grim, 1968, Carroll, 1974, Eslinger and Pevear, 1988 and Moore and Reynolds, 1997).

Tetrahedral units: Tetrahedral units consist individually of four relatively large oxygen atoms or hydroxyl molecules, grouped in a tetrahedral arrangement around a smaller central silicon atom (Figure 3.1a). They typically form two-dimensional sheets, with three oxygen atoms at the base of each tetrahedral unit shared among the three adjacent tetrahedra, while the fourth or apical oxygen points upward 47

in the direction normal to the base (Figure 3.1b). The basic unit is often referred to as an SiO4 unit, and the sheet-like arrangement as a tetrahedral sheet.

Figure 3.1: a) single tetrahedron and b) sheet structure of tetrahedrons arranged in a hexagonal network (Eslinger and Pevear, 1988).

Octahedral units: Octahedral units consist of a metal ion (Al+3, Fe+2, Fe+3 or Mg+2) surrounded by six oxygen or hydroxyl units arranged at the points of an octahedron (Figure 3.2a). As with the tetrahedral units, they typically form two- dimensional sheets (Figure 3.2b), within which O or OH components are shared by adjacent octahedra. They may, however, also form double chains of octahedral units, as in the fibrous clay minerals such as palygorskite and sepiolite.

Figure 3.2: a) single octahedral unit and b) sheet structure of the octahedral units (Eslinger and Pevear, 1988).

Classifications of the clay minerals are primarily based on the crystal structure of the material. Some non- clay minerals such as talc and pyrophyllite, with a sheet- like structure similar to some of the clay minerals, are also included in some discussions of clay mineral structures. The basic groups of clay mineral can be classified as follows:

1. The Amorphous Clay Minerals or Allophane. Allophane commonly occurs in soils formed on volcanic ash (Moore and Reynolds, 1997). These clay mineral substances show no apparent crystal structure when studied by x-ray diffraction, i.e. they do not produce peaks indicating detectable crystallinity in x-ray diffraction studies. This makes very difficult to identify allophane positively in the study of clay substances.

Clays identified as amorphous by XRD may exhibit crystal structure using other techniques, and hence they should be more specifically referred to as X-ray amorphous clay minerals.

2. Layered Clay Minerals. These have an internal sheet- like or phyllosilicate structure. They can be subdivided into:

a) Two-layer clay minerals. The simplest phyllosilicate clay mineral structure combines one octahedral and one tetrahedral sheet to form a 1:1 layer structure (Figure 3.3 kaolinite). The unshared oxygen at the apex of each tetrahedral unit becomes an integral part of the adjacent octahedral unit to form the two layer sheet-like structure.

b) Three-layer clay minerals. This phyllosilicate group has a structure that consists of two tetrahedral sheets and one octahedral sheet combined to form a 2:1 layer structure. The structure is similar to that of the 2 layer group, but has another tetrahedral sheet, inverted with respect to the first covalently bonded to the other side of the octahedral sheet (Figure 3.3 mica/illite and Figure 3.4 smectite).

Ionic substitution can occur in these minerals, especially the three layer types. As an example aluminium may replace silicon in the tetrahedral layer, or Mg may replace Al in the octahedral layer. This leads to a nett negative charge on the basic silicate structure. The negative charge is balanced by the presence of cations, or a combination of cations and water, often between adjacent 3-layer units.

c). Four-layer clay minerals. This sheet structure consists of two tetrahedral and two octahedral layers that form the aluminosilicate lattice. The structure is similar to that of the 2:1 layer clays, with an additional sheet of octahedral units between each 3-layer sheet (Figure 3.4 50

chlorite). Such minerals are said to have a 2:1:1 layer structure.

3. Fibrous Clay Minerals. The fibrous clay minerals do not have a sheet like structure like most other clay minerals. They have an inosilicate structure, with tetrahedral units linked into double chains. The chains are then joined by individual octahedral units to form the unit cell.

Figure 3.3: Kaolinite (left) and mica/illite (right) structures (Eslinger and Pevear, 1988). 51

Figure 3.4: Chlorite (left) and smectite (right) structures (Eslinger and Pevear, 1988).

3.2.3 Interstratified or Mixed-layer Clay Minerals

There are some kinds of clay minerals that have crystals built up from a combination of two or more individual types of clay minerals (e.g. illite, smectite or montmorillonite, chlorite) in a vertical stacking sequence. These clay minerals are called ‘mixed-layer’ or ‘interstratified’ clay minerals. Mixed layering results from the fact that bonding is strong within individual layers but weak between layers, and the different types of layers in clay minerals have nearly identical configurations of tetrahedral oxygens bounding their outer surfaces (Eslinger and Pevear, 1988), so that they can fit together relatively well.

Theoretically, all kinds of crystal layers can combine to form mixed layer clay minerals. The most common mixed layer clay minerals, however, are illite-smectite (I/S), smectite-chlorite and chlorite-vermiculite (Reynolds, 1980, 52

Eslinger and Pevear, 1988 and Moore and Reynolds, 1997). An example of a three component mixed-layer clay mineral would be illite-smectite-chlorite.

Mixed layering may be either regular or irregular in form. The stacking sequence in the regular mixed layer clay minerals has a specific or repeated pattern, whereas a random stacking pattern occurs in the irregular mixed layer clay minerals.

Classification of the layered clay minerals is summarized as shown in Table 3.1.

Table 3.1: Classification of layered clay minerals (Moore and Reynolds, 1997).

Layer Group Subgroup Species Type Serpentine-kaolin Serpentine (Tr) Chrysotile, antigorite, (z∼0) lizardite, berthierine, 1:1 odinite Kaolins (Di) Kaolinite, dickite, nacrite, halloysite Talc-pyrophyllite Talc (Tr) (z∼0) Pyrophyllite (Di) Smectite Tr smectites Saponite, hectorite (z∼0.2-0.6) Di smectites Montmorillonite, beidellite, nontronite Vermiculite Tr vermiculites (z∼0.6-0.9) Di vermiculite Illite Tr illite? (0.6>z<0.9) Di illite Illite, glauconite 2:1 Mica (z∼1.0) Tr micas Biotite, phlogopite, lepidolite Di micas Muscovite, paragonite Brittle mica Di brittle micas Margarite (z∼2.0) Chlorite Tr, Trchloritea Common name based on (z variable) Fe2+, Mg2+, Mn2+, Ni2+ Di, Di chlorites Donbassite Di, Tr chlorite Sudoite, cookeite(Li) Tr, Di chlorite No known examples 2:1 Sepiolite-palygorskite Inverted ribbons (with z variable) a2:1 layer first in name of chlorite, Tr = trioctahedral and Di = dioctahedral; z = charge per formula unit.

The layer charge (x) in Table 3.1 is the net negative charge per formula unit that may exist on a 2:1 layer when the total anionic negative charge per formula unit is greater than the total cationic positive charge, assuming complete ionization (Bailey, 1988). A net negative charge can arise from: 1. substitution of other ions (R3+ or R2+) for Si4+ in tetrahedral units, 2. substitution of other ions for Al+3, Mg+2 etc (R1+ or R2+ for R2+ or R3+, respectively) in octahedral units, 3. the presence of octahedral vacancies, or 4. dehydroxylation of OH to O (Bailey, 1988).

Consider the case of saponite, a member of the smectite group, having a formula (Carroll, 1970) of:

+3 +2 (Mg2.92Fe .08Fe .03)(Si3.40Al.60)O10(OH)2.

O10(OH)2 causes a negative charge of –22. This should be neutralized by a positive charge of +22 in balancing the formula. However, the total positive charge calculated is not +22; the positive charge is:

(2.92*2)+(.08*3)+(.03*2)+(3.40*4)+(.60*3) = 21.54.

Such a combination of positive and negative charge causes a negative charge of 0.46. This is within the range of X values that is listed for saponite in Table 3.1. A clay mineral type having an X value of zero is one with either no substitution or complete substitution in its lattice structure.

3.2.4 Geotechnical Properties and Clays

The geotechnical or engineering properties of a rock substance may be at least partly related to the clay-size particles, especially the nature and relative proportions of the clay minerals in the material.

Clay-mineral components. Certain clay minerals, even if present in very small proportions, may exert a considerable influence on the geotechnical attributes of a clay substance. For example, the presence of small proportions of smectite in a clay substance may produce a material very different from another clay substance with the same composition in all ways except for the absence of smectite (Grim, 1962). An example of the influence of 55

smectite content on Atterberg limit properties of clay substances is shown in Table 3.2.

Table 3.2: Plastic limit and liquid limit of pure clay minerals and mixtures (modified from Grim, 1962).

Clay minerals Plastic limit Liquid limit Smectite 82 118 Illite 25 36 Kaolinite 37 58 Illite +10%smectite 36 58 Illite +5% smectite 26 61 Kaolinite+10% smectite 33 65

The plastic limit is the lowest moisture content at which a clayey soil will behave like a plastic solid, while the liquid limit indicates the maximum moisture content it can absorb before it begins to behave like a viscous liquid.

The nature of any mixed layer components, the morphology of the clay minerals and the chemical composition of the clay components may also have considerable influence on the properties of clays, clay substances and rock materials (Grim, 1962).

Non-clay minerals. The non-clay minerals are generally coarser than about 2 µm in size. However, many non-clay minerals, such as quartz and feldspar, may also occur as clay size particles (Moore and Reynolds, 1997). The nature of the non-clay minerals, and their abundance, may have an influence on the strength properties of rock materials, including parameters such as quartz percentage, (Attewell and Farmer, 1982, Farmer, 1983, Brady and Brown, 56

1985), quartz to feldspar ratio (Tugrul and Zarif, 1999), and quartz and feldspar size (Tugrul and Zarif, 1999).

Ion-exchange properties. Ion (especially cation) exchange properties are of great fundamental and practical importance in the investigation of clay minerals (Taylor and Spears, 1970, Velde, 1992). The clay minerals, especially mixed layer clay minerals, and some of the organic material found in clay substances may have a significant ion-exchange capacity (Grim, 1962, Taylor and Spears, 1970, Velde, 1992). Intraparticle swelling of mixed-layer clay minerals during periods of saturation followed by desiccation causes the breakdown of mudrocks containing significant proportions of expandable mixed- layer clay minerals (Taylor and Spears, 1970).

The exchangeable sodium percentage (ESP), expressed as the percentage of exchangeable Na+ to cation exchange capacity, is directly related to the amount of dispersion in the mudrocks (Taylor and Smith, 1986). This parameter could be used as a measure of the tendency for dispersion in water of Ca-, Na-smectites and Ca-, Na-illites (Taylor and Smith, 1986).

Organic material. The presence of organic material may also have an influence on the swelling and shrinking due to wetting or drying of clay substances. Some of the organic material may have a significant ion-exchange capacity (Grim, 1962, Taylor and Spears, 1970, Velde, 1992). The ion-exchange capacity may cause swelling of the clay substances on water absorption. This may cause rock containing organic matter to deteriorate with changes in humidity.

Due to its potential for decomposition, soil containing a high proportion of organic matter should not be used in an embankment construction. The decomposition, in turn, may cause subsidence or instability problems.

The above discussion indicates the significance of mineralogical analysis in the study of geotechnical properties, which has been identified as the primary concern of the present study.

As already stated, both microscopic and XRD techniques can be used in mineralogical analysis of soil and rock samples. Both methods have advantages and disadvantages in this field of study.

Advantages of microscopy techniques

1. Grain shape and grain size distribution can be determined, as well as mineralogical composition, in both qualitative terms (from optical properties) and quantitative terms (from point count analysis). 2. The nature of the depositional environment may be established in some circumstances, based also on other field evidence.

Disadvantages of microscopy techniques

1. Only small portion of the rock sample is used in thin section preparation, which may not fully represent the total rock mineralogy. 2. Difficultly is encountered in identification of fine grained and opaque minerals. 3. A skilled technician is required for sample preparation, especially from slake-prone materials. 58

Advantages of the XRD technique

1. The material studied can be representative of the entire soil or rock sample. Even though the XRD technique uses only a small amount of powdered material, a small but representative sample can be obtained from larger masses by using riffle boxes or a cone and quartering method. 2. The method is fast, reproducible and requires a less skilled operator for data collection. 3. Analysis can be performed on fine grained rock substances and opaque minerals. 4. The method can be applied to the study of clay minerals, including both qualitative and quantitative analysis. 5. Samples are easy to prepare for XRD analysis.

Disadvantages of the XRD technique

1. Grain shape and size distribution cannot be determined. 2. Limitations on identification and quantitative determination of minerals in low concentrations, and for X- ray amorphous materials. 3. Mineral identification, and also quantitative analysis, need skilled or highly trained personnel.

The rock samples examined in the present study were mainly fine grained materials containing opaque minerals (hematite), as indicated by their reddish brown colour. Clay minerals were also the major objective of the study. Therefore the XRD technique was selected over traditional microscope methods. However, a number of thin sections were also studied to confirm the findings of the XRD, and 59

to evaluate textural features and modes of mineral occurrence.

3.3 X-ray Diffraction Techniques

3.3.1 Background Theory

X-ray diffraction (XRD) has become a basic tool in mineralogical analysis of sediments, especially fine- grained sediments and clay minerals, due to the limitations of optical microscope methods. The planes in the crystals are too close together to be seen with light rays, but can be studied by shorter wavelength electromagnetic radiation in the X-ray band.

A full account of XRD analysis can be obtained from standard textbooks (e.g. Moore and Reynolds, 1997; Hardy and Tucker, 1988). Figure 3.5 shows the alignment of a typical X-ray diffractometer system.

Figure 3.5: Schematic representation of the geometry of an X-ray diffractometer (Hardy and Tucker, 1988).

The X-rays are first collimated to produce a subparallel beam, and then diverged by a divergence slit. The divergent beam is then directed at the sample. The sample 60

is rotated at a regular speed (e.g. one degree 2θ per minute). When the X-ray beam hits one of crystal planes in the sample at an appropriate angle, the atomic units that form the plane act as a diffraction grating and produce diffracted beams. Constructive interference occurs when the diffracted beams from a set of planes emerge from the sample in phase. The conditions under which this occurs are governed by Bragg’s Law (Figure 3.6), i.e.:

λ = sind2n θ where: n = integer, λ = wavelength of the X-rays, d = lattice spacing in angstroms, and θ = angle of diffraction.

The diffracted beam emerging from the sample is passed through a receiving slit and collimator. At this stage, the scatter slit is used to reduce any scattered X-rays before entering the X-ray detector. In systems using a monochromator, as shown in Figure 3.5, the beams pass from the receiving slit to the crystal monochromator and then to the detector.

Figure 3.6: An illustration of Bragg’s Law (Hardy and Tucker, 1988).

Bragg’s Law can be explained as follows:

In Figure 3.6, a, a1 and a2 are lattice arrays of atoms regarded as an infinite stack of parallel, equally spaced planes with a separation of d. X-Y and R-S represent incident and reflected rays respectively. The path difference can be expressed as:

sind +θ sind θ = sind2 θ = ∆

A constructive interference of the refracted rays will occur when the path difference (∆) is equivalent to an integral number, i.e. at particular θ angles. At other angles the path differences are not equal to one or more whole wavelengths, and the diffracted beams from any adjacent planes produce a destructive interference pattern. A peak is registered by the X-ray detector over the angle at which constructive interference occurs, but only background radiation is recorded at angles where destructive interference takes place.

3.3.2 XRD Equipment and Setting

A Philips PW 3710 based X-Ray diffractometer (Figure 3.7), coupled with Philips APD software, was used in the present study for mineralogical analysis.

Figure 3.7: Philips PW 3710 X-ray diffractometer used for the present study.

The XRD data were gathered using Cu K alpha radiation (λ = 1.5418 Å), generated using a tube voltage of 40 kV and a filament current of 30 mA. A graphite curved crystal diffracted beam monochromator was incorporated in the X-ray path. System configuration and data collection were managed using Philips APD software, with a basic configuration as follows:

Divergence slit - 1° Receiving slit - 0.1° (with monochromator) Start angle - 2° 2θ End angle - 60° 2θ (powder mounts) - 30° 2θ (oriented aggregates) Step increment - 0.04° 2θ (powder mounts) - 0.02° 2θ (oriented aggregates) Counting time/step - 2 seconds (powder mounts) - 0.5 seconds (oriented aggregate)

The diffractogram trace of each scan was saved automatically under a specific file name, using the Philips .rd file format.

Output from the APD system consisted of digital data files (.rd files), which provided data to allow plots of diffracted x-ray intensity against 2θ angles (Figure 3.8) for mineral identification and qualitative interpretation (Section 3.4.1), and also for subsequent processing and manipulation. Software used for XRD interpretation included XPlot for Windows for mineral identification (Section 3.4.2) and Siroquant for quantitative interpretation of mineral percentages (Section 3.7.2).

3.3.3 Sample preparation

Two types of sample preparation were employed in the present study, randomly oriented mounts of whole rock powders and oriented aggregate mounts of separated clay fractions. The whole rock powdered samples were used for study of bulk mineralogy, including both the clay and non- clay minerals contained in the rock specimen, whereas the oriented aggregates were used to study the clay minerals in 64

greater detail. Because the powdered samples were randomly oriented, both basal d-spacing (001) as well as hkl d- spacing (other than 001) peaks could be recognized. By contrast, in the oriented aggregates, where the clay size particles were allowed to settle slowly and develop a preferred orientation, only the basal d-spacing (001) could be recorded (but at an enhanced level) (Eslinger and Pevear, 1988, Hardy and Tucker, 1988, Velde, 1992, Moore and Reynolds, 1997).

Representative samples of each specimen were obtained by passing the crushed rock through a riffle box. Sufficient quantity of each sample was prepared for both mineralogical and chemical analyse (XRD and XRF analysis). Representative portions of the crushed rocks were then ground for approximately 1 minute by using TEMA ring- grinding mill. If the crushed samples were too moist, the samples were oven dried before the grinding process.

In whole-rock analysis, a sample of each powdered rock was packed into a glass-backed sample holder with an aluminium frame (Gibbs, 1971, Hardy and Tucker, 1988, Velde, 1992, Moore and Reynolds, 1997). Care was taken not to put too much pressure on the powder during packing, as excess pressure could cause preferred orientation of platy particles such as the clay minerals (Moore and Reynolds, 1997). Since preferred orientation of cleavage or crystal faces could enhance or suppress particular XRD peaks, this could lead to errors in interpretation.

Clay size fractions for oriented aggregate study were obtained by sedimentation methods based on Stokes’ Law (Gibbs, 1971, Hardy and Tucker, 1988, Velde, 1992, Moore and Reynolds, 1997). To avoid problems with flocculation 65

of the clay particles, a small amount of Calgon (sodium hexametaphosphate) was added to each suspension (Moore and Reynolds, 1997). The settling time for particles finer than 2 µm was taken as about 4 hours, at 20° C, for a withdrawal depth of 5 cm (Hardy and Tucker, 1988). About 50 ml of the suspension was taken at the 5 cm depth, after 4 hours settling time, and then centrifuged for 10 minutes at a speed of 2000 revolutions per minute. The rotation forced the clay fraction to settle to the bottom of the centrifuge tube, and thus concentrated the clay size particles. Excess water was decanted from the tube, after which the remaining water and clay were mixed and dropped on to a glass slides by using a pipette technique. Two slides were prepared for each clay sample. The slides were left to become air-dried before the XRD analysis process.

Complete analysis of the rock samples, including detailed analyses of the clay minerals, were obtained by XRD after some or all of the following treatments: a) random powder, whole rock sample; b) oriented aggregate, <2µ fraction, air-dried; c) oriented aggregate, <2µ fraction, glycol saturated; d) oriented aggregate, <2µ fraction, heated to 400° C for approximately 1 hour; e) oriented aggregate, <2µ fraction, heated to 600° C for approximately 1 hour;

Processes b), c), and d) were used for detailed study of the clay mineral components, while random powder (treatment a) was used in determining the mineral content (both clay and non-clay minerals) of each whole rock sample. Some oriented aggregate samples were heated to 66

600° C (treatment e) for approximately 1 hour, to distinguish between kaolinite and chlorite.

As already stated that two glass slides were prepared for each rock sample. The first slide was used for XRD analysis in the air-dried state. The other slide was left in a glycol bath overnight and analyzed in the glycol- saturated state. After that the slide saturated with glycol vapour was heated at 400° C for 1 hour, and subjected to another XRD analysis. The glycol and heated patterns were analyzed from the same slide to avoid any differences in peak intensity that might arise from different sample mounts. The air-dried pattern was used as preliminary guide to the nature of the clay minerals, and to supplement the glycol and heated patterns.

3.4 Mineral Identification from Powder XRD Data

3.4.1 Using Philips APD Software

The “Pattern Treatment” function of the APD software was used to define the d-spacing of each individual peak on each diffractogram. Figure 3.8 is modified from the print out after this routine to show peak intensity at particular 2θ angles. This type of output was used to give a preliminary indication of the minerals present, particularly in the powdered rock samples. Note that a square root scale is used, for the intensity axis in the graphic plot of the diffractometer trace, to enhance the low intensity peaks.

Cu K alpha radiation

Figure 3.8: Peak positions and peak intensities used in identifying of mineral content.

The peak positions of quartz were used to check on the accuracy of peak positions for the other minerals present. Moore and Reynolds (1997) suggest that the quartz pattern 68

can act as a built in internal standard, and suggest adding quartz to the sample if it is not present, in order to calibrate the diffractometer trace. Errors in peak position detected by this calibration may arise from sources such as misalignment of the diffractometer, incorrect sample position or loose compaction of the powdered sample. The position of the quartz pattern can be used to correct for any such ‘zero error’ problems.

In Figure 3.8, the peak at 3.337 Å (26.69° 2θ) with a relative intensity of 100 % was identified as being due to quartz. The second-strongest peak of quartz at 4.25 Å (20.89° 2θ) was also checked and found to be present, along with the other quartz peaks at 2.45 Å (36.60° 2θ), 2.27 Å (39.52° 2θ), 2.23 Å (40.35° 2θ), 2.12 Å (42.50° 2θ), 1.98 Å (45.86° 2θ) and 1.82 Å (50.19° 2θ).

The peak at 3.18 Å (27.99° 2θ) was selected to identify next in this particular sample because it had highest intensity apart from quartz. This peak, together with peaks at 4.02 Å (22.07° 2θ), 3.76 Å (23.64° 2θ), 2.98 Å (29.99° 2θ), 2.93 Å (30.52° 2θ) and 2.85 Å (31.40° 2θ), gives a good match to the albite XRD pattern, and so these peaks were used to indicate the presence of albite.

The remaining peaks were then selected and the same procedure applied to identify the respective minerals until all peaks could be referred in same way to a mineral XRD pattern.

3.4.2 Using XPlot for Windows

More definitive mineral identification was established by processing each .RD file produced from the Philips APD system using the separate XPlot for Windows software produced by Raven (1996). This software includes a routine for automatically finding peaks on the diffractometer trace and displaying their d-spacings, and for manually identifying additional peaks and their d-spacings, if necessary, where they have been omitted by the ‘peak find’ routine. The peaks identified by this process were then submitted to a search–match routine, with a series of user- defined options, to identify the minerals present by comparison to the electronic version of the ICDD powder diffraction database.

After running this search-match software, a list of possible minerals was displayed. From this list, decisions were made based on the geological context of the sample to select the minerals that have best fit to the peak positions and intensity values. Electronic correction of peak positions for ‘zero errors’ in the diffractogram can also be made, if necessary, by calibrating the trace against a known mineral in the pattern such as quartz.

An example of output from the XPlot for Windows software used in mineral identification for the project is shown in Figure 3.9.

Figure 3.9: XPlot for Windows screen showing mineral identification output.

3.5 Clay Mineral Characteristics from Oriented Aggregate X- ray Diffractrometry

3.5.1 Clay Mineral Identification

More specific information on the clay minerals in the samples was obtained from the XRD traces of oriented aggregates, prepared as indicated in Section 3.3.3. These enhance the basal (00l) spacings more than randomly oriented powders (Carroll, 1970, Hardy and Tucker, 1988, Velde, 1992, Moore and Reynolds, 1997). In the clay minerals the hkl peaks (peaks other than those due to the basal d-spacing) are not very diagnostic, because most clay minerals have similar structures in the X and Y crystallographic directions. Only the stacking pattern along the Z direction differs from clay mineral to clay mineral. XPlot for windows is less useful in identifying 71

of clay minerals from oriented aggregates. This is because XPlot for windows also provides hkl peak positions that may be misleading in identification of the clay minerals.

From the Bragg equation (nλ = 2dsinθ), l may be substituted for n and the equation re-arranged to give lλ/2d = sin θ. If θ is small (less than 40°) the angle may be substituted for its sine and this equation can be rewritten as θ = l*(constant). This equation implies that at small diffraction angles the members of an 00l series for one mineral are equidistant (Figure 3.10). In other words d(002), d(003) and d(004) are d(001)/2, d(001)/3 and d(001)/4 Å respectively. For example, if clay mineral has d(001) of 14 Å, then d(002) and d(003) of this clay mineral will be located at 7 Å (14/2), 4.7 Å (14/3) and 3.5 Å (14/4) respectively (Moore and Reynolds, 1997). This method is useful in locating rational sequences of basal d- spacing in the study of clay minerals (see section 3.5.3).

Figure 3.10: Equidistance of basal (001) peaks (Moore and Reynolds, 1997).

In line with generally accepted practice, identification of clay minerals for the study was based on 72

the fact that they expand with organic molecule absorption and collapse on heating. For example, smectite will expand (to a larger d-spacing) on uptake of glycol and collapse (to a smaller d-spacing) after heating at 400 °C for 1 hour. The oriented aggregate mounts for the present study were run firstly in the air-dried condition, after which slide was left in a glycol bath overnight at room temperature and an XRD trace run on the slide again. Finally, the clay slide was heated at 400° C for at least 1 hour prior to a third XRD run. The diffractograms after each treatment were then compared to the changes as listed in Table 3.3, to identify the clay minerals present.

Table 3.3: Basal crystallographic (d{00l}) spacing of principal clay minerals after various treatments (Carroll, 1970).

Mineral Basal d spacing (00l) Glycolation effect Heating effect Kaolinite 7.15 Å (001); 3.75 Å No change Become amorphous at 550-600 °C Illite 10 Å (001), broad, other No change (001) noticeably basal spacings present more intense on but small heating as water layers are removed Smectite 15 Å (001) and integral (001) expands to 17 Å At 300 °C (001) series of basal spacings with rational becomes 9 Å sequence of higher orders Chlorite, Mg-form 14 Å (001) and integral No change (001) increases in series of basal spacings intensity; <800 °C shows weight loss but no structure change Chlorite, Fe-form 14 Å (001) less intense No change (001) scarcely than in Mg-form; increases; integral series of basal structure spacing collapses < 800 °C Mixed-layer Regular, one (001) and No change unless an Various Minerals integral series of basal expandable component spacings is present

Random, (001) is Expands if smectite Depends on addition of individual is a constituent minerals present minerals and depends on in inter-layerd amount of those present mineral

It can be seen from Table 3.3 that kaolinite, illite and chlorite are not affected when saturated with glycol or heated, i.e. the (001) reflections are the same for air 73

dried, glycol and heated patterns, except that particular peaks may be more intense in some cases. The effect of glycol saturation is most dramatic with smectite; this mineral expands from 15 Å (air dried) to 17.3 Å (glycolated) and collapses to 10 Å on heating.

Mixed-layer illite/smectite (I/S) can be distinguished from illite by comparing the peak-height-intensity ratio (Ir) for I(001)/I(003) in the air dried and glycolated patterns (Moore and Reynolds, 1997), i.e.:

)003(/)001( driedairII Ir = II )003(/)001( glycolated

If smectite (expandable) layers are absent, Ir should equal 1 (one). If smectite layers are present it is greater than 1. If very fine grained quartz is present this relation is unusable, since quartz (101) and illite (003) have a common d-spacing value of 3.34 Å.

3.5.2 The nature of the XRD patterns from the oriented aggregate samples studied

Figure 3.11 shows the variation of clay minerals encountered in this study.

Figure 3.11: Variation in clay mineral XRD traces encountered in this study in a) glycolated and b) heated conditions.

Figure 3.11 shows the difference between glycolated (left) and heated patterns (right) of selected clay fractions. The names of the interpreted clay minerals are listed above the peak positions.

3.5.3 Qualitative interpretation

The clay minerals in the samples were identified from oriented aggregate mounts, which enhanced the intensity of the 00l diffraction peaks. The samples were analyzed in an 75

air-dried state, after glycol saturation and after heating at 400° C. Variations in 001 d-spacing caused by the different treatments were checked against standard patterns, such as the data published by Carroll (1970) and Hardy and Tucker (1988), as summarized in Table 3.3.

The diffractograms of a typical oriented aggregate sample from the Patonga Claystone are shown in Figure 3.12.

Cu K alpha radiation

Figure 3.12: Diffractogram of preferred oriented aggregate, sample number 511, under air-dried (bottom), glycolated (middle), and heated (top) conditions.

A small proportion of very fined grained quartz was identified in the oriented aggregate mounts of most samples, by peaks positioned at d-spacings of 4.26 and 3.35 Å (Figure 3.12).

A peak at a d-spacing of 7.15 Å appears in all of the patterns. The rational sequence of peak positions was checked by using the equidistance method (Section 3.5.1). 76

The second order of this d-spacing is about 3.58 Å (7.15/2). From the unchanged characteristics under various treatments and the 1st and 2nd order d-spacing, this mineral was interpreted as kaolinite (Carroll, 1974; Hardy and Tucker, 1988; Moore and Reynolds, 1997).

Peaks at around 14.2 Å, with a rational sequence of 7.1, 4.8 and 3.54 Å are also encountered in every XRD pattern, relatively unchanged after the various treatments. These are taken to indicate the presence of chlorite (Carroll, 1974; Hardy and Tucker, 1988; Moore and Reynolds, 1997; Ward, 1997). Generally chlorite can be distinguished from kaolinite by the peaks at 3.54 Å (4th order of chlorite) and 3.58 Å (2nd order of kaolinite) (Carroll, 1974; Hardy and Tucker, 1988; Moore and Reynolds, 1997). However, due to the small proportion of chlorite contained in the rock samples studied, the chlorite peak is often superimposed on the kaolinite peak, as indicated by peak locations at 3.56 Å (Figure 3.13) (c.f. Figure 3.12 and 3.20). This makes it difficult to distinguish chlorite and kaolinite individually in quantitative interpretation of oriented-aggregate data.

The broad peak at 10.57 Å on the air-dried trace is interpreted as a combination of two peaks, one at 10.11 and one at 10.57 Å. The peak at 10.11 Å does not vary with glycol or heat treatment, and has a 2nd order peak at 5 Å; this is identified as representing illite. The peak at 10.57 Å in the air dried state expands, as indicated by a small hump between the 10.01 and 14.35 Å peaks, in the glycol trace. The intensity of the peak at 10.01 Å (due to illite) is also reduced with the glycol treatment, due to loss of diffraction effects from the mixed-layer material.

The hump between 10 and 14 Å disappears after heating to 400˚ C. This indicates an expandable clay mineral (Table 3.3) (Carroll, 1974; Hardy and Tucker, 1988; Moore and Reynolds, 1997). This expandable clay mineral is not pure smectite, because smectite should expand to 17 Å after glycol treatment (Carroll, 1974; Hardy and Tucker, 1988; Moore and Reynolds, 1997). The 10 Å peak is more intense after heating, suggesting the existence of illite in the mixed layer clay; therefore the peak is interpreted as representing a mixed-layer clay of illite and smectite (Hardy and Tucker, 1988; Moore and Reynolds, 1997). The type of mixed layering is defined as irregular because the peaks have no rational sequence (Carroll, 1974, Eslinger and Pevear, 1988, Moore and Reynolds, 1997). The pattern produced by this mixed layer I/S, in the absence of chlorite, illite and kaolinite, can be seen from Figure 3.17.

Since kaolinite has its 1st and 2nd order peaks at 7.16 and 3.58 Å and chlorite has its 2nd and 4th order peaks at 7.10 and 3.54 Å respectively (Carroll, 1974, Hardy and Tucker, 1988, Moore and Reynolds, 1997), some difficulty may occur in interpretation of a mixture of kaolinite with (especially) Fe-rich chlorite (Carroll, 1974, Moore and Reynolds, 1997). Fe-rich chlorite gives a weak intensity for the d(001) and d(003) peaks that may look similar to the pattern of kaolinite; in other words such a sample could contain only chlorite, only kaolinite or a combination of both minerals (see Figure 3.13). Moore and Reynolds (1997) suggest methods to distinguish the two minerals by either boiling the sample in 1 N HCl for 2 hours to dissolve most chlorites, placing the sample in a reagent that forms a strong hydrogen bond to expand the kaolinite, or heating the clay slide at 550° to 600° C for 78

1 hour making kaolinite XRD-amorphous (Hardy and Tucker, 1988, Moore and Reynolds, 1977). The method of heating at 550° to 600° C for 1 hour was used for more specific kaolinite and chlorite identification in this study.

Cu K alpha radiation

Figure 3.13: Kaolinite and high Fe-chlorite (Moore and Reynolds, 1997).

From the above procedures, the clay minerals kaolinite, illite and mixed layer illite-smectite were identified in the rock samples used in this study. Chlorite, confirmed by heating to 600 ˚C, was also found in most of the samples. Only 11 out of 61 samples do not contain chlorite. Quartz and feldspar were the main non- clay minerals, encountered almost in every Patonga Claystone sample.

3.5.4 Estimation of illite and smectite proportions in mixed layer clay minerals

Various attempts have been made by different researchers to estimate the relative proportions of smectite and illite in mixed layer illite-smectite (I/S), 79

for example the methods described by Reynolds (1980) and Sŕodón (1980, 1981). Reynolds (1980) has provided a large number of calculated patterns for various types of mixed layered clay minerals. Figures 3.14a and b show examples of randomly interstratified and ordered mixed layer (I/S) clay minerals respectively. From these figures, peak migration near 5 Å is particularly diagnostic of mixed- layer (I/S) clays. Reynolds (1980) has produced a table to aid in determining the proportion of illite in mixed-layer clays, reproduced in Table 3.4.

a). b).

Figure 3.14: Glycolated patterns of randomly interstratified (a) and ordered (b) mixed layer (I/S) with a range of interstratified illite/smectite percentages, CuKα radiation (Reynolds, 1980).

The number in Figure 3.14a and b indicates the proportion of illite in the mixture. Note the migration of the peak at around 5.2 Å (17° 2θ with CuKα radiation) when this proportion changes.

Table 3.4: Determining the composition of mixed layer (I/S) from the d(002) peak (Reynolds, 1980).

% Illite in Random (R=0) Ordered (R=1) Illite/Smectite d (Å) d (Å) 0 5.62 5.62 10 5.59 5.59 20 5.57 5.55 30 5.54 5.50 40 5.50 5.44 50 5.44 5.39 60 5.37 5.34 70 5.28 5.28 80 5.16 5.22 90 5.07 5.09 100 5.01 5.01

From the above table, in a randomly interstratified I/S, if the d(002) peak occurs at 5.54 Å the mixed layer clay probably has around 30% illite in its structure.

Sŕodón (1980, 1981) has proposed a graphical method of estimating the proportion of smectite in a mixed layer I/S, both in regularly and randomly stacked patterns, as shown in Figure 3.15. This is based on the 2θ angle that produces key peaks under glycol saturation using CuKα radiation.

To use this graph in estimating the proportion of illite or smectite in the mixed layer (I/S), two peaks are measured in °2θ, one between 15.4 and 17.8 °2θ and one between 25.8 and 27.0 °2θ, using CuKα radiation (or between 5.75 and 4.98 Å, and between 3.45 and 3.30 Å). Note that large, low angle peaks are not used, because the low angle peaks may suffer interference from other clay minerals (Sŕodón, 1980, 1981). The point represented by these two peaks is plotted on the relevant graph. The plotted point 81

is then transferred to the right, parallel to the diagonal lines, allowing the percentage of smectite or illite to be estimated.

Figure 3.15: Graphical method for estimating illite content of mixed layer I/S with random (a) and ordered interstratification (b), using CuKα radiation (modified from Sŕodón, 1980).

Both the above methods are similar, except that Sŕodón adds a high angle peak at about 26–27 °2θ (CuKα radiation) to the consideration. Sŕodón’s curves probably provide the most precise determinations of illite and smectite proportions in mixed layer I/S, provided all the necessary peaks can be clearly defined. Care is needed because 82

quartz also has a peak near 26 °2θ (CuKα radiation), and quartz also occurs in many clay size fractions.

3.5.5 Compare I/S proportion to Newmod

Newmod is computer software, written by Reynolds (1980), for creating synthetic diffractograms of different clay minerals, either as single mineral traces or as combinations of clay mineral patterns. Diffractograms of pure smectite and illite produced by Newmod are shown in Figure 3.16, and mixed layer I/S with different proportion of illite in Figure 3.17.

The XRD traces of I/S with different proportions of illite, produced by Newmod, were compared to the XRD traces of the I/S in the rock samples studied, to estimate the relative proportions of illite and smectite in the mixed layer clay minerals.

2 Theta (degree) Cu K alpha radiation Figure 3.16: Illite (top) and glycolated smectite (bottom), modified from Newmod software.

A typical illite pattern (Figure 3.16) shows d(00l) peak positions at 10.06, 5.01 and 3.33 Å, whereas a glycolated smectite pattern shows peak position at 17.03, 8.52, 5.63, 4.23 and 3.38 Å.

The effect of different proportions of illite in a randomly interstratified illite/smectite on the glycol- saturated d-spacing values is illustrated in Figure 3.17. With a high proportion of illite, e.g. 90% illite in the interstratified mineral (Figure 3.17 top), the diffractogram resembles the illite pattern (Figure 3.16 top). With increasing proportions of smectite in the crystal (Figure 3.17 middle and bottom), the expanding behaviour allows the smectite component to be more clearly defined. An interstratified structure with 70% illite in the I/S shows a peak with a relatively high intensity at a d-spacing of 13.13 Å. The same peak is of lesser intensity and shifted to a lower spacing when the proportion of illite is increased to 80%. The peak at around 5 Å is also affected by these differences in proportion of the two clay minerals. If the proportion of illite in the mixture decreases from 90 to 80 and 70%, the d-spacing (002) shifts from 5.06 to 5.17 and 5.28 Å respectively (c.f. Table 3.4 and Figure 3.17).

Note that peak at 3.3 Å (Figure 3.17) is less affected by these differences in the illite proportion. The peak at 3.3 Å may thus be less useful in estimating the proportions of illite and smectite in the mixed layer material, especially if fine-grained quartz is present, since quartz has a d-spacing also of 3.35 Å (Griffin, 1971, Moore and Reynolds, 1997). Also note that Reichweite = 0 (randomly interstratified) is used in these calculations because of the non-integral d-spacing patterns indicated by the peak 84

positions in the mixed-layer clay patterns of the samples studied.

2 Theta (degree) Cu K alpha radiation

Figure 3.17: Various proportions of illite in mixed layer I/S (glycolated pattern) from Newmod.

Comparison of Figure 3.18 (from the rock samples studied) to Figure 3.17 (calculated from Newmod) shows that there is no peak at a d-spacing of 17.03 or 8.52 Å on the diffractogram derived from the samples studied. This indicates the absence of pure smectite. However, a hump exists between 14 and 10 Å in the glycolated pattern that disappears in the heated pattern, along with an increased intensity of the 10 Å peaks (Figure 3.18). This is taken as representing an expandable mixed-layer clay consisting of illite and smectite in the samples studied.

A typical glycolated diffractogram of the rock samples studied is shown in Figure 3.18 (bottom). When compared to the traces generated by Newmod, the peak at 12 Å is of relatively low intensity, but the peaks at 10 and 5 Å are very close to the first and second order of the illite 85

peak, indicating a very high illite proportion in the mixed layer clay mineral. The XRD trace in Figure 3.18 (bottom) looks similar to the traces of I/S with 80 to 90% illite in Figure 3.17, as well as in Figure 3.14. The d-spacing is also close to that of illite-rich I/S in Table 3.4, suggesting that illite makes up about 80 to 90% of the illite-smectite interstratification in the samples studied.

2 Theta (degree) Cu K alpha radiation Figure 3.18: Typical glycolated (bottom) and heated (top) diffractograms of rock samples from the study area used in defining the proportions of individual clay minerals in mixed layer I/S.

An attempt was made to use the method for estimating the illite proportion in the I/S proposed by Sŕodón (1980) (Figure 3.15). Unfortunately, this method could not be used with confidence, because of interference from illite and quartz in the 3.42 to 3.29 Å peaks (Sŕodón, 1980, Moore and Reynolds, 1997).

Variations in the proportion of illite in the mixed layer I/S of the studied rock samples are shown in Figure 3.19.

2 Theta (degree) Cu K alpha radiation

Figure 3.19: Typical glycolated diffractograms of rock samples from the study area, showing variation of illite percentage in the mixed layer I/S.

3.5.6 Quantitative Interpretation of Oriented Aggregates

3.5.6.1 Quantitative assessment of clay mineral proportions

Estimation of individual clay mineral proportions is significant in engineering geological study of rock materials (Sections 3.2.1 and 3.2.4). Several methods had been used in semi-quantitative and quantitative interpretation of clay mineral proportions, e.g. methods based on relative peak heights, peak areas and addition of other minerals (e.g. boehmite) to the sample.

For rapid, reproducible semi-quantitative results, the method proposed by Weir et al. (1975, discussed by Hardy 87

and Tucker, 1988) is particularly useful for comparative purposes. In this method the intensities of the individual clay components are measured on an oriented mount after various treatments (air dried, glycol solvated, and heated to 375 and 550 °C) in order to isolate the clay components, and the sum normalized to 100%.

I ()kaolinite I (chlorite) + ()(illiteI + I smectite )+ = %100 5.2 0.2

The peak intensity (I) of each clay mineral is measured above background. The divisors 2.5 and 2.0 are used respectively to correct for the stronger X-ray responses of kaolinite and chlorite, relative to illite and smectite (Hardy and Tucker, 1988). The disadvantage of this method is that an error in one component causes an error to another component with the normalization process.

If a truly quantitative assessment is required, a more rigorous approach by an introduction of internal standard or mineral spikes must be adopted. A material such as boehmite (γ-AIOOH), which has a similar mass absorption coefficient and X-ray response to the clay minerals but a separate diffraction pattern, can be used. This method was proposed by Griffin (1954, as discussed by Hardy and Tucker, 1988). A known amount of boehmite (generally 10% by weight) is added to mixtures of standard clay minerals to produce calibration charts of mineral percentages against the relative intensity of the measured diffraction line to that of the 10% boehmite diffraction line (Hardy and Tucker, 1988). The disadvantage of this method arises from (1) difficulty in satisfactorily blending the platy particles into the mixture, and (2) variability of 88

composition and degree of crystallinity within the clay mineral groups.

Use of commercial mixing/grinding devices can alleviate the first problem. However, the second problem can only be overcome by preparing calibration curves from the actual clay minerals under investigation.

The method proposed by Griffin (1971), which is similar to that described by Weir et al. (1975), was used in the present study to estimate the percentage of each clay mineral in the clay fractions of the various samples studied. This method was considered to provide a practical approach in routine work for a large number of samples. One of the advantages of using this method arises from the ease of integration with the Philips APD software used in the XRD data gathering process. The in-built “peak search” routine provided by the Philips APD software gives a direct measure of peak intensity (above background) for each individual XRD peak.

Peak heights above background level at 7 Å and 10 Å were measured from the glycolated and heated patterns of each oriented aggregate sample. The percentages of the different clay minerals were then calculated by the following equations: ⎛⎞D ⎜⎟ ⎝⎠2.5 %(KC+= ) * 100 ⎛⎞D ⎜⎟C + ⎝⎠2.5 E % K = + )CK(%* + FE % = + − K%)CK%(C %(IM+= ) 100 − %( KC + ) 89

⎛⎞D A * ⎜⎟B %*%()IIM=+⎜⎟ ⎜⎟C ⎝⎠

%%()%MIMI=+− where: A = height of the 7 Å peak in glycolated trace, B = height of the 10 Å peak in glycolated trace, C = height of the 7 Å peak in heated trace, D = height of the 10 Å peak in heated trace, E = height of the 3.58 Å peak in heated trace F = height of the 3.54 Å peak in heated trace K = kaolinite, C = chlorite, I = illite, and M = expandable clay.

The height of the 7 Å peak was divided by 2.5 to compensate for the difference of diffraction intensity between kaolinite (+ chlorite) and the 10 Å illite and mixed layer (I/S) peaks (Griffin, 1971; Ruan and Ward, 2001). The disadvantage of this method is that the presence of any other minerals and/or amorphous material is not taken into account.

3.5.6.2 Clay Mineral Percentages from Oriented Aggregates in the Present Study

The percentages of the different clay minerals in each sample were estimated from the oriented aggregates of the clay fractions by the method of Griffin (1971). Although chlorite has a 4th order peak at a d-spacing at 3.54 Å and kaolinite has a 2nd order peak with a d-spacing at 3.57 Å, 90

kaolinite and chlorite could not be estimated separately by this method in the present study. Both minerals have superimposed peaks at around 3.57 Å (Figure 3.20). This probably reflects the presence of only a very small proportion of chlorite in the samples studied.

2 Theta (degree) Cu K alpha radiation Figure 3.20: Traces of the d(004) chlorite XRD peak at 3.54 Å and the d(002) kaolinite peak at 3.57 Å.

The glycolated pattern in Figure 3.20 indicates the presence of well-defined chlorite (004) and kaolinite (002) peaks, and thus individual peak heights can be measured separately. However, in the heated pattern (Figure 3.20), there is no distinct peak from which to clearly determine the chlorite (004) intensity.

Quantitative interpretations of the clay mineral percentages from the oriented aggregate studies are listed in Table 3.5.

Table 3.5: Percentages of clay minerals in <2 µm fraction by method of Griffin (1971).

Sample %(K+C) % I % M Sample %(K+C) % I % M 130 25 38 37 414 29 33 38 131 27 32 40 501 23 37 40 132 18 41 41 502 19 37 44 133 17 35 48 504 23 34 43 134 14 36 49 506 24 28 48 135 23 30 48 508 21 22 56 136 21 29 50 511 27 29 44 137 23 28 49 512 24 25 52 138 24 24 52 513 22 20 58 139 16 30 55 602 29 39 32 140 18 25 57 605 26 28 46 141 25 46 29 606 25 36 38 142 17 39 43 607 19 21 61 143 14 49 37 608 36 24 40 144 18 31 51 609 20 21 59 145 22 37 41 612 58 18 23 146 20 30 50 613 21 28 50 203 24 40 36 615 22 28 50 205 36 31 33 701 27 37 36 211 20 36 44 702 33 31 36 212 16 36 48 703 38 45 17 213 18 32 50 704 33 32 35 214 15 29 55 705 42 32 26 215 20 36 43 706 47 28 26 216 19 34 47 708 30 31 39 217 19 34 47 801 61 21 18 310 14 29 57 809 52 23 25 311 18 31 51 815 50 22 28 312 27 35 38 820 36 30 33 313 18 32 50 O3R 34 27 40 409 33 26 41 Remarks:- K : Kaolinite; C : Chlorite; I : Illite and M : Mixed layer I/S or expandable clay minerals.

Average, maximum, and minimum values of these clay mineral percentages are listed in Table 3.6.

Table 3.6: Statistical values of clay mineral content in studied samples.

K + C I M Average 26 31 43 Maximum 58 47 61 Minimum 14 18 17

The most abundant clay mineral evaluated from the oriented aggregate is the mixed layer I/S, with an average value of about 43% for the full range of samples studied. Kaolinite plus chlorite and mixed layer I/S have wide ranges between their respective minimum and maximum values.

Clay mineral contents based on rock type are shown in Table 3.7.

Table 3.7: Clay mineral contents based on rock type.

Mudstone Sandstone

K + C I M K + C I M Min 14 20 17 23 18 20 Max 42 47 61 58 34 52 Average 23 32 45 40 27 33

The mudstone and sandstone samples from the Patonga Claystone contain different percentages of these individual clay minerals. The mudstone samples, on average, are richer in mixed layer I/S, while the sandstone samples are richer in kaolinite plus chlorite. The average values for the illite content are approximately equal for both the mudstone and sandstone samples. More detail of this clay 93

mineral variation is discussed in the bulk mineralogy section below.

Table 3.6 shows that kaolinite plus chlorite ranges from 14 to 58% of the clay minerals encountered in the studied rock samples. The highest proportion was found in samples 612 and 801, and the lowest proportion was found in sample 143 (Figure 3.11 and Table 3.5).

The illite in the clay fractions, as shown in Table 3.6, has a narrow concentration range, varying from 18 to 47% of the clay (<2 µm) fraction. The highest proportion of illite was found in mudstone sample number 143 (Figure 3.11 and Table 3.5).

The concentration of mixed layer I/S varies from 17 to 61% of the clay fraction. The lowest proportion was found in sandstone sample number 801, while the highest proportion was found in mudstone sample number 609 (Figure 3.11 and Table 3.5).

The chlorite content is quite low compared to the other clay minerals. The presence of chlorite is mostly indicated by a small hump at around 14 Å, except for sample numbers 203, 409, 612 and 801. These samples are sandstone and mudstone with some greenish mottles, and have relatively strong 14 Å peaks.

3.6 Chemical Analysis

X-ray fluorescence spectrometry was used to obtain data on the chemical composition of the rock samples studied. This technique is widely used (e.g. Andreozzi et al., 1997, Peuraniemi et al., 1997, Ward et al., 1999a and 94

1999b, Ruan and Ward, 2001) in chemical data gathering, for a range of geological purposes.

3.6.1 X-ray Fluorescence Spectrometry

3.6.1.1 Methodology

X-ray fluorescence spectrometry (XRF) is a standard technique in hard-rock petrology. It is also widely used for whole rock analysis of mudrocks, less often for sandstones, and rarely for carbonates and evaporite materials (Fairchild et al., 1988). XRF is ideal for major and minor element determination, such as Si, Al, Mg, Ca, Fe, K, Na, Ti, S and P, and also for trace elements, such as Pb, Zn, Cd, Cr and Mn.

The XRF technique is based on analyzing the secondary radiation emitted when a sample is bombarded with high energy X-rays (Figure 3.21). The X-ray beam is usually directed upon the sample at an incident angle of about 60°, and the fluorescent radiation is observed at an angle of about 30° from the sample surface (Vanden Heuvel, 1965). The detector converts the energy of the secondary X-rays into electrical impulses, which are in turn amplified and recorded as intensity or pulses (counts) per second.

The wavelengths and intensities of the emitted radiation depend on the elements present. Measurement of the intensity of characteristic radiation for a particular element gives a value reflecting the concentration of that element in the sample. A calibration curve is produced by measurement of the emissions from appropriate standards, and the emissions from the unknown sample are compared to the calibration data. 95

Figure 3.21: Schematic diagram of unit for measuring X-ray fluorescence (Vanden Heuvel, 1965).

For whole rock analysis, samples may be prepared as either pressed pellets (briquettes) or fused discs. The fused disc method was used in this study, because it is considered to be better for major element analysis (Fairchild, et al., 1988).

As with the XRD study, powdered rock samples were used as the starting point for fused disc preparation. A mass of 0.84 grams of each rock sample was mixed with 4.5 grams of flux and 0.06 grams of ammonium nitrate. This mixture was fused at 1050˚ C, and then cast into a disc of about 35 mm diameter. The major elements were determined by using a Philips PW 2400 XRF instrument, with Philips processing software (Figure 3.22).

Figure 3.22: Philips PW 2400 XRF analyzer with PW 2150 sample changer, used in the present study.

CO2 and H2O were driven off by reactions during the fused disc preparation. The mass proportion lost in this way was determined as the loss on ignition (LOI). The procedure involved heating the oven-dried powdered rock sample at the same temperature used to prepare the fused disc (1050° C) for 2 hours. The percentage of mass lost was calculated from the difference in the sample weight before and after heating, relative to the original oven- dried weight.

3.6.1.2 Results

Fifteen rock samples were selected for XRF analysis, covering materials ranging from high to low in slake durability index. The results are outlined in Table 3.8.

Table 3.8: Chemical analysis of selected rock samples by XRF methods.

203 205 414 504 506

SiO2 60.01 64.11 62.86 63.83 60.00 TiO2 0.85 0.79 0.86 0.85 0.86 Al2O3 17.79 17.16 16.61 16.28 18.40 Fe2O3 7.49 5.05 5.47 6.18 8.41 MnO 0.06 0.07 0.12 0.08 0.04 MgO 2.23 1.76 2.31 1.70 1.34 CaO 0.34 0.26 0.53 0.31 0.24 Na2O 1.37 1.91 1.88 1.65 1.00 K2O 2.88 2.55 2.24 2.49 2.56 LOI 4.75 4.28 4.55 4.33 5.21

512 513 602 606 612

SiO2 61.70 59.58 63.65 60.12 63.36 TiO2 0.83 0.78 0.82 0.82 0.89 Al2O3 17.70 19.20 17.44 17.40 16.92 Fe2O3 6.57 7.51 5.48 8.09 6.02 MnO 0.05 0.04 0.05 0.07 0.06 MgO 2.02 1.37 1.63 1.91 2.00 CaO 0.28 0.24 0.26 0.30 0.28 Na2O 1.75 1.21 1.04 1.36 2.24 K2O 2.60 2.96 2.86 2.78 1.70 LOI 4.56 5.14 4.86 4.71 4.43

615 701 801 815 O3R

SiO2 59.95 60.34 68.51 65.74 63.27 TiO2 0.79 0.87 0.78 0.72 0.79 Al2O3 18.05 17.78 15.45 16.64 17.82 Fe2O3 8.55 8.24 3.75 4.85 4.51 MnO 0.04 0.04 0.06 0.04 0.05 MgO 1.46 1.65 1.53 1.33 1.60 CaO 0.24 0.35 0.26 0.22 0.25 Na2O 1.18 1.08 1.91 2.25 2.01 K2O 2.85 2.40 1.83 2.27 2.80 LOI 4.81 5.04 4.04 3.88 5.41

These chemical composition data are statistically evaluated in Table 3.9.

Table 3.9: Statistical evaluation of chemical composition determined by XRF of selected samples.

Composition Range % Average %

SiO2 59.58-68.51 62.47

Al2O3 15.45-19.20 17.38

Fe2O3 3.75-8.55 6.41 MnO 0.04-0.12 0.06 MgO 1.33-2.31 1.72 CaO 0.22-0.53 0.29

Na2O 1.00-2.25 1.59

K2O 1.70-2.96 2.52

TiO2 0.72-0.89 0.82 LOI 4.17-5.41 4.73

SiO2 is the most abundant oxide encountered in the studied rock samples, with an average value of about 62%.

The second most abundant oxide is Al2O3. The combination of SiO2 and Al2O3 make up about 80% of the total oxides.

The chemical results show a relatively narrow range of values, except for Fe2O3, which ranges from 3.75 to 8.55%. This narrow range of chemical composition possibly indicates that the same sediment source continuously supplied the sediments to be deposited. However, the variation of Fe2O3 may suggest some sort of post depositional process impacting on the sediment deposit.

The variation in chemical composition with rock type is listed in Table 3.10. From this comparison, the proportion of SiO2 in the mudstone samples is significantly lower than that in the sandstone samples. However, the mudstones contain more Al2O3, Fe2O3 and K2O than the sandstones. Differences in the abundance of quartz, clay minerals and hematite between mudstone and sandstone 99

samples may be responsible for this. This is discussed further in conjunction with the quantitative XRD analysis in section 3.7.5. The other oxides are approximately constant between the mudstone and sandstone samples.

Table 3.10: Chemical composition based on rock type.

Mudstone Sandstone

Min Max Average Min Max Average

SiO2 59.58 63.65 61.15 63.36 68.51 65.11

Al2O3 16.61 19.20 17.82 15.45 17.16 16.49

Fe2O3 4.51 8.55 7.03 3.75 6.18 5.17 MgO 1.34 2.31 1.75 1.33 2.00 1.66 CaO 0.24 0.53 0.30 0.22 0.31 0.27

Na2O 1.00 2.01 1.39 1.65 2.25 1.99

K2O 2.24 2.96 2.69 1.70 2.55 2.17

TiO2 0.78 0.87 0.83 0.72 0.89 0.81 LOI 4.55 5.41 4.93 4.17 4.43 4.32

3.6.2 Organic matter content

3.6.2.1 Methodology

The proportion of carbon in the samples was determined, to indicate the presence of any organic matter. Organic matter, if present, may affects the determination of LOI in XRF analysis, and may influence the geotechnical properties of the rock materials.

A LECO CNS-2000 carbon-nitrogen-sulfur analyzer (Figure 3.23) was used for carbon content determination in this study. This instrument can analyze carbon (C), sulfur (S) and nitrogen (N) at the same time, although in this study only carbon was a major concern. 100

Figure 3.23: LECO CNS elemental analyzer used for carbon, sulfur and nitrogen determination.

The analysis process is based on combustion of the sample, which converts elemental carbon, sulfur and nitrogen into CO2, SO2, N2 and NOx (LECO, 1993). These gases are then passed through infrared cells to determine the carbon and sulfur content, and passed through a thermal conductivity cell to determine N2. The apparatus can be used to analyze carbon either in the form of carbonate or as organic carbon.

The LECO is a computer-based instrument, which means that the input data such as sample weight are keyed into the system. After the analysis is finished, the result is kept in the system as well as printed out.

Blank calibrations were performed before running each sample. The total carbon content was reported as a percentage of the rock sample.

The same set of rock samples used for XRF analysis was tested using this method. Although the samples covered a wide range of slake durability properties, the analysis was 101

not intended to compare durability but to check for any organic content that may be related to the loss on ignition (LOI) value.

The test procedure involved calibrating the instrument by running the blank correction routine until consistent results were obtained. Each ground rock sample was weighed and then placed on a sample holder (called a boat). At this stage the weight of the sample was keyed into the computer attached to the analyzer. The boat was pushed into the combustion chamber and the process of combustion started. When the analysis was finished, the result was displayed on the screen as well as printed in hard copy form.

In the normal procedure a ground sample weight of 0.3 gm was used for carbon content determination. The rock samples for the present study, however, were expected to have very low carbon contents, and so sample weights of 0.5 gm were used instead to compensate for the low organic content and the absence of carbonate. Some samples were analyzed in duplicate, to check the accuracy and consistency of the equipment. No chemical treatment was performed on the samples in the organic matter determination for the present study.

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3.6.2.2 Results

The results of the carbon content determinations are listed in Table 3.11. The carbon contents range from 0.04 to 0.79 %, with an average value of 0.12% and a standard deviation of 0.19.

Table 3.11: Determination of carbon content for selected rock samples.

Carbon content Carbon content Sample Sample % % 203 0.05 606 0.08 205 0.06 612 0.08 414 0.11 615 0.06 504 0.06 701 0.04 506 0.09 801 0.06 512 0.07 815 0.17 513 0.07 O3R 0.79 602 0.08

No reaction was observed in the hydrochloric acid treatment, suggesting the absence of carbonate material in most of the samples studied. The XRD analysis (Section 3.4) also suggested the absence of carbonate material in the rock samples studied. Therefore the carbon contents found in the rocks studied were solely from carbon material.

The total carbon contents of these samples are seen from Table 3.11 to be very low. Organic and/or carbonate carbon can thus be discounted in the LOI evaluation, and in any relevant geotechnical data.

Organic matter has some effect on geotechnical properties through swelling and shrinking when wet and dry. 103

With the low proportion found in the rock samples for this study, however, it can be concluded that organic content is not a major factor controlling the geotechnical properties of the Patonga Claystone.

3.7 Quantitative Whole-Rock Mineralogical Analysis Using Siroquant

3.7.1 Previous Methods

Several approaches can be used in quantitative XRD analysis. Some of the methods will be briefly discussed here, along with details of the method used in the present study.

Although factors such as crystallinity may also be involved, the XRD peak intensity, or preferably the peak area, due to a mineral in a mixture is mainly proportional to its concentration (Hardy and Tucker, 1988). Therefore it is possible to make rough estimates of relative mineral contents by comparing their intensities or peak areas. According to Hardy and Tucker (1988), however, this method is unreliable, due to the different diffracting abilities of minerals from different crystal structures.

Another method for quantitative XRD analysis is to use an internal mineral standard. Internal standards are a completely new substance added to the sample, such as potassium permanganate (KMnO4), halite (NaCl) or cerium oxide (CeO2). Selection of the internal standard is important. It is a good practice to have an internal standard that has a similar X-ray response to that of the analyzed minerals (Hardy and Tucker, 1988), but a 104

diffraction pattern that does not interfere with those of the other minerals present.

Calibration curves are prepared by running XRD traces on known mixtures, each with a known mass of the internal standard added. The proportion of each mineral in the sample can be estimated by plotting the ratio of its key peak intensity values to the key peak intensities from the standard added against the (known) relative proportions of the respective minerals in the calibration mixtures. There are many disadvantages of this method, including difficulties in obtaining a truly homogeneous mixture of sample and internal standard, as well as limitations in the number of minerals that can be incorporated in the analysis process. Other factors include the development of preferred orientations of any platy particles, and the variability of composition and degree of crystallinity of the minerals in natural rock materials.

Another approach to quantitative XRD is the so-called Rietveld method. Rietveld (1969) developed a formula to give the intensity at any point in the XRD scan of a single mineral, with information on how to refine relevant crystal structure and instrumental parameters by least-squares analysis of the profile. A total of 14 different parameters were identified, including mineral scaling factor, asymmetry, preferred orientation, half-width, instrument zero, line-shape and unit cell parameters.

The Rietveld method has been used in quantitative XRD by several authors, such as Hill and Howard (1987) and Taylor (1991). This methodology allows a calculated XRD profile of each mineral to be generated from its known crystal structure. Each calculated pattern is then merged 105

and fitted to the observed XRD pattern by iterative least- squares analysis, to find the optimum individual phase scales for best fit to occur. The different mineral percentages in the observed sample are determined from the phase scales when best-fit conditions are obtained.

3.7.2 Using Siroquant

One technique based on the Rietveld method for quantitative XRD is Siroquant. This method has been successfully used in quantifying mineral mixtures by authors such as Ward et al. (1999a and b) and Ruan and Ward (2001).

The Siroquant (Figure 3.24, 3.25, 3.26 and 3.27), personal computer software, developed by the Commonwealth Scientific and Industrial Research Organization (CSIRO) (Taylor, 1991), was used for determining the percentages of both clay and non-clay minerals in the whole rock samples from their XRD powder patterns.

106

Figure 3.24: Operation of Siroquant software for quantitative XRD analysis. Top panel shows the fit of observed and calculated patterns while the bottom panel indicates the difference between these two patterns.

Figure 3.25: Refining parameters for Siroquant. ‘-‘ and ‘x’ indicate the variables that are refinable and fixed respectively for the analysis run in question.

107

Figure 3.26: Graphic output from Siroquant showing the observed trace (top), calculated trace (middle) and the difference between these two traces (bottom).

Figure 3.27: Tabulated Siroquant results with global chi2 value also indicated.

Following identification based on inspection of the powder and oriented aggregate XRD data, Rietveld-format XRD 108

data (.hkl) files were prepared using Siroquant for each mineral present in the rock samples, drawing on unit cell information in the Siroquant database. In some cases use was made of previously prepared hkl files already in the Siroquant database. A task file (.tsk), incorporating the .hkl files to be used in the analysis, was set up for each sample to be analyzed. The expected minerals were identified using the search-match routine in XPlot for Windows, as discussed in Section 3.4.2, and the oriented aggregate XRD data (Section 3.5.3).

Correction was carried out to remove the background from the observed XRD trace, and then a calibration function was applied to compensate for the effects of low angle diffraction and the goniometer geometry. The calibration function was found also to boost up the noise associated with the low angle diffractions. The presence was also detected in some instances of aluminium metal peaks derived from the sample holder. For these two reasons, data from regions at 2-4˚ 2θ and 44-45˚ 2θ were excluded from the Siroquant analysis.

The option to ‘use automatic pre-scale’ was taken as the first step in the interpretation process, allowing an approximate initial fit to be obtained quickly. After that ‘stage control and refinement’ (Figure 3.25) was used in the analysis. In this stage, a 6 cycle process and damping factor of 0.40 were used.

Operation of Siroquant involved interactive adjustment and best-fit matching of the calculated pattern to each of the observed XRD patterns (Ward et al., 1999a and b; Ruan and Ward, 2001). The input parameters, Figure 3.25, consisting of scale, unit-cell dimension, line-widths, 109

preferred orientation for individual minerals, and the zero setting for the machine, were refined under operator instruction (Sietronics, 1996) to fit the full profile of XRD pattern. The overall goodness of fit, expressed as the global chi2 value, also provided by the software, was used in confirming the best fit between the observed and calculated patterns (Figure 3.26). The chi2 value should approach 1.0 for a perfect fit between the inferred and observed patterns. The errors associated with each individual component, represented by the estimated standard deviations (e.s.d.) of the relevant Rietveld scale factor, were also calculated. The global chi2 and estimated standard deviation were included the table-form results (Figure 3.27).

Quantitative interpretation was carried out with Siroquant on the whole rock XRD powdered patterns, in the light of both the clay and non-clay mineral identifications. Quartz, kaolinite, illite, chlorite, mixed layer (I/S), albite, haematite and anatase were the principal minerals found in the study and used in the Siroquant task files. Global chi2 values were typically between 4 and 7, representing values similar to those obtained by Ward et al. (1999b) for evaluation of sandstones from the Sydney Basin, and Ward et al. (1999a) and Ruan and Ward (2001) for mineral matter of coal samples.

3.7.3 Problems with Siroquant

One limitation of Siroquant is the errors associated with determination of minerals at low concentrations. For example, with the chlorite in Figure 3.27, the estimated error is of a magnitude similar to the actual mineral 110

determination (e.g. 0.4 ± 0.37%). The chlorite in this instance represents a small portion of the powder mount, detected by XRD but with quantification below the resolution of the Rietveld technique.

3.7.4 Results

The mineral percentages determined by Siroquant for the samples studied are listed in Table 3.12 and in Appendix B.

Table 3.12: Mineral percentages of samples as determined by Siroquant.

Mineral 130 131 132 133 134 135 136 137 138 139 Quartz 47.4 41.9 32.2 34.9 33.5 32.8 41.8 44.2 39.4 39.8 Kaolinite 8.7 13.9 10.8 10.4 11.1 15.7 6.1 9.6 11.2 6.4 Illite 15.2 17.0 20.1 18.3 16.3 16.0 14.4 10.0 9.8 12.4 Chlorite 0 2.6 2.4 1.0 4.3 2.1 2.5 3.7 5.8 1.9 Mixed layer 13.5 15.0 20.3 21.0 19.6 19.7 26.7 25.7 23.5 32.5 Albite 8.9 8.9 8.0 8.2 9.8 8.2 4.3 4.2 7.8 1.6 Heamatite 5.7 0.4 5.5 5.8 4.8 5.4 3.9 1.9 1.8 5.2 Siderite 0 0 0.1 0 0 0 0 0 0 0 Anatase 0.6 0.2 0.6 0.5 0.6 0 0.2 0.5 0.5 0.2 Global Chi2 4.45 6.82 4.78 5.03 7.35 4.20 6.51 7.61 7.05 5.70

Mineral 140 141 142 143 144 145 146 203 205 211 Quartz 39.0 47.9 40.4 44.2 39.9 43.1 37.6 36.2 34.1 36.9 Kaolinite 4.7 8.0 9.2 6.7 10.3 11.7 12.3 11.5 14.2 8.1 Illite 11.0 16.0 20.8 21.6 13.5 16.0 14.5 17.5 16.8 15.9 Chlorite 2.0 3.0 3.0 0.6 1.5 0.2 0.1 2.8 1.0 3.9 Mixed layer 30.6 9.9 19.4 17.9 22.2 20.5 21.0 19.7 17.4 22.4 Albite 6.9 10.1 1.4 3.6 8.1 4.9 8.0 8.3 16.6 9.1 Heamatite 5.8 4.7 4.9 5.2 4.0 3.2 5.9 3.8 0 3.6 Siderite 0 0 0 0 0 0 0 0 0 0 Anatase 0 0.3 0.6 0 0.5 0.4 0.4 0.1 0 0 Global Chi2 5.99 5.27 6.25 6.42 5.87 5.13 5.12 5.08 4.68 6.96

Mineral 212 213 214 215 216 217 310 311 312 313 Quartz 31.1 44.9 36.2 27.6 37.4 34.0 32.0 34.8 33.4 34.8 Kaolinite 16.3 11.0 9.5 11.7 6.8 9.7 9.6 11.1 13.2 14.0 Illite 10.0 15.6 19.3 22.2 14.6 18.4 14.7 10.7 17.2 10.4 Chlorite 0 0 0.4 0.5 0 2.1 2.1 0 0 0.1 Mixed layer 28.9 17.1 22.0 25.4 25.6 19.5 29.2 31.7 22.5 27.7 Albite 8.7 8.7 6.5 7.9 12.0 11.2 6.2 8.6 8.7 8.9 Heamatite 4.9 2.7 5.6 4.6 2.9 4.8 6.3 2.8 4.9 3.8 Siderite 0 0 0 0 0 0 0 0 0 0 Anatase 0 0 0.4 0 0.6 0.2 0 0.3 0.1 0.3 Global Chi2 4.94 7.20 6.57 6.63 6.06 5.72 7.47 4.66 5.74 4.43

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Table 3.12: - Continued -

Mineral 409 414 501 502 504 506 508 511 512 513 Quartz 35.6 34.2 32.2 31.0 38.9 34.6 32.7 34.8 34.9 30.4 Kaolinite 18.9 12.4 12.5 13.1 11.6 13.1 12.0 13.4 9.2 13.3 Illite 12.7 18.8 22.0 19.4 17.9 11.5 10.8 11.7 10.4 14.4 Chlorite 2.3 4.3 2.2 0.4 1.7 0.3 3.1 0 3.1 0.1 Mixed layer 20.1 17.2 20.6 22.9 16.6 30.8 32.4 26.9 27.8 32.2 Albite 10.1 13.0 6.3 8.1 11.1 4.4 4.2 9.4 11.8 5.6 Heamatite 0 0.1 4.0 4.9 1.8 4.9 4.3 3.7 2.5 3.5 Siderite 0 0 0 0 0 0 0 0 0 0 Anatase 0.3 0 0.2 0.3 0.4 0.5 0.6 0.1 0.4 0.3 Global Chi2 4.13 5.69 5.27 5.40 5.24 4.86 5.21 4.51 5.18 4.94

Mineral 602 605 606 607 608 609 612 613 615 701 Quartz 37.7 29.9 36.8 34.4 35.2 34.9 39.3 32.1 32.8 31.9 Kaolinite 14.2 16.0 11.9 14.5 13.5 12.5 24.4 11.0 11.2 13.2 Illite 20.5 12.3 18.0 13.1 11.7 12.1 7.4 15.2 12.5 15.8 Chlorite 2.3 2.1 0.5 0.8 3.3 0.3 4.0 2.7 0.2 0.2 Mixed layer 17.4 24.0 16.7 25.7 22.7 30.8 7.4 26.8 33.7 25.0 Albite 7.3 9.1 13.4 5.9 13.4 3.7 17.3 6.5 5.5 8.0 Heamatite 0 6.3 2.2 5.1 0 5.2 0 5.2 3.7 5.6 Siderite 0 0 0 0 0 0 0 0 0 0 Anatase 0.6 0.3 0.4 0.6 0.3 0.5 0 0.3 0.3 0.4 Global Chi2 4.46 5.04 5.61 4.48 4.71 4.51 5.37 4.60 4.26 4.94

Mineral 702 703 704 705 706 708 801 809 815 820 Quartz 39.8 34.8 48.1 36.8 41.4 36.7 42.9 40.1 36.4 43.9 Kaolinite 14.7 15.5 16.0 18.2 16.1 12.7 23.6 24.9 22.6 13.8 Illite 8.5 18.6 10.8 15.2 11.7 14.0 6.7 8.9 9.6 8.1 Chlorite 2.1 2.0 1.0 0 3.8 2.9 5.6 3.2 2.9 2.0 Mixed layer 17.9 13.7 9.6 13.4 7.5 16.2 6.1 7.4 10.7 18.1 Albite 13.1 10.1 8.0 11.4 15.0 11.1 15.1 15.6 17.8 13.8 Heamatite 3.9 5.1 6.1 4.7 4.5 5.9 0 0 0 0 Siderite 0 0 0 0 0 0 0 0 0 0 Anatase 0 0.2 0.5 0.2 0 0.5 0 0 0 0.3 Global Chi2 5.07 4.58 4.33 5.41 4.80 5.00 6.00 5.39 5.61 5.43

Mineral O3R Quartz 34.0 Kaolinite 16.4 Illite 8.1 Chlorite 2.8 Mixed layer 20.6 Albite 18.1 Heamatite 0 Siderite 0 Anatase 0.1 Global Chi2 5.97

Statistical data on the mineral percentages in the rock samples are summarized in Table 3.13.

112

Table 3.13: Statistical analysis on mineral content of the samples studied, based on Siroquant data.

Minerals Min Max Average Median Mode SD Quartz 27.6 48.1 36.9 36.2 34.8 4.7 Kaolinite 4.7 24.9 12.8 12.4 11.1 4.2 Illite 6.7 22.2 14.3 14.5 15.2 4.0 Mixed layer I/S 6.1 33.7 21.1 20.6 21.0 6.9 Chlorite 0 5.8 1.8 2.0 0 1.5 Hematite 0 6.3 3.6 4.0 0 2.1 Feldspar 1.4 18.1 9.1 8.7 8.4 3.8

For the full range of samples used in this study, the difference between the minimum and maximum percentage of quartz is smaller than for the other minerals. The value of the difference in relation to the maximum percentage of quartz is about 40%, while for the other minerals the differences are between 70-90%. This can be taken to indicate that the proportion of quartz is relatively constant.

Since the total of the different mineral proportions must be 100%, a high proportion of one mineral inherently means a low proportion of one or more others. Given that the proportion of quartz in the Patonga Claystone is relatively constant, Table 3.13, in conjunction with Table 3.7, seems to indicate an inverse relationship between feldspar and clay minerals, especially the mixed-layer I/S component. This may reflect the effects of weathering, either during transport or after sediment deposition, with the feldspar in the original sediment being altered to clay minerals.

The range of mineral percentages found in the mudstone and sandstone samples used for the present study are listed in Table 3.14. 113

Table 3.14: Mineral proportions in mudstone and sandstone samples based on Siroquant data.

Mudstone Sandstone Minerals Min Max Average Min Max Average Quartz 27.6 48.1 36.3 34.1 43.9 39.4 Kaolinite 4.7 18.911.7 11.2 24.9 17.0 Illite 8.1 22.215.1 6.7 17.9 11.2 Mixed layer I/S 9.6 33.7 22.8 6.1 23.5 14.2 Chlorite 0 4.3 1.5 1.0 5.8 3.2 Hematite 0 6.3 4.2 0 4.5 1.0 Feldspar 1.4 18.18.0 7.8 17.8 13.8

The data suggest that the sandstones in the Patonga Claystone have on average more quartz and significantly more feldspar than the mudstones. Kaolinite and chlorite are slightly more abundant in the sandstones, but illite and mixed layer I/S, as well as haematite, are more abundant in the mudstones. The maximum values are approximately the same for the mudstones and the sandstones, but the mudstones have lower values of the minimum percentage for more minerals than the sandstones. The mudstones have higher proportions of mixed layer I/S, and also a wider range of quartz contents than the sandstones. The consistency of mineral proportions found in the rocks studied suggests the same source of sediment input, but variations in the geological processes, such as selective settling, making differences in the mineral proportions. This process causes a ‘particle size effect’, with the mudstones being richer in the finer-grained clays (illite and mixed layer I/S) and the sandstones having more unaltered coarser grained feldspars and quartz. The haematite is also presumably fine grained, and concentrated in the mudstones.

114

3.7.5 Comparison of Siroquant Mineralogy to Chemical Composition

The mineral percentages determined by Siroquant were cross-checked by comparing the chemical compositions implied by those mineral mixtures to the chemical analysis data obtained independently by XRF for the same rock samples. The chemical composition inferred from the mineralogy for each sample was calculated from the Siroquant results by using a Microsoft Excel spreadsheet. Most of the calculations were based on ideal stoichiometric formulae, such as for quartz, kaolinite, chlorite, siderite, albite, haematite and anatase (Ward, et al., 1999a; 1999b). The composition used for illite was one without Fe or Mg in the structure. The calculated results were then normalized. The results are presented in Table 3.15.

Table 3.15: Chemical composition of samples in Table 3.12, interpreted from Siroquant data.

Sample SiO2 Al2O3 Fe2O3 MgO CaO Na2O K2O TiO2 CO2+H2O Number % % % % % % % % % 203 64.6 16.3 6.9 1.2 0.4 1.4 2.7 0.2 6.3 205 67.0 17.9 2.8 0.9 0.3 2.3 2.5 0.1 6.1 414 66.2 17.7 3.2 1.4 0.4 1.9 2.7 0.1 6.4 504 67.3 16.1 4.7 1.0 0.3 1.7 2.6 0.5 5.8 506 62.7 16.3 8.0 1.0 0.4 0.9 2.7 0.6 7.3 512 65.7 15.7 5.7 1.2 0.4 1.8 2.4 0.5 6.5 513 62.5 17.9 5.7 1.1 0.5 1.1 3.1 0.4 7.8 602 66.5 17.4 3.0 1.2 0.3 1.2 2.9 0.7 6.6 606 65.4 16.6 5.7 1.2 0.3 1.5 2.1 0.5 6.6 612 69.2 17.0 2.9 0.8 0.2 2.2 1.2 0.1 6.3 615 62.8 16.8 7.0 1.0 0.5 1.1 3.0 0.4 7.5 701 62.2 16.7 8.5 0.9 0.4 1.4 2.7 0.5 6.6 801 70.5 16.0 3.0 1.0 0.2 1.9 1.0 0.1 6.2 815 68.0 17.7 2.8 0.8 0.2 2.3 1.5 0.1 6.5 O3R 67.4 17.2 2.9 1.0 0.3 2.5 1.9 0.2 6.6

115

75 25 a). SiO2 b. Al2O3 y = 0.91x + 2.83 20 R2 = 0.80 15 65 10

y = 0.23x + 13.49 5 2 SiO2 - XRF (%) Al2O3 - XRF (%) R = 0.03

55 0 55 60 65 70 75 0 5 10 15 20 25 SiO2 - SiQ (%) Al2O3 - SiQ (%)

10 3 c. Fe O 2 3 d.MgO 8 2 6

4 1 y = 0.68x + 3.11 y = 1.19x + 0.48 2 2 MgO - XRF (%) 2

Fe2O3 - XRF (%) R = 0.82 R = 0.36 0 0 0123 0246810 MgO - SiQ (%) Fe2O3 - SiQ (%)

3 4 e. Na2O f. K2O

1 y = 0.80x + 0.24 y = 0.44x + 1.49 K2O - XRF (%)

Na2O - XRF (%) 2 R2 = 0.87 R = 0.57 0 0 0123 01234 Na2O - SiQ (%) K2O - SiQ (%)

1.0 10 h. LOI

0.5 5 y = 0.05x + 0.80 R2 = 0.06 y = 0.43x + 1.88 LOI - XRF (%) 2 TiO2 - XRF (%) R = 0.37 g. TiO2 0.0 0 0.0 0.5 1.0 0246810 TiO2 - SiQ (%) CO2 + H2O - SiQ (%)

Figure 3.28: Comparision of oxide percentage from Siroquant and XRF. 116

Comparisons of the inferred chemical composition for each rock sample to the actual chemistry of that same rock are given in Figure 3.28. The actual chemical compositions determined from XRF are plotted on the y-axis, while those evaluated from Siroquant are plotted on the x-axis. Some compositions rest above the diagonal line that indicates equality between the two values, while some rest below. For the points that plot below the diagonal line, the oxide percentage evaluated from Siroquant is greater than that analyzed directly by the XRF method. For points that plot above the line the Siroquant interpretation under-estimates the oxide percentage relative to the XRF data.

From Figure 3.28, the proportion of SiO2 (3.28a) and the LOI (3.28h), estimated from Siroquant, are greater than those determined by XRF analysis. However, the percentages of Fe2O3 (3.28c), MgO (3.28d), K2O (3.28f) and TiO2 (3.28g) derived from the Siroquant data are mostly less than the

XRF results. Al2O3 (3.28b) and Na2O (3.28e) are estimated to be approximately equal by both methods. Relations between the inferred chemical compositions derived from Siroquant against actual chemistry derived from XRF analyzed are listed in Table 3.16.

Table 3.16: Linear regression equation and R2 for inferred chemical composition from Siroquant and actual chemistry – XRF method.

Minerals Equation R2 SiO2 0.91x + 2.83 0.80 Al2O3 0.23x + 13.49 0.03 Fe2O3 0.68x + 3.11 0.82 MgO 1.19x + 0.48 0.36 Na2O 0.80x + 0.24 0.87 K2O 0.44x + 1.49 0.57 TiO2 0.05x + 0.80 0.06 LOI 0.43x + 1.88 0.37

117

The SiO2 results (Figure 3.28a) are not coincident, i.e. SiO2 evaluated from Siroquant is over-estimated, but the trend of these two parameters indicates that high values from Siroquant correspond to high values indicated by the XRF data (R2=0.80) (Table 3.16). The difference between these two results is about 4% SiO2, with XRD giving the higher values. Ward, et al. (1999a and b) and Ruan and

Ward (2001) also reported slight over-estimates of SiO2 percentages in similar studies.

The plot of Al2O3 (Figure 3.28b) shows a group of points on the diagonal line. The group is too clustered to show a trend (R2=0.03, Table 3.16), but appears to be close to equality in all cases.

The Fe2O3 percentages (Figure 3.28c) determined by XRF are greater than those inferred from Siroquant (R2=0.82, Table 3.16). This may be because the rock samples contain small amounts of iron oxide too poorly crystalline to be detected by XRD. The other source of such a difference may be errors in the inferred chemical composition of the chlorite used in the normalization. Errors in the (assumed) chlorite composition may also effect the plot of MgO that also lies above the diagonal line. Another possible source of the error in this relation is the Fe and Mg contents used in calculation of the illite and mixed layer I/S components.

Figure 3.28e indicates a coincidence of both methods in the chemical composition determination for sodium (R2=0.87, Table 3.16). This may suggest a single source of Na, possibly confirming that most of the feldspar is albite-rich.

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Departures from the diagonal line in some cases, such as for MgO, K2O, Al2O3 Fe2O3 and LOI, may be caused by differences in chemical composition between the minerals in the rocks studied and the published chemical composition data used in the computation. Alternatively, it may be caused by ionic substitution of Fe for Al or Al for Si in the clay mineral structures. More specifically for K2O (Figure 3.28f), the under-estimation of Siroquant result may be due to differences in the proportions of illite and smectite used in the evaluation of the I/S composition. Illite was estimated to be around 80-90% of the illite/smectite (Section 3.5.5), while the Siroquant result was based on a mineral with 50% illite, hence the I/S in the actual samples included more K2O than was expected to be present.

The plot of the TiO2 results (Figure 3.28g) reveals a scattered pattern with very low R2 (R2=0.06). The rock samples in this study contain some anatase (TiO2) that can be detected by XRD, but its concentration is usually below the limit that can be precisely quantified by Siroquant. Some Ti may also occur in the kaolinite lattice, rather than as a separate anatase component.

Figure 3.28h compares the LOI from the XRF analysis to the inferred CO2 and H2O of the clay and carbonate minerals identified by Siroquant. Differences in sample preparation may cause H2O, for example, to be over-estimated. XRD studies were carried out on the samples on an ‘as received’ moisture content, i.e. some interlayer moisture was probably present in the clays, whereas the LOI was measured on ‘oven-dried’ rock samples. Other sources of the difference may include to the organic matter and the 119

proportions of illite and smectite in the mixed layer I/S used in the computation.

3.7.6 Comparison of Powder and Oriented Aggregate XRD Data

The percentages of the different clay minerals evaluated by Siroquant were normalized by calculation to 100%, and the results plotted against the clay mineral percentages estimated from the oriented aggregate mounts. Each clay mineral evaluated from the Siroquant data was computed as the proportion of that clay mineral in relation to the total clay mineral content. The percentage of illite evaluated from Siroquant, for example, was multiplied by 100 and divided by the sum of the percentages of kaolinite, chlorite, mixed layer clay and illite as follows:

I*100 I%= (K+++ C) M I

The terms on the right hand side are the percentages of each mineral evaluated from Siroquant, while the left hand side indicates the normalized percentage of (in this case) illite as a fraction of the total (Siroquant) clay mineral content.

A comparison of the results obtained by the two methods is shown in Figure 3.29. A good correlation appears to have been achieved, with an acceptable R2 value. The percentages of the different clay minerals estimated from the oriented aggregate mounts and those determined on a normalized basis from Siroquant plot close to the 1:1 (diagonal) line indicating equality. The percentage of kaolinite plus chlorite estimated by Siroquant is slightly 120

higher than that for the same minerals calculated by the graphical method (Griffin, 1971) from the oriented aggregate mounts, while for illite and mixed layer clay the reverse applies.

80 a).

40 % Kaolinite+ 20 y = 0.97x + 4.05 Chlorite - Siroquant R2 = 0.82 0 0 20406080 % Kaolinite+Chlorite - Clay fraction

60 b).

20 y = 0.92x + 0.16 R2 = 0.58 % Illite - Siroquant 0 0204060 % Illite - Clay fraction

80 c). 60

20 y = 0.95x + 1.10 R2 = 0.73 % Mixed Layer - Siroquant 0 0 20406080 % Mixed Layer - Clay fraction

Figure 3.29: Plots of clay mineral percentages determined from oriented aggregate data against normalized percentages of the same minerals from Siroquant: a) Kaolinite and Chlorite, b) Illite and c) Mixed layer clay minerals. 121

The correlation in each case was also expressed in the form of a linear regression equation (y = ax + b) (Table 3.17), where a is the slope of the straight line of best fit and b is the y-intercept. Ideally a = 1 and b = 0 and R2 = 1 for perfect correlation.

Table 3.17: Linear regression equations and R2 for clay minerals.

Minerals Equations R2 Kaolinite + Chlorite y = 0.97x + 4.05 0.82 Illite y = 0.92x + 0.15 0.58 Mixed layer y = 0.95x + 1.10 0.73

R2, the coefficient of determination, indicates the percentage of data accounted for by the linear regression on that relation, i.e. an R2 value of 0.82 indicates that 82% of the plotted data obey that relationship (Hoppe, 1999).

From Figure 3.29 and Table 3.17, the percentage of kaolinite + chlorite evaluated from Siroquant is slightly greater than percentage of the same minerals evaluated from the clay slides. This is may be due to the fact that some kaolinite crystals may be coarser than 2 µm. For illite, the Siroquant results are lower than those from the oriented aggregate study while for the mixed layer clay minerals the results from Siroquant are approximately equal to the results from the clay slides.

All of the linear correlations listed in Table 3.17 have a slope (“a” value) very close to 1, i.e. the differences are relatively minor. This suggests a high 122

level of consistency between the two methods used in estimating the clay mineral proportions. Such a consistency further supports the use of Siroquant in quantitative XRD analysis. Siroquant has been successfully applied to quantitative clay mineral studies in a similar way by Ward et al. (1999a and b) and Ruan and Ward (2001).

3.7.7 Relationship between LOI and mineralogy

Loss on ignition of the studied rock samples was plotted against mineralogy evaluated from Siroquant as shown in Figure 3.30a (total clay minerals) and Figure 3.30b (quartz plus feldspar). It is clearly seen from the graphs that in rock samples with high proportions of clay minerals the loss on ignition is also high. The opposite occurs in rock specimens with high quartz and feldspar proportions; the rocks in this case exhibit low LOI values.

The plots (Figure 3.30) show somewhat scattered correlations between these parameters, with R2 values of 0.28 and 0.43 for total clay and quartz plus feldspar respectively. The difference in coefficient of determinations is probably due to errors associated with the relatively small proportions of the clay minerals, whereas quartz and feldspar are the main constituents of the samples studied.

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7.0 a).

6.0

5.0

Loss on ignition % 4.0

R2 = 0.28 3.0 30 35 40 45 50 55 60 65 Total clay - SiQ

7.0 b).

6.0

5.0

4.0 Loss on ignition % R2 = 0.43 3.0 30 35 40 45 50 55 60 65 Quartz + Feldspar - SiQ

Figure 3.30: Relationships between loss on ignition and total clay minerals (a) and quartz plus feldspar (b).

3.8 Cation Exchange Capacity

Cation exchange capacity (CEC) is a property that has been used extensively in soil chemistry, for purposes such as predicting soil fertility, site selection for waste disposal, and sensitivity to acidification (Soon, 1988). In geotechnical work, CEC is used mostly to study the expansive and dispersive behavior of soils (Sherard et al., 1972b, Sherard et al., 1976a, Bell and Maud, 1994). 124

3.8.1 Methodology

CEC can be determined by several procedures, such as by ammonium saturation followed by sodium saturation or the methylene blue absorption method (Fredrickson, 1986, Soon, 1988, Velde, 1992).

In the present study, ammonium saturation was used for CEC determination. The same fifteen samples subjected to XRF analysis were also subjected to CEC determination by the ammonium acetate method. The slake durability indices of these samples cover a range from low to high.

The CEC determination procedure involved keeping the powdered rock samples in a chamber at 75% relative humidity for 3 days. Then approximately 10 grams of the sample was mixed with a 1 M ammonium acetate (NH4Oac) (pH 7.0) solution and left to stand overnight (Figure 3.31). Each sample was leached several times with NH4Oac, and the leachate kept for determination of exchangeable bases.

The ground rock samples were then washed with 1N

NH4Cl, followed by 0.25N NH4Cl, to get rid of excess ammonium ions, and then the electrolyte was washed out with isopropyl alcohol. At this stage each rock sample was in an ammonium-saturated condition. The samples were then leached with acidified NaCl. The leachate was distilled into boric acid (H3BO3) with an added indicator. The solution was titrated with standard 0.1N HCl until the colour changed from bluish green to pink at the equilibrium point (Chapman, 1965). The CEC was calculated in units of milli-equivalents of cation per 100 grams of rock (meq/100 gm.).

125

Figure 3.31: Sample preparation for CEC determination.

The CEC value was calculated from the following equations.

− 100*17*C*)BA( NH% = 3 1000*D 100*NH% NH%~CEC = 3 4 180 where: A = volume of hydrochloric acid in titration, B = blank correction = 0.3 in this study, C = concentration of HCl acid, and D = weight of sample in grams.

The percentage of NH3 was calculated first, then converted to NH4 in units of milli-equivalents per 100 grams of sample, i.e. the CEC value.

A rapid method for CEC estimation using methylene blue adsorption has also been described by various authors, and 126

is more fully discussed by Soon (1988). Soon (1988) has claimed that standard method of CEC determination is time– consuming and involves several steps, but with the methylene blue method one can complete 60 or more analyses in a single day. This rapid method involves weighting 2 grams of soil in 250 ml flask. 50 ml of 5 mM methylene blue solution (pH 6.8 in 50 mM sodium acetate) is added shake the flask for 15 minute and then allowed to stand and settle for 2 hours. A 0.25 ml aliquot of the supernatant solution is pipetted into a test tube containing 12.25 ml of distilled water and mix. Standard solution containing 0.5 ml of 5 mM methylene blue is prepared and measure transmittance at 550 nm. High pH and high organic matter content, such as calcareous soil, tend to produce an under- estimate of the CEC value. Because of the large size of methylene blue making fewer ions to fit on to the clay particles, a lower CEC is usually indicated. This technique was not used in the present study.

3.8.2 Results

The results of the CEC determinations for the present study are listed in Table 3.18.

The CEC values determined in the study ranged from 12.49 to 31.35 meq/100 grams of dried rock, with an average value of 22.46 meq/100 gm (Table 3.19). Statistical analyses of cation ion exchange capacity are also listed in Table 3.19.

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Table 3.18: CEC results for rock samples studied.

Sample CEC TEC Na+ K+ Ca2+ Mg2+ Rock type No 203 28.33 17.26 4.28 1.81 4.47 6.70 Red mudstone 205 20.20 17.11 6.19 1.72 3.99 5.22 Green sandstone 414 20.57 24.37 10.30 1.93 9.70 2.44 Red mudstone 504 20.29 15.68 4.43 1.63 6.45 3.16 Green sandstone 506 27.42 19.72 9.12 1.92 5.58 3.11 Red mudstone 512 31.35 19.37 10.01 2.36 4.24 2.76 Red mudstone 513 30.92 20.60 11.55 2.07 4.45 2.52 Red mudstone 602 21.79 15.36 4.32 2.03 5.20 3.80 Red mudstone 606 19.42 17.15 6.43 2.42 4.71 3.60 Green sandstone 612 19.25 16.23 7.97 1.42 3.44 3.40 Green sandstone 615 26.69 19.02 9.30 2.54 4.14 3.05 Mudstone 701 25.30 19.57 4.54 1.75 8.63 4.66 Red mudstone 801 12.49 11.16 1.22 0.96 4.17 4.81 Green sandstone 815 14.31 11.59 6.61 1.25 2.52 1.21 Green sandstone O3R 18.65 17.66 2.63 0.57 3.88 10.59 Brown mudstone

Table 3.19: Statistical analysis of cation exchange capacity.

CEC TEC Na+ K+ Ca2+ Mg2+ Minimum 12.49 11.16 1.22 0.57 2.52 1.21 Maximum 31.35 24.37 11.55 2.54 9.70 10.59 Average 22.46 17.46 6.59 1.76 5.04 4.07

Clay minerals usually have a significant cation exchange capacity (Velde, 1992), especially smectite and related minerals. Table 3.18 indicates that the mudstone samples tend to have more CEC than the sandstones, presumably because the mudstones contain more clay minerals than the sandstones. From Table 3.5, 3.12 and 3.18 it is clear that the CEC value is related to the total clay mineral content of the respective rock samples. Total clay 128

contents evaluated from Siroquant are plotted against the CEC values for the same samples in Figure 3.32.

3.8.3 Relation of CEC to Clay Content

CEC is clearly related from Figure 3.32 to the total clay mineral content. The plot gives a coefficient of determination (R2 value) of 0.63 (Table 3.20 and Figure 3.32). Rock samples with high clay contents also have high cation exchange capacities. For example, samples 512 and 801 have CEC values of 31.35 and 12.49 meq/100 gm, and total clay proportions of 51 and 42% respectively.

Table 3.20: Coefficient of determinations between CEC and clay minerals.

Clay minerals R2 Total clay minerals 0.63 Illite 0.05 Illie + mixed layer I/S 0.65 Mixed layer I/S 0.72 Kaolinite 0.54

The plot in Figure 3.32 and the associated linear regression equation imply that the studied rock samples have zero CEC at a total clay content of about 25%. However, such an extrapolation should be done with great caution, as the nature of the clay minerals, as well as the total clay content, along with experimental uncertainty, can also play a part.

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y = 0.86x - 21.02 2

CEC meq/100 grams R = 0.63 0 35 45 55 65 Total percentage of clay minerals

Figure 3.32: Plot of total clay mineral content (from Siroquant) against CEC value.

The proportions of the individual clay types are plotted against CEC in Figure 3.33. Percentages of illite, illite plus mixed layer I/S, mixed layer I/S, and kaolinite estimated from Siroquant are shown in Figure 3.33a), b), c), and d) respectively.

The plot of the illite percentage estimated from Siroquant against CEC (Figure 3.33a.) gives scattered points with a low coefficient of determination (R2 = 0.05) (Table 3.20), suggesting no particular correlation trend. A combination of the proportion of illite and mixed layer I/S (Figure 3.33b), however, reveals a good correlation between the sum of these two clay minerals and the CEC value (Table 3.20). A better coefficient of determination is achieved from the percentage of mixed layer I/S alone (Figure 3.33c), with an R2 value of 0.72 (Table 3.20).

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40 40 a). b).

20 20 CEC CEC R2 = 0.05 R2 = 0.65

0 0 01020300 1020304050 % Illite % Illite and Mixed layer clay

40 40 c). d).

20 20 CEC CEC

2 R = 0.72 R2 = 0.54

0 0 0 102030400 102030 % Mixed layer clay % Kaolinite

Figure 3.33: Plots of individual clay types against CEC value: illite (a), illite plus mixed layer I/S (b), mixed layer I/S (c), and kaolinite (d).

The coefficient of determinations derived from the plots of illite plus mixed layer clay (I/S) (Figure 3.33b) and mixed layer clay (I/S) alone (Figure 3.33c) against CEC value indicate that the CEC of the rocks studied is related to the proportion of these two clay minerals. Since the plot of illite against CEC (Figure 3.33a) is scattered with a relatively low R2 value, the CEC value is apparently less dependent on the proportion of illite present. Hence the CEC value of the samples studied depends mainly on the proportion of the mixed layer illite-smectite. Smectite typically has a much greater cation exchange capacity than 131

illite (Grim, 1962), a factor consistent with this relationship.

A negative correlation is shown by the plot of the kaolinite percentage against CEC value (Figure 3.33d and Table 3.20). This can be explained in terms of the total clay mineral content found in the rock samples for this study. The total proportion of clay and non-clay minerals is broadly consistent among the samples, whereas the proportions of the individual clay minerals differ from sample to sample (Table 3.12). Samples containing larger proportions of one clay mineral therefore generally have lower proportions of the other clay minerals. On the plot, samples with high proportions of kaolinite would therefore be low in mixed layer clay and illite, and would have a low CEC value. The opposite occurs in rocks with low kaolinite contents. The CEC value is thus related to the percentage of the combination of illite and mixed layer I/S (Figure 3.33b), especially the mixed layer I/S (Figure 3.33c), and thus is related negatively to the kaolinite content. In other words, the high coefficient of determination is derived from the correlation between the CEC and the clay minerals other than kaolinite.

3.9 Comparison to Thin Section Studies

As can be seen from Table 3.14, mineralogical determination based on quantitative XRD, the sandstones of the Patonga Claystone have a greater concentration of chlorite than the mudstones. Thin sections of rock samples used in the present study were observed under the optical microscope. The mudstone sample (Figure 3.34) shows no chlorite while the sandstone sample (Figure 3.35) suggests 132

the occurrence of chlorite in the rock fragments of this fine-grained material. This finding confirms to some extent the quantitative XRD data evaluated by Siroquant (Section 3.7).

Figure 3.34: Mudstone (sample number 613) under optical microscopy (x50).

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Figure 3.35: Sandstone (sample number 504) under optical microscopy (x50).

3.10 Concluding Summary

X-ray diffraction analysis was used as the basis for mineralogical analysis in this study, both qualitatively and quantitatively. Qualitative XRD was used for mineral identification by comparing the peak positions to those in standard published documents, and also, with the computer software XPlot for Windows, to the electronic ICDD mineral database. Siroquant software, based on the Rietveld method, was used in quantitative analysis of mineral percentages from the X-ray diffraction data.

The average quartz content of the Patonga Claystone found in this study was about 37% (range 28 to 48%). Mixed layer clay minerals, ranging from 6 to 34% with an average of 21%, were the second most abundant mineral in the rock unit. The rocks of the formation contain an average of 134

about 4% hematite, ranging from 0 to 6%. Lesser proportions of hematite (in some cases zero) were found in the sandstone samples, whereas the highest hematite contents, up to 6%, were found in the mudstone samples.

The relations between the different mineral proportions and rock type indicate a consistency in the average percentage of quartz in both mudstone and sandstone samples, 36.3% and 39.4% in mudstone and sandstone respectively. However, the minimum value of the quartz percentage in the mudstones is lower than in the sandstone samples (27.6 and 34.1% in mudstone and sandstone respectively). The maximum quartz content in the mudstones is higher than in the sandstone samples, with values of 48.1 and 43.9% respectively. These differences suggest possible differences in the grain size of the quartz, reflecting variations in the sediment source and the action of geological agents during transport and deposition.

Some of the quartz in the Patonga Claystone also occurs as very fine grains. XRD peaks at positions indicating quartz appear in every diffractogram of the oriented aggregate samples of the clay (<2 µm) fraction. Fine-grained feldspar was also found in some clay aggregate slides.

The proportion of mixed layer I/S is higher in the mudstones than in the sandstone samples, whereas the feldspar content in the mudstones is lower than in the sandstones. These differences may indicate chemical weathering of feldspar minerals to mixed layer clay (I/S). The proportions of the other clay minerals are consistent in both the mudstone and sandstone samples.

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The other significant difference between the mudstones and sandstones was the proportion of hematite. The mudstones contain more hematite than the sandstones, but have a lower proportion of chlorite. The hematite content is reflected in the red colour of the mudstone samples, while chlorite gives a greenish gray and gray colour to the sandstones. The appearance and disappearance of hematite and chlorite probably reflect oxidation and reduction in the environment of deposition. Red mudstone containing hematite was probably formed in an oxidizing environment while the greenish gray sandstone was deposited in a more reducing environment.

The clay mineral contents evaluated by Siroquant were compared to the clay mineralogy evaluated from oriented aggregate XRD data. The comparison revealed a notable consistency for both methods, with only very minor differences.

X-ray fluorescence spectroscopy (XRF) was carried out to determine the chemical composition of a range of rock samples. The results showed that the most abundant chemical component was silica (SiO2) (59.58 – 68.51%). The second most abundant oxide was aluminium oxide (Al2O3), with a range of 15.45-19.20%. The other oxides make up to about 20% of the rock material.

The chemistry of the mineral mixtures, including both clay and non-clay minerals, determined by Siroquant was calculated and compared to the XRF results. The results from this comparison were generally acceptable, given the uncertainty associated with the composition of the clay minerals that dominate the samples studied.

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The cation exchange capacity (CEC) was also determined for a suite of rock samples. The CEC results were found to be consistent with the total clay contents evaluated by Siroquant. The results were found to correlate mainly with the proportion of mixed layer I/S found from the quantitative XRD analysis, which is consistent with this material representing the most highly exchangeable clay mineral in the rock samples.

Hydrochloric acid treatment was used in checking for the presence of carbonate material in the rocks studied. No reaction was observed in this treatment, suggesting the absence of carbonate material in most of the samples studied. Organic matter content was analyzed by using a LECO C-S-N analyzer. The results were low (0.04 to 0.79%). In the absence of carbonate material, the carbon found in the rocks studied is thought to be solely derived from organic material.

The consistency of chemical composition between the XRF and the Siroquant results, the clay mineral proportions from both oriented aggregate XRD and Siroquant, and the CEC values in relation to both the total clay content and the mixed layer I/S percentage evaluated from Siroquant, all suggest that quantitative XRD analysis by Siroquant, used in this study, can be applied to similar clay-rich rocks with some degree of confidence. The results were thus used to assist in the interpretation of slaking and other geotechnical properties, discussed in the next sections of this thesis.

CHAPTER 4.1

MUDROCK DURABILITY

4.1.1 Introduction

Because of their abundance, mudrocks are one of the most frequently encountered rock types in engineering construction. Many mudrocks, however, deteriorate rapidly when subjected to changes in moisture content. This non- durable behavior of mudrocks is responsible for difficulties in numerous geotechnical engineering projects, such as slope instability problems, underground excavation problems and embankment failures, and for mining problems such as underground mine roof and floor behaviour, surface mine highwall failure, and breakup and dispersion of shales in coal washing processes.

Mudrocks are generally considered to be problematic rocks, and the durability of mudrocks is a major concern in geotechnical projects. The durability behavior of mudrocks, however, is highly variable, with some disintegrating instantaneously and others taking years of exposure before showing any signs of deterioration. Because of this variability, and its significance, much research has been done on the slaking behavior of mudrocks.

From a different point of view, the variable slaking properties of mudrocks in the coal washing process have also been of concern to the British coal-mining industry since the 1950s (Taylor, 1988). A ‘Shale Panel’ was 138

established by the National Coal Board (now British Coal) in 1953. Their research led to a better understanding of the abrasion and breakdown behavior of mudrocks in water. The research resulted in the development of several durability evaluation tests, the most important of these being the ‘end-over-end’ slaking test, otherwise known as the slake durability test, developed by Franklin and Chandra in 1972. The test was recommended by the International Society for Rock Mechanics (ISRM) in 1979, and has been standardized by the American Society for Testing and Materials (ASTM D4644) in 1990.

Other examples of the recognition of problems related to weathering behaviour of mudrocks or shales include the considerable attention given to mudrock weathering (for example, Chandler, 1969, 1972; Spears and Taylor, 1972; Russell and Parker, 1979; Steward and Cripps, 1983; Taylor, 1988), durability testing (Franklin and Chandra, 1972; Russell, 1982; Dick and Shakoor, 1992; Dick, et al., 1994), and durability classification (Morgenstern and Eigenbrod, 1974; Oliver, 1979b; Grainger, 1984; Taylor, 1988). Details of these works will be given in relevant sections elsewhere in this thesis.

Some details of this research, the resulting slaking test methods, rock slaking classifications, and the test methods used in the present study will be discussed in this chapter. A summary and discussion of the results obtained from the study itself will be given in the next chapter.

4.1.2 Slaking Mechanisms

Term ‘slaking’ is defined as ‘the crumbling and disintegration of the earth materials upon exposure to air or moisture; specifically the breaking up of dried clay or 139

indurated soil when saturated with or immersed in water, or the breaking up of clay-rich sedimentary rocks when exposed to air’ (Gary, et al., 1974). ‘Slaking’ is also explained as ‘the disintegration of tunnels in swelling clay due to inward movement and circumferential compression’ and ‘treatment of lime with water to give hydrated (slaked) lime’ (Gary, et al., 1974).

For the present study, slaking is defined as the breakdown and dispersion of rocks, especially mudrocks, in response to alternate wetting and drying or even only in water immersion.

In alternate wetting and drying, if a fragment of mudrock is allowed to dry out, air is drawn into the outer pores and a high suction pressure develops. This in turn results in increased shearing resistance of the individual fragments by virtue of the high contact pressures. The bulk of the voids are filled with air under extreme desiccation conditions (Figure 4.1.1). If the rock is then rapidly immersed in water, it becomes pressurized by the capillary pressures developed in the outer pores. Pressurization is followed by failure of the mineral skeleton along the weakest planes, and an increased surface area is then exposed to a further sequence of events (Taylor and Spears, 1970). The air pressure developed depends on the capillary pressures, which themselves are related to the surface tension of the water (Seedsman, 1986) and the pore radius involved (Vallejo, et al., 1993).

The relationship between pore pressure and pore diameter can be explained by the equations below. 140

Figure 4.1.1: Processes involved in slaking: (a) shale sample; (b) macropore with water and air pressure; (c) air and water forces at the air-water interface in a macropore (Vallejo, et al., 1993).

At equilibrium conditions, the following equation applies: ⎛⎞⎛⎞ππdp22 du π−dTs ⎜⎟⎜⎟ + = 0 ⎝⎠⎝⎠44 where, d = diameter of the macropore,

Ts = surface tension of water acting on the manisus, p = air pressure u = pore water pressure.

From the above equation (Vallejo, et al., 1993), the following relationship can be obtained:

141

⎛⎞4T pu=+⎜⎟s ⎝⎠d

This equation indicates that the pore pressure (p) in the portion of the macropore filled with air increases as the diameter (d) of the macropore decreases. Thus, the smaller the diameter of the macropore, the larger the pressure will be. In other words, slaking of mudrock by air compression will be more pronounced in those mudrocks containing small diameter macropores (Vallejo, et al., 1993). However, this mechanism requires the rapid build up of pressures (Seedsman, 1986). Low permeability and the presence of expansive clays may restrict the movement of the wetting front. Given enough cycles of drying and wetting, breakdown can occur as a result of air breakage. This process can reduce the mudrock into gravel-size particles (Bell, 1992).

Bell (1992) explained failure occurring in consolidated and poorly cemented rocks in terms of swelling pressure and capillary suction pressure. This failure happens during the saturation process, when the swelling pressure, or internal saturation swelling pressure (σs), developed by capillary suction pressures, exceeds the tensile strength. An estimate of σs can be obtained from the modulus of deformation (E):

σ E = s εD

where εD is the swelling coefficient (Bell, 1992). The swelling coefficient is determined by a sensitive dial gauge recording the amount of swelling of an oven-dried core specimen per unit height, along the vertical axis 142

during saturation in water for 12 hours, with εD being obtained by this equation:

change in length after swelling εD = initial length

Swell can also occur as a result of hydration. For example, when anhydrite is hydrated to form gypsum there is a volume increase of between 30 and 58%. This exerts a pressure that has been estimated at between 2 and 69 MPa (Bell, 1992). At shallow depths this process causes expansion, but the process is gradual and is usually accompanied by the removal of gypsum in solution. At greater depths anhydrite is effectively confined during the process. The confinement results in a gradual build up of pressure, and the stress is finally liberated in an explosive manner.

4.1.3 Causes of Mudrock Deterioration

Interaction between mudrock and water can be considered as the main cause of mudrock deterioration. The actual processes involved in the breakdown are still not fully understood, although it is known that mudrock-water interaction causes expansion of the mudrock. Hudec (1982) lists three possible factors that affect this deterioration: “structuring” of water on clay surfaces; osmotic pressure; and frost action.

1. The structuring of water in clay-water mixtures may cause a thixotropic effect, i.e. the viscosity of the water increases as the clay surface is approached. Since mudrock has a high internal surface area, defined in terms of square meters per gram, water molecules adsorbed by these surfaces tend to completely fill the internal pores. The 143

adsorbed water may become strongly bound to the internal surface and hence increase in specific volume. Volume expansion of the water in turn causes volume expansion of the rock.

2. Osmotic pressures generated within the rock may also deteriorate the mudrock or cause the mudrock to expand. Due to the extremely small pore size in mudrocks, the water in such pores has a lower pressure than bulk water does. Water is therefore impelled to enter the rock. This water will create pressure within the pores, which causes expansion of the pore and the rock. In other words, saturating the clay causes it to expand, whereas drying the clay causes it to contract. Alternate wetting and drying of some mudrocks causes their disintegration.

3. Freezing and thawing (frost action) can be considered as similar to the wetting and drying process. Cooling the pore water to below freezing temperatures significantly lowers its vapour pressure and causes water vapour transfer from larger pores to the smaller pores. This process may lead to expansion of the mudrock and then to mudrock deterioration.

Based on the above, it can be concluded that cyclic wetting and drying of mudrock will result in cyclic application of tensional and compressional stresses between the pore walls and between the clay particles. During the sedimentation processes forming mudrocks, the clay particles are often simply pressed together, and water is expelled from the pores by the weight of the overlying sediments. Removal of the confining pressure, such as with stress relief caused by excavation, accompanied by water infiltration, may result in the complete disintegration of the mudrock particles to separate fragments and eventually to material resembling the original mud. 144

Cementation also plays a role in mudrock deterioration, due to its tendency to prevent particle dispersion with unloading. If the tensional stress of the water-clay interaction is great enough to overcome the bonding strength of the cement, especially in poorly cemented mudrocks, then the mudrock is likely to be slaking prone.

A number of studies (e.g. Jumikis, 1979; Farmer, 1983; Franklin, 1989; McNally and McQueen, 2000) have shown that saturated rocks have lower strength than dried rocks. Van Eeckhout (1976) gives a good explanation for the influence of moisture on the rock strength. This includes: fracture energy reduction; capillary tension decrease leading to negative pore pressure; pore pressure increase causing positive pore pressure; frictional reduction; and chemical and corrosive deterioration.

Fracture energy reduction. This is the mechanism predominantly used to explain moisture effects on rock strength. The Griffith fracture criterion, used in this explanation, states that for a continuous material with a crack of unit thickness:

2Eγ σt = πCo

Eγ or σt = K Co

where σt = tensile stress necessary to cause crack growth E = Young’s modulus of elasticity γ = surface energy, and

Co = one-half the initial flaw or crack length. K = constant

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It is generally assumed that an equation of the form σ

1/2 = K(Eγ/Co) holds, where γ is the energy required per unit advance of the crack and Co is some measure of a critical flaw length (Van Eeckhout, 1976). If γ is lowered with the absorption of water, the fracture strength will also be lowered, and so will the rock strength.

Capillary tension decrease. Many researchers have noted that mudrocks may expand or swell due to capillary tension caused by moisture absorption, leading to reduction in strength (Singh and Cummings, 1983; Taylor and Smith, 1986; Taylor, 1988; Vallejo, et al., 1993). The degree of swelling varies with both the direction of measurement and the rock type. For example, swelling in the direction perpendicular to bedding is greater than that parallel to bedding, and limestone and granite swell less than shale, marl and mudrock (Van Eeckhout, 1976). If mudrocks have reversible swelling characteristics, those mudrocks will not disintegrate; otherwise they will disintegrate. The worst mudrocks of the latter category are those that contain expandable clay minerals, particularly members of the smectite group (Underwood, 1967; Spears and Taylor, 1972). Although swelling is a reversible process, the rock may be broken down due to a lack of confining pressure. If a mudrock contains expandable clay minerals, it will disintegrate rapidly during wet-dry cycling. In contrast, a rock may swell or expand without expandable clay minerals. Rock swelling in the absence of expandable clay minerals is generally attributed to capillary action or stress relief (Van Eeckhout, 1976).

Pore pressure increase. It has long been known that pore pressure affects the strength of rocks with interconnecting pores. This phenomenon is controlled by the effective stress, i.e. changes in stress can lead to 146

changes in pore pressure, which may significantly affect shear resistance. If the pore fluids in a rock are pressurized as the rock is compressed, in other words if effective stress increases, this will lead to a lowering of the rock strength. The Ewet/Edry ratio, in low permeability rocks, can be used as an indicator of possible build up of pore pressure. If there is no change in Young’s modulus in wet conditions, it can be said that no pressurization occurs in the pores (Van Eeckhout, 1976).

Frictional reduction. Another possible moisture weakening mechanism is a reduction in the coefficient of friction. Consider the Coulomb criterion, the well-known equation in describing the strength of material, expressed as follows (Brady and Brown, 1985).

cs σ+= n tan ϕ where: s = shear stress c = cohesion

σn = normal stress ϕ = angle of internal friction.

The term φ defines the frictional angle of material, while tan φ defines the coefficient of friction. From the above equation, shear strength decreases with decreasing frictional angle (or decreasing coefficient of friction).

Van Eeckhout (1976) studied the influence of moisture content on the coefficient of friction. This study revealed that there was some change in the coefficient of friction with different moisture contents. The explanation of the process is not clear, but it can be concluded that Young’s modulus and the coefficient of friction are affected by moisture change. 147

Many workers, e.g. Taylor and Smith (1986), Taylor and Spears (1970), Vallejo et al. (1993), have used the reduction in coefficient of friction with change in moisture content in explaining rock slaking by the failure of shear strength. Air is drawn into the outer pores of a rock and dries out producing high suction pressures. When the rock is wetted again the air is pressurized as a water film is drawn in by capillary action. This process will thus cause the skeletal structure to be stressed. If this stress is higher than the shear strength of the skeletal structure, the rock will slake.

Chemical and hydration processes. Mineralogical changes due to hydration processes must also be considered in evaluating geotechnical properties. The changes may be severe if soluble or reactive minerals are present. Solubility, for example, may increase with stress and with the acidity of the water. Sulphide minerals, such as pyrite and marcasite, are frequently present in mudrocks. An expansion in volume large enough to cause structural damage can occur when these minerals suffer oxidation to form hydrous and anhydrous sulphates. According to Fassiska et al. (1974), the oxidation of sulphides can increase rock volume by up to 350%. Hydration of the sulphates involves a further increase in volume. If sulphate ions exist in solution, any cation in the system may cause precipitation of hydrous sulphate crystals. For example, if calcium carbonate is present, gypsum may be formed. This may give rise to an eight-fold increase in volume over the original sulphide, and exert pressures of up to about 0.5 MPa, leading to further disruption of the grain fabric and weakening of the rock involved.

From the above, the causes of rock disintegration may be summarized as being controlled by expandable clay minerals, mineral composition, volume change related to 148

hydration, moisture, pore space characteristics, or combinations of several such factors.

4.1.4 Slake Durability Testing

Several types of slake durability tests have been investigated and used by researchers worldwide to assess the durability of mudrocks. Some tests are based on specific mechanisms of rock disintegration, resulting from physical breakdown by wetting and drying. Some tests are designed to measure the amount of tightly held surface, pore and capillary water, as an indicator of the rock durability. Some tests are qualitative while some are semi-quantitative or quantitative.

The following durability related tests will be discussed here:

1. Jar slake test, 2. Emerson crumb test, 3. Rate of slaking, 4. Water absorption, 5. Wet-dry deterioration test, 6. Franklin slake test.

Jar slake test. The jar slake test (Vellejo, et al., 1993) is the simplest of all durability tests. This test is performed to give a qualitative assessment of the rock’s slaking characteristics after immersion for a specified period of time. A lump sample of the rock, about 50-100 grams, is oven-dried at a temperature 105° C for 24 hours before being submerged in a container filled with tap water. Any rock deterioration during the test is observed, and the slaking characteristics as well as the final product are recorded as a jar slake index (Ij) following 149

the guidelines listed in Table 4.1.1. The jar slake index indicates how rapidly the rock sample deteriorates, i.e. quick or slow, whether a few or several fractures develop, and whether the rock completely disintegrates or there is no change. The test can be performed on the sample at its natural moisture content or in an “as received state” as well.

Table 4.1.1: Jar Slake Ranking (Vellejo, et al., 1993).

Jar Slake Behaviour Index, Ij 1 Degrades to a pile of flakes or mud 2 Breaks rapidly and/or forms many chips 3 Break slowly and/or forms few chips Breaks rapidly and/or develops several 4 fractures 5 Breaks slowly and/or develops few fractures 6 No change

This test investigates properties of the rock material related to water absorption, swelling properties, and porosity in both the ‘as received’ and ‘oven-dried’ states. Moreover, in the oven-dried state, since the rock sample is free from water, the effect of remaining moisture content on the slaking behaviour can be studied. However, testing in an oven-dried condition may be considered as too severe for the atmospheric conditions found in rock formations exposed in nature.

Since the rock piece is immersed in water for up to 48 hours until the test is completed, the test resembles the water absorption test (see below). Hence the water absorption properties can be tested along with the jar slake test. The jar slake test provides a qualitative measurement, therefore the result can not be easily used in mathematical correlations with other test results.

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Emerson Crumb Test. This test was originally designed for testing of dispersive soils in embankment construction (Emerson, 1967). The test is also classified as a qualitative assessment. Specimen preparation can be done by lightly compressing a moist soil sample into a pellet 15 mm wide. The tendency for colloidal sized particles to disperse and to go into suspension is observed as the specimen immersed in distilled water.

At first Emerson described the dispersive character of the materials by reference to four grades:

1. No reaction – no sign of colloid dispersion, 2. Slight reaction – some colloid cloud at the surface of the crumb, 3. Moderate reaction – easily recognizable cloud of colloids in suspension and 4. Strong reaction – colloidal cloud covers the bottom of the beaker.

Emerson later modified the test by using a small air- dry crumb, which is taken directly from the soil sample and placed in a container filled with water (Emerson, 1967).

Ingles and Metcalf (1972) recommended using good quality water (either distilled water or rain water) without any dispersant or wetting agent. Slaking is observed first (slaking or no slaking), and subsequent dispersion (dispersion or flocculation) is observed in the finest slaked fragments. In this test, the slaking behaviour is defined by breakage of the specimen, while the dispersion behaviour is derived from the diffusion of the soil particles over the specimen or covering the bottom of the beaker.

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Figure 4.1.2: Determining class numbers of aggregates from the Emerson Crumb test (Emerson, 1967).

The dispersive behaviour of the test specimens can be grouped into eight classes as shown in Figure 4.1.2 (Emerson, 1967). From Figure 4.1.2, the aggregates can be classified firstly based on their slaking characteristics into slaking and non-slaking. The materials with slaking status are further classified based on their dispersion behaviour. These are: complete dispersion (class 1), some dispersion (class 2) and no dispersion. For specimens in the no dispersion category, a further test is performed to classify the aggregate by mixing it with the amount of water equivalent to the natural moisture content. Another test is performed on the remoulded sample. From this point, the aggregate can be classified into either one showing dispersion (class 3) or one showing no dispersion. If the aggregate falls into the no dispersion category, the aggregate is further classified based on the presence or absence of carbonate and gypsum. If carbonate or gypsum is present, the aggregate is classified as class 4. If not, a 152

further test must be done. The aggregate is mixed with water in a ratio of 1:5 for the aggregate:water suspension. After this, the aggregate is classified, based on whether it shows dispersion (class 5) or flocculation (class 6). If the aggregate does not slake, at the beginning of the test, the aggregate may be either swelling (class 7) or non-swelling (class 8).

These classes of the Emerson Crumb test can be summarized as follows. Classes 1 to 6 are the classes for soil aggregates that slake when immersed in water. Aggregates that do not slake are classified into either class 7 or 8 by observing their swelling behaviour. Class 8 aggregates are absolutely unchanged, whereas class 7 aggregates swell but remain coherent.

Rate of slaking. The rate of slaking test involves saturating the mudrock sample, contained in a funnel with a filter paper, for a period of at least 2 hours (Morgenstern and Eigenbrod, 1974). The proportion of water absorbed by the mudrock (after free water has filtered through the paper) is then determined. The second part of the test consists of determining the Atterberg limits on the slaked portion, and on the crushed and sieved unslaked portion of the sample. The test is based on the rate of water absorption and the proportion of clay size materials. The rate of water absorption, related to porosity, void geometry, fractures and Atterberg limits, implicitly reveals the proportion of clay size materials.

Morgenstern and Eigenbrod (1974) used water absorption in conjunction with Atterberg limits in this way to categorize argillaceous soils and rocks. The proposed system is considered to be useful in classifying soft rocks and hard soils.

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Water sorption. Mudrocks rapidly absorb water on their internal surfaces when exposed to moisture. The absorbed water fills the very small pores and partially fills the larger capillaries. Water sorption includes adsorption (adherence of water to the surfaces of the solid material), and absorption (uptake, or assimilation of water into the pores). The term natural absorption capacity is used to refer to the quantity of water that can be absorbed per unit mass by the rock material, and is measured by the water absorption test.

The water absorption test (ISRM, 1979 and ASTM, 1990a) involves placing a dried rock sample in water for a period of 48 hours and then weighing it. In the water adsorption test, the sample is exposed in a high humidity chamber. The weight gain, in both tests, is taken as a measure of the proportion of absorbed water, and is reported as a percentage of the dried rock sample. In durable rocks the amount of water absorption is close to the porosity determination, whereas in slaking rocks it represents a combination of porosity filling water and water on fracture surfaces.

A regular shaped sample should be used in determination of water adsorption, since water or humidity only adheres to the surface of the rock sample. Another point to be considered, for comparative purposes, is that the volume or size of the specimen should be similar for each sample in a test series. Otherwise, comparison between samples is unreliable.

The water absorption test is similar to the rate of slaking test discussed earlier (Morgenstern and Eigenbrod, 1974), except that the Atterberg limits are not included, and a longer immersion time is used. Either one of these two tests can provide a measure of the degree of water 154

absorption. The water absorption test was used in this study because observations of rock behaviour, equivalent to the jar slake test, could be made at the same time. The results of water absorption testing are discussed in Chapter 4.2.

Wet-dry deterioration test. This test is also based on the fact that the process of wetting and drying is the most commonly observed cause of rock deterioration. The test imposes several cycles of alternate wetting and drying, by soaking samples in water or chemical solutions (e.g. sodium sulphate), decanting, and then air or oven drying the sample at a fixed temperature or over a range of temperatures. The wet-dry deterioration test is considered to involve a cyclic wet-dry process, the rate of water adsorption, and the rate of slaking (Withiam and Andrews, 1982).

The sodium sulphate soundness test (ASTM D 5240-92) and the ASTM test of the durability of rock under wetting and drying conditions (ASTM D 5313-92) are classified as ‘wet-dry deterioration tests’.

The sodium sulphate soundness test (ASTM D 5240-92) is an indirect attempt to simulate the expansion of water on freezing. The test applies a combination of salt wedging, by crystallization of Na2SO4 or MgSO4, and alternate soaking and desiccation to the rock (McNally, 2000). The test involves oven-drying of 5 rock samples each cut to 10 cm cubes, and placement of the sample in a sulphate solution, followed by oven-drying, with a repetition of the process of immersion and drying for a total of 5 cycles.

The largest remaining pieces of all rocks samples after testing are used in calculation of the soundness 155

loss, i.e. the average percentage loss on soundness is calculated from:

− )BA( % average soundness loss = 100* A where: A = oven-dried cumulative mass of all rocks prior to testing, and B = oven-dried cumulative mass of the largest remaining pieces of all rocks after testing.

The sodium sulphate soundness test is widely used for testing of aggregate (road pavement and concrete) and building stone that is to be exposed to the atmosphere, pollutants or marine spray. A low value for the soundness loss indicates a high durability rock.

The sodium sulphate soundness test has been criticized for being unrealistically severe, due to the combination effect of salt wedging and oven-drying to simulate the expansion of water on freezing of the sample (McNally, 2000). Therefore the test was considered as an unsuitable testing method for the present study.

Another test based on water deterioration is the “wet and dry test” (ASTM D 5313-92). This accelerated weathering test is designed to simulate summer-time conditions of alternating rainfall and subsequent drying by the summer sun. It also simulates the rise and fall of tidal movements and water levels in reservoirs, lakes, rivers, etc. At least 5 rock specimens are used, the size of which should be as large as the testing laboratory can handle but not less than 125 mm. Each specimen should be 64 mm thick and cut normal to bedding or any potential planes of weakness. The test consists of oven-drying the 156

rock sample and placing the sample on a thin layer of sand in a container filled with water for a period of 12 hours. The water is decanted and then the sample is dried in an oven at a temperature of 60-70° C for a minimum period of 6 hours. The process of wetting and drying is repeated for a total of 80 cycles (ASTM, 1993).

Only the largest remaining piece of each rock specimen is used in the calculation. The resistance of the rock sample to the accelerated weathering can be evaluated. The percentage of loss is calculated from:

− )BA( loss% = 100* A where: A = oven dried mass of sample prior to testing, and B = oven dried mass of the largest fragment remaining after testing.

As already stated this wet and dry test simulates the conditions of a rock exposed to the atmosphere, with moisture uptake and under partially dry conditions. The test is useful for determining the durability of rock for erosion control, e.g. for riprap testing. Unfortunately, there is no standard or guideline to define the classes of durability from the test results. Another disadvantage is that the test is very time consuming (80 cycles).

Franklin slake test. The Franklin slake test, also called the “slake durability test” or “end-over-end test”, uses a steel mesh drum with 2 mm diameter openings (Figure 4.1.3) (Franklin and Chandra, 1972; ISRM, 1979; and ASTM, 1990c). The rock sample is placed in the drum, and the drum is rotated at speed of 20 revolutions per minute for a period of 10 minutes (total of 200 rounds), while partly submerged in water. Following this, the material retained 157

in the drum is oven-dried and weighed. This cycle is repeated. The standard slake durability index is the proportion of the original rock sample remaining in the drum after the second cycle, derived in both cases from the respective dried sample masses (ASTM, 1992).

The processes acting in the test are equivalent to those operating during natural surface exposure, i.e. wetting and drying of the rock material.

Figure 4.1.3: Slake durability equipment and its dimension (ASTM, 1992).

More specifically, the processes involved in the slake durability test are wet abrasion between rock pieces and steel mesh, water uptake, impact force from dropping of rock pieces in the drum, and complete drying of the sample. The slake durability test can be used to distinguish soft rock from hard rock on the basis of the slake durability index. Rocks having a second cycle slake durability index greater than 75% are defined as having ‘High’ or ‘Very High’ durability (Franklin and Chandra, 1972). Details of the classification systems of rock durability based on this test are discussed in the following sections.

The slake durability test uses the oven-dried sample mass as the original weight for comparative purposes. This 158

implies that a rock sample at natural moisture content cannot be tested until it is oven-dried. Therefore the effect of the initial moisture content on durability cannot be investigated. However, oven-drying of the rock sample may be considered as too severe in relation to the atmospheric conditions found in the nature. In other words, while the wet cycle may be considered as representing submerging of the rock below the groundwater table in nature, the rock is in general not as dry in natural exposures as the oven-dried material used in the test.

A test similar to the slake durability test, except for the drying conditions and the more severe impact force, is the Los Angeles Abrasion (LAA) test (ASTM, 1969a and b). The LAA test subjects a crushed and graded (sized) sample to wear due to collision between the rock particles themselves, and also the impact forces produce by abrasive impact against steel spheres. The test consists of placing a graded sample of rock aggregate and abrasive charges into a machine rotating at about 30-33 revolutions per minute. The total number of revolutions depends on the graded size of the rock sample, 500 revolutions for an aggregate smaller than 38 mm, and 1000 revolutions for an aggregate larger than 19 mm. The abraded rock is sieved through a US number 12 (1.7 mm) sieve. The amount of wear is taken from the loss in weight (the mass passing through the sieve), expressed as a percentage of the original sample mass. The higher the LAA value the less the durability of the rock sample.

The Los Angeles uniformity of wear ratio of the rock sample can be evaluated by calculating the ratio of the loss after 100 or 200 revolutions to the loss after 500 or 1,000 revolutions respectively. A value of less than 0.20 159

indicates the uniformity of the hardness of the rock material.

The processes involved in the LAA test are dry abrasion and the impact obtained by dropping a charge of aggregate, together with the impact from the steel balls. These processes resemble the slaking behaviour of rock material on exposure and impact from traffic load. The test is useful for concrete aggregate, but is considered as too severe, due to the impact force from steel balls, for soft rock materials (McNally, 2000) and irrelevant to slaking on natural exposure.

4.1.5 Relevance of Tests to Deterioration in Natural Exposures

The Emerson crumb test and the jar slake test are both good and simple tests for studying the slaking and dispersive behaviour of a rock specimen subjected to water immersion. However, there are also some disadvantages. Firstly, both the Emerson crumb test and the jar slake test are qualitative tests; the results may not be used in mathematical correlations to other test results. Secondly, due to their qualitative nature, one person may describe the same results in a different way to another person (i.e. the results are somewhat subjective).

Some of the tests discussed above, such as the Los Angeles Abrasion test and the sodium sulphate soundness test, are considered to be too severe for evaluation of soft rock. They are better suited to stronger rocks for different applications, such as sandstone in buildings and basalt in aggregate or railway ballast.

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Since no special apparatus is required, the water absorption test can be performed in a simple laboratory. Another advantage of this test is that the jar slake index test can be performed on the same sample at the same time, as has been carried out in the present study.

The slake durability test and the wet-dry deterioration test are both based on quantitative measurements. These tests also use relatively large quantities of rock sample. The use of large amount of sample provides a more representative and homogeneous mass for the testing process. It also minimizes the effect of localized internal defects. Even so, some heterogeneity of the sample may still occur.

The slake durability test (Franklin test) and the wet- dry deterioration test are similar in performance except that an abrasive action is applied to the sample by rotation in the drum in the slake durability test. However, losses in the slake durability test are usually no more than those in the alternating wet-dry test (Russell, 1982; Hudec, 1982). Therefore the abrasive action would seem to have a relatively insignificant impact on the test results. Both the slake durability test and the wet-dry deterioration test can be performed as one-cycle, two- cycle, three-cycle, or five-cycle tests, with weight losses from the sample determined at the end of each cycle. Hudec (1982) found a good correlation between these two tests.

The results of the three-cycle slake durability test (Id3) can be related to one- and three-cycle wet-dry test results by the following equation:

Id3 = 1.553 + 0.486 (wet-dry 1) + 0.556 (wet-dry 3)

Likewise, three-cycle wet-dry results can be related to the slake durability test results by: 161

wet-dry 3 = 0.239 - 0.544 (Id1) + 1.375 (Id3)

4.1.6 Slake Durability Classification

Several different durability classification systems have been developed among mudrock researchers. Some of these classification systems are briefly discussed below.

Gamble (1971, in Piteau (1977)) proposed a classification of slake durability based on the first and second cycle results of the slake durability test, as shown in Table 4.1.2.

Table 4.1.2: Gamble’s slake durability classification (Gamble, 1971).

%Id1 %Id2 Group Name (dry weight basis) (dry weight basis) Very high durability > 99 > 98 High durability 98 – 99 95 – 98 Medium high durability 95 – 98 85 – 95 Medium durability 85 – 95 60 – 85 Low durability 60 – 85 30 – 60 Very low durability < 60 < 30

Gamble (1971) also proposed a classification based on slake durability and the plasticity index of fine particles as shown in Figure 4.1.4.

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Figure 4.1.4: Gamble’s slake durability classification (modified from Piteau, 1977).

In the classification system in Table 4.1.2, proposed by Gamble (1971), rock can be classified either by the 1st or 2nd cycle slake durability index. In very high and high durability class, there is no significant difference between the values of the 1st and 2nd cycles in the classification. In medium high, medium, low and very low durability classes, however, the lower and upper limits for the 1st and 2nd cycles are significantly different. This suggests that a low durability rock deteriorates more severely, as the test proceeds, than the more highly durable rock materials.

The classification system in Figure 4.1.4 is also a simple, straightforward system. Slake durability index and plasticity index are determined separately, and plotted on one graph to give a two-term categorization for the rock sample. In the example plotted in Figure 4.1.4, the sample has a plasticity index of 20% and a 2 cycle slake durability index of 75%. This rock can be classified as medium durability – medium plasticity. 163

Morgenstern and Eigenbrod (1974) devised a durability classification based on the liquid limit and rate of slaking values. The data are based on a water absorption test to assess the amount of slaking undergone by the argillaceous material. They found that a combination of the maximum slaking water content and the liquid limit enables quantitative prediction of slaking to be made on the basis of the liquid limit alone. The liquid limit was determined by a standard procedure described in ASTM D423- 54T. Materials with medium to high liquid limit are more severely disrupted by slaking than those with low liquid limit. Classes based on the amount of slaking were therefore defined in terms related to the value of the liquid limit as presented in Table 4.1.3.

Table 4.1.3: Description of the degree of slaking (Morgenstern and Eigenbrod, 1974).

Liquid limit Amount of Slaking (%) Very low < 20 Low 20 – 50 Medium 50 – 90 High 90 – 140 Very high > 140

Another parameter used by Morgenstern and Eigenbrod (op cit.) in their study of slaking is called the ‘Rate of Slaking’ (Table 4.1.4).

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Table 4.1.4: Description of rate of slaking (Morgenstern and Eigenbrod, 1974).

Rate of slaking ∆IL Slow < 0.75 Fast 0.75 – 1.25 Very fast > 1.25

The rate of slaking (slow, fast and very fast) in this classification was calculated from ‘change of liquidity

index’ (∆IL) with the number of dry-wetting cycles, i.e. the difference in plasticity of fines at the end of the first wetting cycle compared to the initial state.

∆IL = L1 − II L0

Liquidity index can be calculated from:

− ww I = P L PI where:

∆IL = change of liquidity index,

IL = liquidity index, st IL1 = liquidity index at the end of 1 wetting cycle,

IL0 = liquidity index at the initial state, w = final water content after each wetting state,

wp = plastic limit, PI = plasticity index,

Combining these two parameters, Morgenstern and Eigenbrod (1974) proposed a classification system as shown in Figure 4.1.5.

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Amount of Slaking: WS = WL

Very low Low Medium High Very high VL L M H VH

WL<20 20140 Slow S VS L M H VH

∆IL<0.75 S S S S S

)/2h Fast F VS L M H VH L0

-I 0.75<∆IL<1.25 F F F F F L1 Very fast VF VS L M H VH =(I L1 ∆IL>1.25 VF VF VF VF VF Rate of slaking: ∆ I water immersion

Figure 4.1.5: Slake durability classification (Morgenstern and Eigenbrod, 1974).

The classification in Figure 4.1.5, proposed by Morgenstern and Eigenbrod (1974), is also a two-term classification system, i.e. rated by liquid limit and change of liquidity index. Two sets of indices have to be defined and then used in the classification. For example, a sample with liquid limit of 100% and a change of liquidity index of 1.0 would be classified as ‘High liquid limit – Fast slaking’.

Among other attempts at classifying durability phenomena, as reported by Dick et al. (1994), is the work of Wood and Deo (1975). Wood and Deo (1975) proposed a system to classify the durability of shales for use in highway embankments. The system is based on the stepwise application of a simple slake test, the slake durability test, on dry and on water-saturated samples, and also on a modified sodium sulphate soundness test. Strohm (1980) used lithologic characteristics and durability test results, together with the field performance of a large number of mudrocks used in the construction of interstate highways in the USA, to devise a mudrock durability classification system for highway embankment design. 166

Wilthiam and Andrews (1982), using 14 samples from active surface mines and a variety of durability tests, developed a classification system to identify problematic materials in spoil management programs. Franklin (1983) proposed a quantitative rating system based on second-cycle slake- durability index (Id2), plasticity index (PI) and point load strength index (Is50).

Grainger (1984) used Id2 from slake durability testing, and also uniaxial compressive strength, to classify the durability characteristics of mudrocks. Mudrock with a compressive strength, in the direction perpendicular to any planar microfabric, of 3.6 MPa or more, and with a second-cycle slake durability index of over 90%, would be classified in this system as durable. Taylor (1988) studied the composition, classification and weathering processes of British Coal Measures mudrocks. The study found that quartz content could not be used in differentiating the dominant durable mudrocks from the non- durable types or from the overconsolidated clays in the sequence. Taylor (1988) suggested that durable mudrocks can be better distinguished from non-durable types on the basis of uniaxial compressive strength and 3-cycle slake durability index (Id3). Mudrocks with a compressive strength of over 3.6 MPa and Id3 in excess of 60% were regarded as durable from these criteria.

Dick et al. (1994) studied the relationship between durability and lithologic characteristics of mudrocks in North America, with the objective of developing a mudrock- durability classification based on lithologic characteristics. They used Id2 as a measure of durability, and clay content, clay mineral composition, texture, microfracture frequency, absorption, adsorption, dry density, void ratio and Atterberg limits to characterize the mudrock lithology. Mudrocks were subdivided into 167

claystones, mudstones, siltstones, shales and argillites based on lithologic characteristics, including the presence or absence of laminations, the amount of clay-size (<0.004 mm) material, and the degree of metamorphism. According to their classification mudstone and claystone are categorized by the amount of clay-size material: rocks having more than 50% of clay-size fragments are claystone and rocks having less than 50% clay-size particles are classified as mudstone.

The relationships between durability and lithologic characteristics were studied separately for each class of mudrocks. From these studies, the durability of claystones was found to correlate well with the proportion of expandable clay minerals, and that of mudstones with the frequency of microfractures – determined from number of fractures per unit length as observed during thin section study. The degree of consolidation, as expressed by water absorption, was found to influence the durability of both siltstones and shales, and also that of argillites with their crystalline texture.

Dick et al. (1994) grouped the durability index into 3 classes namely: low (Id2 < 50%), medium (Id2 = 50 - 80%) and high (Id2 > 85%). The lithologic characteristics were quantitatively related to this durability classification as shown in Table 4.1.5.

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Table 4.1.5: Mudrock durability classification system proposed by Dick et al. (1994)

Combined

Durability Claystone Mudstone Shale Siltstone-siltshale Argillite

Slickensided Imf Absorption % Absorption %

High NA NA <0.4 <5.5 <5 All

Medium NA NA 0.8-0.4 10-5.5 9.5-5 NA

Low All All >0.8 >10 >9.5 NA

NOTE: 1. NA, not applicable 2. Imf : microfracture index (numbera of microfractures per unit length of 1 cm).

From Table 4.1.5, claystone was found to be of low durability for all cases in their study. Mudstone durability is characterized by the Imf index (number of microfractures per 1 cm length). Mudstones were classified as having high (Id2 > 85%), medium (Id2 between 50 to 85%) or low durability (Id2 < 50%) if they had an Imf index of less than 0.4, between 0.8 to 0.4 and greater than 0.8 respectively. In other words, a low number of fractures per unit length implies a more durable mudstone. Shale durability was best described in this study by the degree of water absorption. High water absorption implies a low durability index. Shales with water absorption of < 5.5, between 5.5 and 10, and > 10% have durability properties described as high, medium and low respectively.

Several approaches have been used in the study of slake durability of rock materials, as indicated in the preceding discussion. Engineering geological properties related to clay content, such as plasticity index and liquid limit, are among the index properties frequently used or referred to by several researchers (e.g. Gamble, 1971, Morgenstern and Eigenbrod, 1974, Franklin, 1983 and Dick et al. 1994). These index properties reflect the nature and abundance of clay minerals in the fine-grained portion. The various works suggest the significance of 169

clay minerals and their proportion in determining the durability characteristics of rock materials.

Grainger (1984) and Taylor (1988) considered rock strength as a factor controlling rock durability characteristics. They used compressive strength and slake durability indices in classifying rock durability. The strength of a rock substance may be governed by fractures, porosity, and density. In other words, Grainger (1984) and Taylor (1988) considered the larger scale features of the rock material (the rock mass) in the durability classifications. Grainger (1984) used quick undrained triaxial compressive strength values of 0.6, 0.6 to 3.6 and 3.6 to 100 MN/m2 in defining soil, non-durable rock and durable rock respectively. Taylor (1988) suggested relationship between uniaxial compressive strength (UCS) and point load strength index (Is) as:

UCS = 4.70 + 1.68Is

The works of Grainger (1984) and Taylor (1988) suggest a relation of rock strength to slake durability that may also be relevant to the present study.

4.1.7 Some Previous Studies of Slaking Behaviour

Taylor and Spears (1970) found that intraparticle swelling of mixed-layer clay minerals during periods of saturation followed by desiccation in the near surface zone is a major control on the breakdown of British Coal Measures mudrocks. These mudrocks contain significant proportions of expandable mixed-layer clay minerals. Furthermore, Na+ is the most abundant exchangeable ion in 170

those mudrocks which undergo the greatest breakdown. The exchangeable sodium percentage (ESP) is expressed as:

exchangeable Na+ ESP = * 100 cation exchange capacity

ESP has been extensively used as a possible guide to the study of the breakdown of mudrocks. The ESP is directly related to the amount of dispersion in the mudrocks, and so it could be used as a measure of the tendency for dispersion in water of Ca-, Na-smectites and Ca-, Na-illites (Taylor and Smith, 1986).

Chenevert (1970) subjected mudrocks ground to 2.0 to 2.38 mm to different humidities after drying in an oven. He found that the adsorption potential depended on the relative humidity levels. For most of the samples the proportions of moisture adsorbed were larger at higher humidity (90 to 98 percent relative humidity) than at lower humidity values.

Morgenstern and Eigenbrod (1974) used a water absorption test to assess rate of slaking. They found that materials with medium to high liquid limit were more severely weakened during slaking. They used the liquidity index for classifying the class of slaking behavior of the argillaceous materials, as already discussed in section 4.1.5.

Clay minerals in mudrocks adsorb water on their internal surfaces when exposed to moisture, and this causes crystal expansion. Several workers have focused their studies on water adsorption at different relative humidities and/or drying temperatures. For examples, Van Eeckhout and Peng (1975) subjected some coal mine shales to zero and 100 percent relative humidity for long periods, 171

and found that the moisture in the samples influenced the strength properties. Van Eeckhout (1976) subsequently concluded that mudrocks kept at a constant 60 percent relative humidity would retain a relatively high strength, with contraction and expansion being kept to a minimum. Fluctuations in humidity affected these properties, however, and lowered the strength of the mudrocks. Olivier (1979) also studied the effect of relative humidity. He concluded that irreversible changes to microcracks in the fabric of non-durable rocks occur during prolonged periods of air-drying at relative humidities below 60 percent. Small humidity variations could lead to volume changes (Olivier, 1979; Venter, 1981).

Venter (1981) determined the influence of temperature and humidity cycles on the volume, change of moisture content and durability of mudrock samples. He concluded that change of temperature did not affect either volume or moisture, but even small changes in humidity caused fluctuations in both. Furthermore, he concluded that temperature and humidity changes on their own did not succeed in disintegrating the mudrocks, and the nature of the samples was not seriously affected. From this point it seems that free water, i.e. samples immersed in water after oven-drying, is necessary to initiate severe fracturing, disintegration or slaking.

Smith (1978) studied the geotechnical properties of mudrocks in the UK and North America, and the results are reported by Taylor and Smith (1986). Smith (1978) carried out tests on the rate of disintegration of mudrocks breaking down to pass through a No. 36 BS sieve (425 µm). The rate of disintegration was measured and compared to the (almost) linear relationship observed over the initial stages of disintegration. Slaking durability of the rock was classified as follows (Taylor and Smith, 1986): 172

1. Rapid slaking rate > 3.5 %/min 2. Fast - medium slaking rate 3.5 - 0.5 %/min 3. Slow slaking rate < 0.5 %/min

All of the specimens in the ‘rapid slaking’ category contained high proportions of expandable clay (40 to 100%), principally smectite. Orientation ratios determined by x- ray diffraction indicated that all the specimens in this group had a randomly oriented clay mineral fabric. A high degree of preferred orientation may control the slaking behaviour, and even if the specimen has a quite high smectite component it may be a slow slaking material. This suggests that many of the slow slaking samples (group 3 above) are probably in this group because of clay mineral orientation and diagenetic bonding or cementation (induration) (Taylor and Smith, 1986).

Some researchers have related fractures/microfractures to slaking phenomena, because these microfractures provide conduits for moisture redistribution in the samples resulting in slaking (Russell, 1982; Dick and Shakoor, 1992). Dick and Shakoor (1992) observed that fully dried mudstones, when submerged in water, show that slaking is initiated along the microfractures. This is confirmed by observations in the initial stages of weathering, in which angular fragments have dimensions approximating to the microfracture spacing. Dick and Shakoor (1992) conclude that microfractures reduce the durability by increasing the total surface area of the rock mass. Russell (1982) pointed out that difference in durability of mudrocks with similar lithology is principally because of the rock fabric. The greater the fracture curvature the less durable the rock sample, because curvatures causes the cracks to meet each other more frequently during slaking, generating small fragments.

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The influence of sample fragment size and slaking fluid on the durability of mudrocks has also been studied by Withiam and Andrews (1982). They concluded that fragment size has a greater influence on the durability result than the slaking fluid. Fragment sizes of greater than 25 mm (1 inch) were recommended for use in durability determination. Slight differences in durability index were noted with different slaking fluids, e.g. sodium sulphate, ethylene glycol and distilled water, used in their study. Since the differences were small, however, it was suggested that distilled water can be used to give a satisfactory result.

Vallejo et al. (1993) studied the influence of fabric and composition on the durability of shales in the USA. Kaolinite was the predominant clay mineral in these samples, with an absence of expandable clay minerals. Vallejo et al. (1993) concluded that the durability of the shales was controlled by other factors, rather than by the expandable clay. They used macropores in assessing the durability, and concluded that the size of the macropores had a definite influence on the slaking of the shales. An optimum macropore diameter was identified equal to or less than 0.06 mm, at which size air pressure is most effective in breaking the shales. Shales with macropore diameters greater than this may develop only small fractures or no degradation at all.

Dick et al. (1994) found a close relation between slake durability index (Id2) and adsorption for shale. They found that water adsorption provides a better predictor of durability than void ratio, because water adsorption is not only a measure of induration but is also influenced by the presence of expandable clay minerals. From their study, the linear regression relationship between Id2 and percent absorption shows a strong 174

correlation (R = -0.93). The relationship can be expressed as:

Id2 = 126.0 - 7.5 * % absorption.

The above expression implies that shale with water absorption greater than 16.8% should have a second cycle slake durability index of 0%, i.e. should completely disintegrate during the second wet cycle.

The previous studies on rock durability discussed in this section suggest that clay minerals, especially expandable clays, are of significance in the breakdown of mudrocks (Taylor and Spears, 1970, and Taylor and Smith, 1986). The studies by Morgenstern and Eigenbrod (1974), Smith (1978), Vallejo, et al. (1993) and Dick et al. (1994) suggest a relation between water absorption and rock durability. Such a relation was used in the selection of test methods for the present study.

4.1.8 Tests Used in this Study

A series of related durability tests, including water adsorption, water absorption, jar slake test, and slake durability test, were used in the present study as discussed below. Most of the test procedures followed, as much as possible, the standard method or methods described in journals and textbooks (e.g. Franklin and Chandra, 1972, ISRM, 1979, Jumikis, 1979, Farmer, 1983, Franklin, 1989, ASTM, 1990a, b and c, Bell, 1992d, Vellejo et al, 1993 and Akai, 1997). Departures from these standard methods, if any, will be explained when required.

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4.1.8.1 Jar slake test

The jar slake test (Vellejo, et al., 1993) was used in this study because the test gives the slaking characteristics, as well as dispersion behaviour, of the rock specimen. Two conditions of moisture content, i.e. the as-received and the oven-dried state, were used in the experiments to compare the effect of original moisture content on rock breakage. To test their behaviour in the oven-dried condition, the rock samples were dried at a temperature 105° C for 24 hours, while for the as-received tests the rock samples were tested at the as-sampled moisture content.

In both cases a lump sample of the rock, about 50-100 grams, was used. The lump was immersed in a container filled with tap water. Rock deterioration during the immersion period was observed, and recorded by noting the characteristics of the final product as a jar slake index

(Ij). Since the jar slake index procedure uses terms ‘slowly’ and ‘rapidly’ in describing rock breakage, frequent observations were made in the early stages of the test and less frequent observations as the test proceeded.

Larger rock lumps, with a weight of 50-100 grams, were used to compensate for any inhomogeneities or internal defects in the sample.

As already discussed, the water absorption test (ISRM, 1979, and ASTM, 1990a) is similar to the rate of slaking test (Morgenstern and Eigenbrod, 1974), but involves a longer period of water immersion. Either one of these two tests, however, can be used to measure the amount of water absorption per unit mass over a specific period of time. The water absorption test was used in this study because 176

observations of rock behaviour, equivalent to the jar slake test could be made at the same time.

4.1.8.2 Slake durability test

Oven-dried samples were used in the slake durability test, as recommended by the ASTM test procedure (1992). This allowed associated determination of moisture content, and also provided a consistent basis for comparative purposes. Moisture content was calculated from:

⎛⎞AB− w = ⎜⎟* 100 ⎝⎠B where: w = percentage water content, A = mass of sample before oven drying, g, B = mass of sample after oven drying, g.

The slake durability index, for example after the second cycle (Id2), was calculated from:

⎛⎞C Id2 = ⎜⎟* 100 ⎝⎠B Where:

Id2 = slake durability index (second cycle), B = original oven dried mass, grams, C = oven dried mass retained after the second cycle, grams.

During the tests, the nature of the material remaining after each wet cycle was noted before and after drying. The material remaining after each test was categorized into three types, as suggested by ASTM (1992), namely:

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Type 1 : Retained pieces remain virtually unchanged, Type 2 : Retained materials consist of large and small pieces, and Type 3 : Retained material is exclusively small fragments.

As recommended by Withiam and Andrews (1982), a sample size of greater than 25 mm and water as the slaking fluid were used in the present study.

The standard method for the slake durability test recommends weighing the rock sample together with the steel drum to obtain the oven-dried weight. This was found to be impractical for the present study, because the weight of the sample and steel drum exceeded the capacity of the available balance. Weighing of the whole series of drums was also likely to delay progress, due to the fact that only 4 sample drums were available. If a drum was oven- dried, only four samples could be tested per day. This problem was solved by transferring rock sample, after each wet cycle was completed, into a container of known weight and then oven-drying the container with the rock sample. While sample drying was in progress, the slake apparatus could be used for another set of rock samples.

The slake durability index data and calculation are outlined in Appendix C.

4.1.8.3 Water adsorption

Adsorption, defined as water adhering to rock grain surfaces, was measured by using a humidity-controlled and temperature-controlled chamber. A relative humidity of 95

% was achieved by using cupric sulfate (CuSO4.5H2O) (Beattie, 1990), and a constant temperature of 20o C was 178

obtained by leaving this chamber in an oven set at 20o C. Oven dried samples, placed over filter paper to ensure that moisture could reach the bottom part of the samples, were exposed to this relative humidity and temperature for a period of 120 hours. Dick et al. (1994) recommend an exposure time of 96 hours, but 120 hours was selected to ensure they had fully reached the equilibrium.

Water adsorption was calculated from:

moist weight − dry weight Adsorption = 100* dry weight

Two replicate samples of each mudrock were used in this test, and average values for these two were used.

4.1.8.4 Water absorption

Absorption, defined as water retained mechanically within mudrock void space, was determined following the ASTM method C97 (ASTM, 1990) with some minor modifications. The standard method recommends oven drying the rock samples before submerging in water. To prevent excessive slaking during submerging, the rock samples in the present study were submerged at the air-dried moisture content. Forty- eight hours after submerging, the water was drained off and excessive water on the rock surface was wiped away. The sample was then weighed. The saturated sample was oven dried and weighed to give a dry sample mass. The percent adsorption was calculated from:

saturated weight − dry weight Absorption = * 100 dry weight

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Two samples of each mudrock were tested separately, and average values from the two tests were used. Rock samples that completely disintegrated into a pile of mud were excluded from evaluation, due to their over-saturated condition.

4.1.8.5 Other tests not used

The Emerson crumb test is considered by many workers to be a good index test for study of slaking and dispersion characteristics. However, this test is considered to be most useful for soil study, especially in embankment work. Another problem arises due to the nature of samples being tested. According to the test method, the sample must be remoulded with water prior to testing. Samples in the present study were treated as rock materials. Crushing and grinding of the rock material would not give the same product as a naturally weathered soil product. The Emerson crumb test was therefore considered to be an inappropriate test method for the present study.

The Los Angeles abrasion test and the sodium sulphate soundness test were both considered as too severe to evaluate the slaking characteristics of the soft rocks used in the present study. The sodium soundness test, although accepted as method for aggregate testing, also has no standard criteria or classification system. The Los Angeles abrasion test is suitable for hard rock, rather than the soft rock used in this study.

As already discussed, the slake durability test and the wet-dry deterioration test are both similar in nature. An abrasive action is induced in the sample by rotation in the drum in the slake durability test, although this has relatively insignificant impact on the test results 180

(Russell, 1982, Hudec, 1982). The results of these two tests are related to each other, i.e. the wet-dry deterioration test index can be calculated from the slake durability test data and vice versa (Hudec, 1982). This suggests that only one such test is sufficient for the present study of soft rock deterioration. Numerous works have been done on the slake durability test, and so the slake durability test was chosen for the evaluation of soft rock deterioration in the present study.

Because of the nature of the studied rock samples, which disintegrate during water immersion, the swelling test (Bell, 1992, ISRM, 1989) was also considered as unsuitable for evaluation of the rock slaking characteristics in this study.

The results of slake durability testing and the related water softening properties will be summarized and discussed in the next part of this chapter.

CHAPTER 4.2

DURABILITY TEST RESULTS

This section deals with the results of the tests carried out for this study.

The sample locations and descriptions are listed in Chapter 1. Most of the samples were collected from drilled core holes, with some from natural outcrops. Samples from both sources were tested for slake durability and geotechnical properties. However, only the drill hole samples were used in regression analysis to assess the key relationships between the various properties.

4.2.1 Moisture content

Although all of the samples were taken from cores that had been drilled more than 3 years before the study commenced, the moisture content, as recommended by the standard method, was checked before the slake durability test.

Statistical results for the moisture determinations are listed in Table 4.2.1. The full range of moisture content results in the ‘as sampled’ state are listed, together with jar slake index and slake durability results in Table 4.2.2.

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4.2.2 Jar Slake testing

Jar slake tests were performed on the rock samples in both oven-dried and as-received condition. The appearance of the samples after soaking was described, using the guidelines suggested by Vellejo et al. (1993), and the results are listed in Table 4.1.1. Frequent observations were made during the early stages of testing, and the final result was evaluated after 48 hours of immersion. Some of the slaking characteristics are illustrated in Figure 4.2.1. The results of jar slake testing for the samples studied are listed in Table 4.2.2.

Table 4.2.1: Statistical summary of moisture content for the rock samples studied.

Mudstone Sandstone Overall Minimum % 1.8 1.5 1.5 Maximum % 4.1 2.6 4.1 Average % 2.8 2.0 2.6 Number 49 12 61

In Figure 4.2.1, the top figure shows a rock sample completely degraded into pile of mud (Ij value of 1). The middle figure illustrates a rock sample behaving as expected for an Ij value of 2, forming many chips after water immersion. The bottom figure depicts a rock sample that remained unchanged after the jar slake index test.

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0 scale 5cm

0 scale 2cm

Figure 4.2.1: Photographs illustrating rock behaviour in the jar slake index test. Top: Ij = 1 - degrades to a pile of flakes or mud; Middle: Ij = 2 – breaks rapidly and forms many chips (size ranges from 0.5 to 3 cm); Bottom: Ij = 6 – no change.

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Table 4.2.2: Results of moisture content determinations, jar slake index tests and slake durability index tests.

Sample Jar slake Moisture Id1 Id2 Id3 Id4 Id5 Remarks Number Air Oven Content(%) % Type % Type % Type % Type % Type 130 5 5 2.4 98.5 2 95.5 2 92.5 2 88.7 2 86.1 2 Green VF Sandstone 131 5 5 2.0 98.7 1 97.7 1 96.7 1 95.9 1 95.1 1 Red Mudstone 132 4 4 2.5 98.6 2 92.9 2 86.6 2 79.5 2 72.5 2 Red Mudstone 133 4 2 2.6 98.2 2 91.6 2 80.7 3 67.1 3 56.0 3 Red Mudstone 134 4 1 2.4 98.6 1 96.3 1 93.8 2 91.4 2 89.2 2 Red Mudstone 135 2 1 3.1 97.0 1 81.6 2 61.7 2 47.4 2 38.9 2 Red Mudstone 136 4 1 2.9 97.8 1 87.3 2 70.3 2 57.6 2 49.1 2 Red Mudstone 137 4 2 2.8 98.0 1 96.3 1 94.8 1 93.4 1 91.9 1 Green-red Mudstone 138 4 4 2.6 98.4 1 97.0 1 95.8 1 94.6 1 93.7 1 F green Sandstone 139 4 1 3.1 94.2 2 62.6 2 30.2 3 14.7 3 9.3 3 Red Mudstone 140 2 1 3.0 97.4 1 88.5 2 76.0 2 64.3 2 53.7 2 Red Mudstone 141 2 1 3.2 98.2 1 92.8 2 83.7 2 71.1 2 61.1 2 Red Mudstone 142 2 1 3.1 96.7 2 81.8 2 67.9 2 54.6 2 47.6 2 Red Mudstone 143 1 1 3.0 87.6 1 49.5 2 21.2 2 6.5 2 2.6 2 Red Mudstone 144 4 2 3.1 98.4 1 95.2 2 91.5 2 86.7 2 82.1 2 Red Mudstone 145 2 4 3.2 97.8 1 90.6 2 84.7 2 79.1 2 73.3 2 Red Mudstone 146 4 4 3.0 98.5 1 94.9 2 91.3 2 87.7 2 85.0 3 Red Mudstone 203 1 1 2.9 67.6 2 8.1 2 Red Mudstone 205 6 4 1.9 98.6 1 97.4 1 96.3 1 95.3 1 94.2 1 F green Sandstone 211 4 1 3.0 93.1 2 66.0 2 42.9 2 32.0 2 23.6 2 Red Mudstone 212 1 1 3.0 83.6 2 36.3 3 9.8 3 4.3 3 2.5 3 Red Mudstone 213 4 4 2.9 96.4 1 88.9 1 83.3 2 77.2 2 72.6 2 Red Mudstone 214 1 1 3.5 85.0 2 27.9 3 3.4 3 0.1 3 0.1 3 Red Mudstone 215 1 1 3.3 87.7 2 41.2 3 10.6 3 8.1 3 8.0 3 Red Mudstone

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Sample Jar slake Moisture Id1 Id2 Id3 Id4 Id5 Remarks Number Air Oven Content(%) % Type % Type % Type % Type % Type 216 4 1 3.1 95.6 2 82.7 2 68.8 2 56.9 2 50.1 2 Red Mudstone 217 4 1 3.1 95.9 2 75.8 2 65.2 2 59.0 2 55.3 2 Red Mudstone 310 1 1 4.1 3.3 3 Red Mudstone 311 1 1 3.2 13.7 3 Red Mudstone 312 1 1 3.3 80.5 2 30.2 3 6.2 3 0.7 3 0.4 3 Red Mudstone 313 1 1 3.1 83.7 2 32.7 3 6.3 3 1 3 0.2 3 Red Mudstone 409 2 2 2.2 96.6 1 87.4 2 78.1 2 72.6 2 69.0 2 Green Mudstone 414 4 3 1.9 98.3 1 94.3 1 91.6 1 90.0 1 88.6 1 Red Mudstone 501 4 3 2.1 97.4 1 79.0 2 61.4 2 45.9 2 36.9 2 Red Mudstone 502 4 1 1.8 98.2 1 89.6 2 77.3 2 63.2 2 51.1 2 Red Mudstone 504 5 6 1.5 98.8 1 97.8 1 97.0 1 96.2 1 95.5 1 F green Sandstone 506 4 1 2.7 94.6 1 58.2 2 15.8 3 4.4 3 0.9 3 Red Mudstone 508 4 1 2.6 95.0 1 71.4 2 48.6 2 34.9 2 26.9 2 Red Mudstone 511 4 1 2.9 95.4 1 78.1 1 60.6 2 46.7 2 32.2 2 Red Mudstone 512 4 2 3.0 98.3 1 88.2 2 74.6 2 63.7 2 55.4 2 Red Mudstone 513 3 1 2.7 94.9 1 75.5 2 56.1 2 39.5 2 33.3 2 Red Mudstone 602 4 1 2.3 94.5 1 71.7 2 44.9 2 26.8 2 16.0 2 Red Mudstone 605 4 4 2.1 98.0 1 82.3 2 64.9 2 48.9 2 38.4 2 VF green Sandstone 606 4 4 1.9 98.8 1 93.6 2 86.1 2 76.8 2 67.8 2 VF green Sandstone 607 4 1 2.4 92.8 2 63.2 2 46.5 2 33.4 2 24.9 2 Red Mudstone 608 3 4 2.1 98.6 1 97.7 1 96.8 1 95.8 1 94.9 1 F green Sandstone 609 1 1 3.2 78.0 3 18.8 3 5.9 3 2.2 3 1.0 3 Red Mudstone 612 6 6 2.1 98.4 1 97.4 1 96.9 1 95.8 1 95.1 1 F green Sandstone 613 4 1 2.6 97.3 2 68.9 2 40.8 2 24.0 2 17.3 2 Red Mudstone 615 4 1 2.6 97.6 1 92.3 1 86.9 2 82.1 2 78.1 2 Red-green Mudstone 701 4 1 2.7 95.2 2 56.4 3 25.7 3 12.7 3 7.6 3 Red Mudstone 702 5 5 2.2 98.1 1 91.8 2 84.0 2 79.7 2 77.7 2 M green Sandstone

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Table 4.2.2: Continued

Sample Jar slake Moisture Id1 Id2 Id3 Id4 Id5 Remarks Number Air Oven Content(% % Type % Type % Type % Type % Type ) 703 4 4 2.8 97.9 1 91.2 1 81.2 2 74.0 2 68.7 2 Red Mudstone 704 4 1 2.4 96.7 2 78.3 2 64.6 2 56.6 2 51.4 2 Red Mudstone 705 4 5 2.8 98.1 1 91.7 2 81.9 2 74.4 2 67.5 2 Red Mudstone 706 5 5 2.4 98.3 1 97.0 1 95.8 1 94.6 1 93.6 1 F green Sandstone 708 4 1 2.7 97.0 2 76.9 2 48.3 2 28.8 3 16.6 3 Red Mudstone 801 4 3 1.9 93.9 1 85.1 2 80.8 2 77.6 2 74.2 2 F green Sandstone 809 4 3 2.0 98.7 1 97.6 1 96.6 1 95.8 1 95.0 1 F green Sandstone 815 6 6 1.8 98.8 1 97.9 1 97.2 1 96.6 1 95.9 1 F green Sandstone 820 5 3 1.9 98.4 1 97.1 1 96.2 1 95.3 1 94.6 1 F green Sandstone O3R 5 1 2.8 87.2 2 59.2 2 37.5 2 25.9 2 18.4 2 Brown Mudstone 1 1 1 5.3 73.0 3 19.4 3 5.2 3 1.2 3 0.2 3 Red Mudstone 2 1 1 6.2 86.5 2 20.4 2 13.5 2 12.5 2 11.7 2 Red Mudstone 3 1 1 3.6 59.2 2 20.0 2 14.5 2 13.4 2 11.4 2 Red Mudstone 5g 1 1 7.3 60.5 2 8.6 2 0.1 3 0.004 3 - - Green Mudstone 5r 4 3 5.6 93.9 1 77.6 2 66.8 2 56.9 2 49.3 2 Red Mudstone 6 4 1 3.7 97.4 1 81.4 2 61.4 2 41.2 2 24.2 2 Red Mudstone

Remarks : Slake durability index test Type 1 - Retained pieces remain virtually unchanged, Type 2 - Retained materials consist of large and small pieces, Type 3 - Retained materials are exclusively small fragments.

Jar slake index test (Ij) 1 – Degrades to a pile of flakes or mud, VF = Very Fine grained 2 – Breaks rapidly and/or forms many chips, F = Fine grained 3 – Breaks slowly and/or forms few chips, M = Medium grained 4 – Breaks rapidly and/or develops several fractures, 5 – Breaks slowly and/or develops few fractures, and 6 – No change.

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The number of samples falling into each jar slake index category is listed in Table 4.2.3. Separate results are given for as received (AR) and oven dried (OV) test conditions, as well as for the mudstone and sandstone samples.

Table 4.2.3: Summary of jar slake test data.

Overall Mudstone Sandstone Ij AR OV AR OV AR OV 6 3 3 0 0 3 3 % 4.9 4.9 0 0 25.0 25.0 5 7 5 2 2 5 3 % 11.5 8.2 4.1 4.1 41.7 25.0 4 33 10 30 7 3 3 % 54.1 16.4 61.2 14.3 25.0 25.0 3 2 5 1 2 1 3 % 3.3 8.2 2.0 4.1 8.3 25.0 2 6 5 6 5 - - % 9.8 8.2 12.2 10.2 0 0 1 10 33 10 33 - - % 16.4 54.1 20.4 67.4 0 0 Total 61 61 49 49 12 12

The results are shown graphically in the following figures. The full range of rock samples is plotted in Figure 4.2.2 and the mudstone and sandstone samples are plotted separately in Figure 4.2.3.

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40 As Received Oven Dried 30

20 Number

0 654321 Jar Slake Index

Figure 4.2.2: Bar graph showing the number of samples in each category from the Jar Slake Test, based on the overall rock samples.

From the classification of slaking characteristics described by Vallejo et al. (1993) (as shown in Table 4.1.1), the severity of slaking can be described in descending order based on the characteristic changes as Ij = 1, 2, 4, 3, 5 and 6. In other words, a rock with an Ij index of 4 may be considered as more slaking prone than a rock with an Ij index of 3, since the rock with Ij = 4 breaks down rapidly and develops more fractures. For convenience in this discussion, the jar slake indices are grouped in to:

1). Rocks with Ij indices of 1, 2 and 4. This group has a quick reaction to change in moisture, and rapidly develops fractures to form fragments or even completely disintegrates. This is defined as slaking prone behaviour. This group is referred to for the present discussion as the ‘slaking rock’ group.

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2). Rocks with Ij indices of 3, 5 and 6. This group is considered to be more stable than the ‘slaking rock’ group. The rocks slowly react with moisture change, and the result may be either the formation of a few chips or fractures or no change at all. This group is called the ‘stable rock’ group.

Approximately 54% of the samples tested were found to break down rapidly and/or develop several fractures (Ij = 4) when tested in an as-received condition (Table 4.2.3 and Figure 4.2.2). When tested in an oven-dried condition, a similar proportion of the samples degraded to a pile of flakes or mud (Ij = 1). From this it can be concluded that the initial moisture content has an effect on the breaking characteristics, i.e. dried samples display more severe breakdown on immersion in water. In the oven dried state, i.e. with a completely dried sample, it is suggested that air pockets are trapped and become more pressurized than in an equivalent moist sample when immersed in water, as has been discussed in the preceding chapter. The intermediate breakdown characteristics are unclear, however, for this set of samples. Forty nine (in as received condition) and forty eight (in oven dried condition) out of the total sixty one samples were found to act as ‘slaking rocks’ under the definition above. Generally, these rock samples can be classified as slaking prone, regardless of the rock type.

The jar slake index results are plotted separately for the mudstone and sandstone samples as shown in Figure 4.2.3.

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40 a). mudstone As Received mudstone Oven Dried 30

20 Number

0 654321 Jar Slake Index

10 b). sandstone As Received sandstone Oven Dried

5 Number

0 654321 Jar Slake Index

Figure 4.2.3: Bar graph showing the number of samples in each category for jar slake tests of mudstone (a) and sandstone samples (b).

Sixty one percent of the mudstone samples tested in the as-received state have Ij values of 4, and 67% of the same mudstones have Ij values of 1 when tested after oven drying (Table 4.2.3 and Figure 4.2.3a). None of the samples have Ij = 6; i.e. no mudstone samples are unaffected by the immersion test. More than 93% of the mudstones tested would be defined as slaking rocks from simple water immersion studies.

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For the sandstone samples (Table 4.2.3 and Figure 4.2.3b), an Ij index of 5 (breaks slowly and/or develops few fractures) is most frequently observed when the rock is tested in an as-received condition. An evenly distributed number of samples have Ij values of 3, 4, 5 and 6 when tested in the oven-dried condition. Ij values of 1 or 2 were not observed among the sandstone samples. Twenty five percent of the sandstone samples have Ij values of 4 under both as-received and oven-dried conditions, and thus are described as ‘slaking rocks’. Seventy five percent of the sandstone samples act as ‘stable rock’ under both as- received and oven-dried conditions. The rock type alone, however, should not be used as a guide for durability classification. Sandstone from the Patonga Claystone may act as a slaking rock, but is not as severely affected as the slaking mudstone from the same rock unit.

As can be seen from Figure 4.2.3, the sandstone and mudstone samples behave significantly different from each other. Most of the sandstone samples develop few fractures or even no change at all during the jar slake index test, while the mudstone samples develop several factures or even completely disintegrate. This is probably due to grain-to- grain contact of the quartz framework and the abundance of clay minerals in the sandstone and mudstone samples respectively. The quartz framework resists the breaking behaviour while the clay minerals promote the breaking characteristics. Another possibility to explain the different breaking characteristics between sandstones and mudstones is the pore size, as suggested by Vallejo, et al. (1993).

Among the mudstone samples themselves (Figure 4.2.3 top), when moisture content conditions prior testing are different, the jar slake index test suggests that in the oven-dried condition the breaking characteristics become

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more severe than in the as received condition. This is probably because the bulk of the voids are filled with air under extreme desiccation conditions (oven dried), but become pressurized by the capillary pressure when immersed in water, as discussed in Figure 4.1.1, Section 4.1.2.

4.2.3 Slake Durability Test

4.2.3.1 Slake Durability Test Results

Five-cycle slake durability tests were performed on sixty-one (61) rock samples for this study, using the method outlined in section 4.1.7.2. The results are listed in Table 4.2.2. Some of the slake durability test results are plotted in Figure 4.2.4 to show the type of variation encountered in the materials after different numbers of test cycles.

From Table 4.2.2 and Figure 4.2.4, it can be seen that the rock samples in this study have wide range of slake durability index values. The standard Id2 value ranges from 0 to 97.9% of the original dried weight. In other words, the slake durability test can be used successfully to distinguish between less durable rocks (low slake durability index), highly durable rocks (high slake durability index), and rocks with a range of characteristics in between.

The slake durability index for a given rock sample may be any value between 0 and 100% of the original dried weight, unlike the jar slake index which has values ranging only from 1 to 6 to identify the slaking characteristics. The slake durability test has therefore sorted the samples across a much wider range of possibilities in terms of slaking behaviour.

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100 504

80 615

606 60 512

40 513

20 O3R Slake Durability Index (%) 203 602

506 0 Id1 Id2 Id3 Id4 Id5

Tested Cycles

Figure 4.2.4: Plot illustrating the range of slake durability index results with different numbers of tested cycles.

As already discussed, the samples used in the present study were kept in core boxes for some 3 years before slake durability testing was carried out. A number of natural outcrop samples were also collected and tested for the same properties. The results of slake durability tests for the outcrop samples are also listed in Table 4.2.2.

The outcrop samples (sample numbers 1, 2, 3, 5g, 5r and 6) had a wide range of slake durability index values, ranging from 19 to 81% (Id2) and even decreasing to 0% for some cycles (Table 4.2.2). The results from the outcrop samples were consistent with those of the cored samples, i.e. similar minimum and maximum values, and similar disintegration modes, suggesting that long-term storage of

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the cored samples has had little impact on the rock durability. Therefore, despite the storage time, the test results on the cored samples were regarded, with some degree of confidence, as being equivalent to those likely to be obtained from newly exposed outcrop material.

Statistical evaluations of the slake durability data are listed in Table 4.2.4. The slake durability indices of the samples tested (Id2, Id3, Id5) vary respectively from 0 to 97.9%, 0 to 97.2% and 0 to 95.9%, with averages of 78.0,

66.1 and 53.1% for Id2, Id3 and Id5 respectively.

The median values (middle values) for the Id2, Id3 and

Id5 test results are 87.4, 76.7 and 55.4, while the modal

(most frequent) values are 97.7, 95.8 and 95.1% for Id2,

Id3 and Id5 respectively.

Table 4.2.4: Statistical summary of the slake durability test results.

Value Id1 Id2 Id3 Id4 Id5 Average % 92.1 78.0 66.1 58.1 53.1 Maximum % 98.8 97.9 97.2 96.6 95.9 Minimum % 3.3 0 0 0 0 Median 97.4 87.4 76.7 64.0 55.4 Mode 98.6 97.7 95.8 95.8 95.1 Standard deviation 16.66 22.47 29.45 32.12 33.06 Number of samples 61 59 58 58 58

A total of sixty-one samples were tested. Fifty-nine samples lasted through to second cycle testing, and fifty- eight samples resisted breakup through to the fifth cycle. Two of the samples (310 and 311) were totally disintegrated and dispersed under wet conditions in the second test

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cycle. These two samples were reported as having Id2, Id3 and Id5 values of 0%. 4.2.3.2 Rock Characteristics After Testing

During the tests, the material remaining after each wet cycle was observed before and after drying. The type of material remaining after each test was categorized into 3 types (Figure 4.2.5), as suggested by ASTM (1992), i.e.: Type 1 : Retained pieces remain virtually unchanged, Type 2 : Retained materials consist of large and small pieces, and Type 3 : Retained material is exclusively relatively small fragments.

The number of samples belonging to each category, after each test cycle, is listed in Table 4.2.5 and shown in Figure 4.2.6.

From Table 4.2.5 and Figure 4.2.6, it can be seen that 62% of the samples remained virtually unchanged (Type 1 mode of disintegration) after the first slake cycle. A total of 33% were assigned to type 2, and only 5% disintegrated rapidly after the first cycle. For the second cycle, the type 1 percentage decreased to 29%, type 2 rose to 60% and type 3 increased to 12%. The percentages with type 1 and type 2 disintegration characteristics remained nearly constant for the third, fourth and fifth cycles, at 21% and 60% respectively. The proportion of samples with type 3 characteristics increased significantly, to 21%, after the fifth cycle.

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0 scale 5cm

Figure 4.2.5: Illustration of fragment types retained during slake durability testing: Top: Type 1; Middle: Type 2; Bottom: Type 3.

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Table 4.2.5: Percentages of samples with each type of disintegration characteristics at each stage of the slake durability testing process.

Id Type 1 Type 2 Type 3 Total Number 38 20 3 Id1 61 % 62.3 32.8 4.9 Number 17 35 7 Id2 59 % 28.8 59.3 11.9 Number 12 36 10 Id3 58 % 20.7 62.1 17.2 Number 12 35 11 Id4 58 % 20.7 60.3 19.0 Number 12 34 12 Id5 58 % 20.7 58.6 20.7

Type 1 Type 2 Type 3 40

Number 20

0 Id1 Id2 Id3 Id4 Id5 Slake Durability Cycle

Figure 4.2.6: Bar graph showing the distribution of disintegration types for each slake durability cycle.

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% of Occurrence 20 Type 1 Type 2 Type 3 0 012345 Slake Durability Cycle

Figure 4.2.7: Changes in the percentage of cases with different disintegration types during the slake durability test.

Figure 4.2.7 illustrates the progressive change in the frequency of occurrence of each type of disintegration during the testing process. After the first cycle slake durability test, most of the samples (more than 62%) were found to have a Type 1 (unchanged) mode of disintegration. The Type 2 disintegration mode (large and small pieces) was represented by more than 32% of the cases. Type 3 (small fragments) was found to be the least occurring category, with only 5% of the total number of samples represented.

When the samples had undergone further wetting and drying in the slake durability test, Type 2 became the most significant mode of breakdown, involving approximately 60% of all samples. Type 1 decreased from about 60% (38 samples) to about 20% (12 samples) of the disintegration types as the test proceeded. Type 3 increased slightly in occurrence with further slake durability testing, with only 12 samples having a Type 1 disintegration mode after the

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3rd slake test cycle. The twelve Type 1 samples after 3 cycles represent a combination of 3 mudstones and 9 sandstones.

Many of the rock samples that are slaking prone as defined by jar slake tests and slake durability indices have retained fragments that are a combination of large and small pieces (Type 2). Although these rocks may have quite high slake durability indices, the disintegration mode suggests that the inhomogeneity of the rock samples or the microfracture pattern is the main factor in controlling the size of the rock fragments and the disintegration process.

4.2.3.3 Rock Types and Slake Durability

The durability classification proposed by Franklin and Chandra (1972) and Dick et al. (1994), based on the second cycle slake index, indicates that the rock samples can be grouped as listed in Table 4.2.6.

Table 4.2.6: Slake durability classification for samples tested.

Franklin and Chandra (1972) Dick et al. (1994) Terms Number of Number of Id2 (%) % Id2 (%) % samples samples Very low < 25 4 6.6 Low 25–50 6 9.8 < 50 10 16.4 Medium 50–75 9 14.8 50-85 19 31.2 High 75–95 28 45.9 > 85 32 52.5 Very high > 95 14 23.0

Two of the samples, surviving only the first cycle of testing, are included in the very low durability group of Franklin and Chandra (1972) and the low durability group of Dick et al. (1994).

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Regardless of the rock type involved, the above table indicates that most of the samples can be classified as highly durable rock (under both the Franklin and Chandra (1972) and the Dick et al. (1994) systems), with the individual percentages under each scheme being 45.9 and 52.5 respectively. In the Franklin and Chandra (1972) system, the summation of the percentage classed as very low, low and medium durability rock is only 31.2% of the total number of samples. The ratio of very low, low and medium durability rock to high and very high durability rock is 1:2.2. Under the system proposed by Dick et al. (1994), the ratio of low and medium to high durability rocks is only about 1:1. This is because Dick et al. (1994) used a wider range with fewer classes than Franklin and Chandra (1972).

As indicated in section 1.5.2, the rock samples used in this study can be grouped into sandstone and mudstone. There were 12 sandstone and 49 mudstone samples in the test program. The test results for each rock type are summarized in Table 4.2.7.

Table 4.2.7: Summary of slake durability and moisture data based on lithological characteristics.

Moisture Id2 Id3 Id5 Lithology % % % % Min 1.5 85.1 80.8 74.2 Sandstone Max 2.6 97.9 97.2 95.9 12 samples Average 2.0 96.0 94.2 91.6 Min 1.8 0 0 0 Mudstone Max 4.1 97.7 96.7 95.1 49 samples Average 2.8 73.5 58.8 43.0

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Table 4.2.7 depicts the differences in slake durability characteristics between the mudstones and the sandstones. Mudstones from the Patonga Claystone show a wider range of slake durability indices for all test cycles, while sandstones from the same formation give a narrow range of indices. Some of the rock samples in the mudstone group exhibit very high slake durability index values, making the average value higher than might otherwise be the case.

Two of the mudstone samples (samples number 310 and 311) and one mudstone sample (sample number 203) were totally disintegrated during the second and third wet cycle respectively. The development of total disintegration in the wet cycle is probably due to the high water absorption. Samples number 310 and 311 rapidly disintegrated during jar slake index and water absorption test resembling a pile of soil, i.e. over-saturated condition, and thus the water absorption values were discounted from the determination (Table 4.2.8). Sample 203 also had high water absorption characteristics (Table 4.2.8).

Sample number 131, a red mudstone, on the other hand, is classified as having very high durability, with Id2 of

97.7% and Id3 and Id5 values of 96.7 and 95.1% respectively. The other mudstone sample that has a very high slake durability index is sample number 134, with Id2,

Id3 and Id5 values of 96.3, 93.8 and 89.2% respectively. This rock sample is grouped with the mudstones because of its fine grain size. These samples show that mudstone may have a high slake durability, and that some factors apart from grain size plays a role in controlling the slaking characteristics of the Patonga Claystone.

The moisture content (minimum, maximum and average values) of the mudstone samples is higher than that of the

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sandstones. This can be explained by the ability of mudstone to absorb and retain more moisture due to its fine but abundant void spaces, and by the abundance of the clay minerals, especially the smectite in the I/S (Chapter 3). The maximum slake durability values for sandstone and mudstone are approximately the same after the 2nd, 3rd and 5th slaking cycles. However, the wetting and drying process apparently leads to more rapid deterioration of the mudstone. This is indicated by the average and minimum values of the respective slake durability indices. For mudstone, the minimum slake durability indices for the 2nd, 3rd and 5th cycles are 8.1, 3.4 and 0.1, whereas for sandstone the equivalent values are 85.1, 80.8 and 74.2% respectively. The average slake durability index for mudstone is also lower than for sandstone (Table 4.2.7).

4.2.4 Water adsorption

Forty (40) samples were subjected to water adsorption tests, using the procedure outlined in section 4.1.7.3. The results are listed in Table 4.2.8. Minimum and maximum values are 2.22 and 4.15% respectively, with an average of 3.06% and standard deviation of 0.46.

4.2.5 Water absorption

Fifty-eight (58) samples were tested for their water absorption properties, using the procedure outlined in section 4.1.7.4. The results, listed in Table 4.2.8, show a wide range of values, with minimum and maximum of 3.20 and 29.70%, an average of 9.75%, and a standard deviation of 5.23.

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Table 4.2.8: Water adsorption and absorption testing.

Sample Adsorption Absorption Sample Adsorption Absorption No % % Rock Type No % % Rock Type 130 - 5.49 Green VF Sabdstone 414 2.89 7.09 Red Mudstone 131 - 4.03 Red Mudstone 501 2.68 8.78 Red Mudstone 132 2.61 5.52 Red Mudstone 502 2.23 5.41 Red Mudstone 133 2.56 6.50 Red Mudstone 504 2.22 4.53 F green Sandstone 134 2.68 5.37 Red Mudstone 506 3.33 11.11 Red Mudstone 135 3.31 10.26 Red Mudstone 508 2.42 11.41 Red Mudstone 136 - 8.53 Red Mudstone 511 3.46 11.93 Red Mudstone 137 - 9.92 Green-red Mudstone 512 3.29 8.63 Red Mudstone 138 - 4.06 Red Mudstone 513 3.12 11.75 Red Mudstone 139 - 11.08 Red Mudstone 602 2.35 6.96 Red Mudstone 140 3.32 12.64 Red Mudstone 605 2.65 7.26 VF green Sandstone 141 3.51 8.40 Red Mudstone 606 2.42 4.58 VF green Sandstone 142 3.44 9.85 Red Mudstone 607 2.60 6.80 Red Mudstone 143 3.43 16.57 Red Mudstone 608 2.88 4.28 F green Sandstone 144 3.42 8.72 Red Mudstone 609 3.64 17.57 Red Mudstone 145 3.43 13.88 Red Mudstone 612 - 4.12 F green Sandstone 146 3.27 9.17 Red Mudstone 613 3.18 8.77 Red Mudstone 203 3.70 16.72 Red Mudstone 615 - 8.21 Red-green Mudstone 205 2.78 5.33 F green Sandstone 701 3.36 9.69 Red Mudstone 211 - 11.64 Red Mudstone 702 2.75 4.25 M green Sandstone 212 - 24.40 Red Mudstone 703 - 9.10 Red Mudstone 213 - 9.12 Red Mudstone 704 3.17 7.64 Red Mudstone 214 - 13.07 Red Mudstone 705 - 7.46 Red Mudstone 215 - 16.14 Red Mudstone 706 2.75 4.20 F green Sandstone 216 - 12.30 Red Mudstone 708 3.35 9.03 Red Mudstone 217 - 9.72 Red Mudstone 801 - 9.61 F green Sandstone 310 4.15 - Red Mudstone 809 - 5.37 F green Sandstone 311 3.46 - Red Mudstone 815 2.42 3.20 F green Sandstone 312 3.54 29.70 Red Mudstone 820 - 4.53 F green Sandstone 313 3.23 24.70 Red Mudstone O3R - 10.73 Brown Mudstone 409 3.23 12.58 Green Mudstone Remarks : VF : Very fine grained, F : Fine grained, M : Medium grained

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A statistical summary of the water adsorption and absorption properties, differentiated by rock type, is given in Table 4.2.9. Mudstone and sandstone have the same minimum value for water adsorption, but differ in other values. The high degrees of adsorption and absorption of the mudstones compared to the sandstone samples is in most cases due to the high fracture porosity of the mudstones and the high proportion of clay minerals, especially the smectite in the I/S (Chapter 3).

Table 4.2.9: Water adsorption and absorption results based on rock type.

Mudstone Sandstone Adsorption Absorption Adsorption Absorption Minimum 2.23 4.58 2.22 3.20 Maximum 4.15 29.70 2.88 9.61 Average 3.13 10.89 2.63 4.85 Median 3.28 9.69 2.75 4.28 Number 34 47 6 11

4.2.6 Relation of Other Parameters to Slake Durability Index

The test results have been subjected to mathematical correlation, testing the other parameters discussed in this Chapter against the slake durability index. The purpose of this task was to identify some of the factors that control the slake durability index.

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4.2.6.1 Moisture content and slake durability

A plot of the ‘as received’ moisture content against the slake durability index of the second, third and fifth cycles is shown in Figure 4.2.8.

Figures 4.2.8(a), (b) and (c) show a wide scattering pattern of plotted points, giving a poorly defined correlation. However, the data suggest that rock specimens in the test program with a remaining moisture content of less than 3% tend to have high 2nd cycle slake durability index values (Figure 4.2.8(a).

Figures 4.2.8(b) and (c) show a less clear correlation between the remaining moisture content and the 3rd and 5th cycle slake durability indices. However, the overall trend of the correlation seems to indicate that a rock sample with high moisture content still has relatively low slake durability indices.

Linear regression analysis was employed to define more precisely the correlations between the second, third and fifth cycle slake durability indices and the as sampled moisture content discussed above. A negative correlation was found in all cases (i.e. slake durability decreases as moisture content increases), with coefficient of 2 considerations (R ) for Id2, Id3 and Id5 of 0.29, 0.32 and 0.31 respectively. Even though the data are scattered, the trend of the relationship can be seen from the graphs in Figure 4.2.8. This relationship suggests that the slake durability index is related to other geotechnical properties affecting moisture content, such as clay-size particle content, mineralogy, porosity, density and water absorption. These relationships are discussed further in Chapter 5 and 7.

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4.0

3.0

2.0

y = -0.01x + 3.51 Moisture content (%) a). R2 = 0.29 1.0 0 20406080100 Id2 (%)

4.0

3.0

2.0

y = -0.01x + 3.22 Moisture content (%) b). R2 = 0.32 1.0 0 20 40 60 80 100 Id3 (%)

4.0

3.0

2.0

Moisture content (%) y = -0.01x + 3.04 c). R2 = 0.31 1.0 0 20406080100 Id5 (%)

Figure 4.2.8: Moisture contents plot against slake durability index as 2nd cycle (a), 3rd cycle (b), and 5th cycle (c).

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4.2.6.2 Jar slake index against slake durability

Because the samples had to be oven dried before the slake durability test, the slake durability data were compared to the oven dried results for the jar slake index test. Plots of oven dried jar slake index data against the results from various cycles of slake durability are shown in Figure 4.2.9.

Figure 4.2.9(a) indicates that an Ij value of 1 (degrade to a pile of flakes or mud) occurs in rocks with a wide range of slake durability indices, while Ij values of 2, 3, 4, 5 and 6 occur in rocks with a narrower range of higher Id2 values (from 80 to 99%). It would be expected that rock specimens with an Ij value of 1 would have very low durability. However, the rock specimens categorized as having an Ij value of 1 have a wide range of second cycle slake durability indices (from 8 to 96 %). This is probably because the rock specimens used in the slake durability test break up into small pieces, but nevertheless remain large enough to be retained in the test drum.

Clearer patterns are seen as the slake durability tests proceed, where rock samples having Ij values of 1 progressively reveal lesser durability characteristics.

Only a few samples with Ij = 1, for example, have Id5 values greater than 60%. Rock samples having Ij values of 2, 3, 4, 5, and 6 have lower slake durability indices after the 3rd and 5th slaking cycles, but even so have indices that are significantly higher than the samples with Ij values of 1. Only a few samples with Ij values of 2 or more have 5th cycle slake durability values of less than

60%, whereas almost all those with Ij = 1 have Id5 values below this figure.

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6 a). 5

Jar slake index 1

0 0 20406080100 Id2 %

6 b). 5

1 Jar slake index

0 020406080100 Id3 %

6 c). 5

Jar slake index 1

0 0 20406080100Id5 %

Figure 4.2.9: Oven dried jar slake index plotted against 2nd cycle (a), 3rd cycle (b), and 5th cycle (c) slake durability data.

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6 a). 5

1 AR - Jar slake index

0 0 20406080100Id2 %

6 b). 5

1 AR - Jar slake index

0 0 20406Id3 % 080100

6 c). 5

1 AR - Jar slake index

0 0 20406080100Id5 %

Figure 4.2.10: Air dried jar slake index plotted against 2nd cycle (a), 3rd cycle (b), and 5th cycle (c) slake durability data.

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The slaking characteristics of the ‘as received’ samples tested by the jar slake index test were plotted against the slake durability index values to investigate any relationship between these two parameters. Plots of the as received jar slake index data against the results from various cycles of slake durability are shown in Figure 4.2.10.

Figure 4.2.10(a) shows that rocks with an as-received

Ij value of 1 all have low slake durability indices (Id2 < 50%), while rocks with Ij values of 2, 3, 4, 5 and 6 have higher slake durability indices (Id2 > 50%). The rock specimens with an Ij value of 1 have even lower low slake durability indices (<20%), as shown in Figures 4.2.10(b) and (c), as the slake durability tests proceed. Some of these rock samples break up completely on testing through to the fifth cycle.

Figures 4.2.10(b) and (c) show that rock samples with Ij values of 2, 3, 4 and 5 have a wide range of 3rd and 5th cycle slake durability indices, although in most cases the

Id3 and Id5 values are lower than the Id2 values for the same rock specimens. Samples with Ij = 4 from as-received tests show a particularly wide range of slake durability values, with some being as low as those with Ij = 1 and some having slake durability indices comparable to rocks with Ij = 2, 3 or 5. In all cases, however, rock samples with an Ij value of 6 (‘no change’) still have very high slake durability indices (about 95%), even after the 5th cycle of testing.

From the above discussion it appears that the jar slake index test can be used as a guide for assessing the durability of a rock specimen, i.e. rock with an Ij value of 1 would be expected to have low slake durability while rock having an Ij value of 6 would have high slake

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durability characteristics. Although rocks with other Ij values may be expected to have intermediate slake durability properties, rocks with an Ij value of 4, when tested in the as-received state, may either break up or resist breaking up when subjected to prolonged exposure through the slake durability test.

4.2.6.3 Water adsorption and slake durability

The water adsorption results for the samples studied are plotted against slake durability index in Figure 4.2.11. The water adsorption values show a poorly-defined negative correlation with the slake durability index. R2 values for the 2nd, 3rd and 5th wet and dry cycles are 0.24, 0.18 and 0.15 respectively. Although the scatter is high and the coefficient of consideration is low, the overall trends show that rocks with low durability tend to have high water adsorption values. Even so, water adsorption would seem to be of limited value as an indicator of durability. Samples with less than 3% adsorption tend to have high second cycle durability, but those with more than 3% adsorption may have durability indices that range from low to high. The distinction is less clear-cut, moreover, for the 3rd and 5th cycle durability results.

The relations of water adsorption to slake durability for the two different rock types, mudstone and sandstone, are shown separately in Figure 4.2.12.

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5.0 y = -0.01x + 3.74 R2 = 0.25 4.0

3.0

2.0 a). Water adsorption % 1.0 0 20406080100Id2 %

5.0 y = -0.01x + 3.41 R2 = 0.18 4.0

3.0

2.0 b).

Water adsorption % 1.0 0 20 40Id3 % 60 80 100

5.0 y = -0.01x + 3.25 R2 = 0.15 4.0

3.0

2.0 c). Water adsorption % 1.0 0 20406080100Id5 %

Figure 4.2.11: Plot of water adsorption for all samples against slake durability index. Top: 2nd cycle, Middle: 3rd cycle, Bottom: 5th cycle.

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The sandstones have water adsorption values of between 2 and 3%. With one exception (sample number 605), they have high slake durability index values. Those mudstones that have a water adsorption value of less than 3% also tend to have relatively high slake durability indices. The mudstones with a water adsorption value of greater than 3%, however, have a much more variable range of slake durability behaviour, with individual samples having Id values, especially after 3 or more cycles, ranging almost from 0 to 100%.

From the coefficient of considerations (R2) listed on the graph, it is clear that degree of water adsorption also has limited value as a predictor of slake durability for either the mudstones or the sandstones used in this study.

However, the trends of these relations suggest that rocks with high durability index values tend to have low values for water adsorption. The mudstones with the lowest slake durability indices after the second cycle (Figure 4.2.12a) have the highest water adsorption values. The contrast between the water adsorption of these and the other samples, however, is very small, limiting the value of water adsorption as an indicator of slake durability for the mudstone materials.

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5 5 a). d).

4 4

3 3

2 2 % Water adsorption y = -0.01x + 3.65 y = -0.03x + 5.79 2 % Water adsorption R = 0.18 R2 = 0.09 1 1 0 20406080100Id2 % 70 80Id2 % 90 100

5 5 b). e).

4 4

3 3

2 2 % Water adsorption y = -0.00x + 3.35 % Water adsorption y = -0.01x + 3.97 R2 = 0.10 R2 = 0.08 1 1 0 20406080100 Id3 % 70 80 Id3 % 90 100

5 5 c). f).

4 4

3 3

2 2 y = -0.00x + 3.20 % Water adsorption 2 % Water adsorption y = -0.01x + 3.67 R = 0.04 2 R = 0.09 1 1 0 20406080100 Id5 % 70 80Id5 % 90 100

Figure 4.2.12: Water adsorption against slake durability in mudstone samples, a) 2nd cycle, b) 3rd cycle, c) 5th cycle, and sandstone samples, d) 2nd cycle, e) 3rd cycle, f) 5th cycle.

The rock breaking characteristics of the samples were observed during the progress of water adsorption test. All

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of the rock specimens showed ‘no change’, Ij = 1 as defined by Vallejo et al. (1993), during the humidity absorption process. Water adsorption mainly represents the water held by or attached to the clay minerals. The difference in degree of water adsorption behaviour between mudstone and sandstone is therefore probably due to the difference in the proportion of expandable clay minerals as already discussed in Chapter 3. Hence mudstones having higher overall proportions of expandable clay minerals have lower slake durability indices than sandstones with lower clay contents.

4.2.6.4 Water absorption and slake durability

Water absorption represents the water held in the fractures and pore spaces of the rocks, as well as that attached to the clay minerals. Water absorption is plotted against slake durability index in Figure 4.2.13. Rock samples with water absorption values greater than 15% tend to have slake durability index values (2nd cycle) less than 50% (Figure 4.2.13a), less than 20% in the 3rd slake durability cycle (Figure 4.2.13b) and less than 10% in the 5th slake cycle (Figure 4.2.13c). It is also quite clear that rock samples, with some exceptions, having water absorption values of less than 10% have high slake durability indices (i.e. greater than 60% in the 5th slake cycle).

Based on these data, rock samples with a high degree of water absorption tend to have low slake durability indices, especially when the tests proceeds for a longer time. In other words, high water absorption values indicate less durable rock materials. When considered against the slake durability classification of Dick et al. (1994), the rocks can be subdivided, with some exceptions,

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into high (water absorption < 10% with Id2 > 85%), medium

(water absorption between 10 and 15% with Id2 between 50 and 85%) and low durability materials (water absorption >

15% with Id2 < 50%), based on their water absorption characteristics.

Figure 4.2.13 shows a greater degree of discrimination between the samples based on slake durability than does Figure 4.2.11. R2 values for the 2nd, 3rd and 5th slake cycles are 0.62, 0.58 and 0.47 respectively. This suggests the possibility of using water absorption as a predictor of slake durability behaviour.

The water absorption and slake durability index are plotted separately for the mudstone and sandstone samples in Figure 4.2.14.

The sandstones, with one exception (Sample 801), have water absorption values of 3 to 6%, while the mudstones have water absorption values of between 3 and 30%. Those sandstones with water absorption of <6%, again with one exception (Sample 605), all have high slake durability indices (>90%), regardless of the number of cycles tested. Even the sandstones with lesser index values would still be regarded as quite durable materials (Id > 70%).

The mudstones fall into two groups in Figure 4.2.14a: those with <15% water absorption, which with one exception have durability indices (Id2) >60%, and those with >15% water absorption, which have Id2 values <60%. Although many of the mudstones with <15% water absorption exhibit lower slake durability indices with increasing numbers of cycles, this relationship suggests that water absorption can provide a good indicator of slake durability within the mudstone group.

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30.0 y = -0.18x + 23.99 R2 = 0.62 20.0

10.0

a). Water absorption % 0.0 0 20406080100Id2 %

30.0 y = -0.13x + 18.43 R2 = 0.58 20.0

10.0

b). Water absorption % 0.0 0 20406080100Id3 %

30.0 y = -0.11x + 15.31 R2 = 0.47 20.0

10.0

c). Water absorption % 0.0 0 20406080100Id5 %

Figure 4.2.13: Plots of water absorption against slake durability index. Top: 2nd cycle, Middle: 3rd cycle, Bottom: 5th cycle.

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30 12 d). y = -0.17x + 23.10 R2 = 0.56 20

10 y = -0.36x + 38.98 R2 = 0.70

% Water absorption a). %Water absorption 0 0 0 20406080100Id2 % 70 80 Id2 % 90 100

30 12 y = -0.12x + 18.04 e). R2 = 0.49 20

y = -0.20x + 24.00

% Water absorption 2

% Water absorption b). R = 0.49 0 0 0 2040 6080100 Id3 % 70 80Id3 % 90 100

30 12 f). y = -0.10x + 15.10 R2 = 0.34 20

6 10

y = -0.15x + 18.60 % Water absorption c). 0 R2 = 0.47 % Water absorption % Water 0 020406080100Id5 % 70 80 Id5 % 90 100

Figure 4.2.14: Water absorption against slake durability in mudstone samples, a) 2nd cycle, b) 3rd cycle, c) 5th cycle, and sandstone samples, d) 2nd cycle, e) 3rd cycle, f) 5th cycle.

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4.2.6.5 Slake durability decay index

Following the procedure suggested by Smith (1986), the percentage of material retained during the slake durability tests was plotted against the rotation time (Figure 4.2.15). Extrapolations were then performed back to 100% retained and forward to 0% retained, to simulate the start and end points of each rock’s decay under the slaking test. The area under curve was calculated by joining the plotted points into a polygon figure.

Highly durable rock has a greater area under the curve (slake durability index * minutes) in such a plot (e.g. rock sample number 608 with Id2 of 97.7% has an area under the curve of 54896.9) than less durable rock (e.g. rock sample number 609 with Id2 of 18.8% has an area under the curve of 1558.2). The square root of the area, identified by Smith (1986) as the slake durability decay index, was calculated, and plotted against the percentage of water absorption (see Section 4.2.5) as shown in Figure 4.2.16.

The relationship between the slake durability decay index and water absorption was found to be in the power form with an equation of:

y = x*35.641 − 91.0 where: y = slake durability decay index x = water absorption (%) with an R2 value of 0.59. The above equation implies that rock with low water absorption will have high slake durability index, which is in turn related to large area under the decay curve, i.e. high durability.

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100

60 Decay Curve

40 Area under Decay Curve

Percent Retained 20

0 0 10203040506070 Time - minutes

Figure 4.2.15: Decay curve – slake durability index against time, sample number 708 is shown here.

500

Highly Inter Less Durable mediate Durable 400

300

-0.91 200 y = 641.35x R2 = 0.59

100 Slake Duarbility Decay Index Duarbility Decay Slake 0 010203040 Water Absorption (%)

Figure 4.2.16: Slake durability decay index and water absorption.

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The slake durability decay index is very high for highly durable rocks, whereas less durable rocks tend to have lower areas under the curve and lower decay index values. Figure 4.2.16, together with Figure 4.2.13, shows that, with some exceptions, the rock samples can be grouped according to the relation of slaking behaviour to water absorption characteristics as highly durable, intermediate and less durable, as listed in Table 4.2.10:

Table 4.2.10: Durability classification based on 2nd slake durability cycle and water absorption for the present study.

Water absorption % Durability Property < 10 Highly durable 10-15 Intermediate >15 Less durable

4.2.7 Concluding Summary

The samples in the study have been subjected to two different types of testing to assess their durability characteristics on interaction with water, the jar slake test and the slake durability index test procedure.

The jar slake test, based on simply immersing small specimens of the samples in water, was found to distinguish slaking from non-slaking rock materials. Significant differences were found between samples tested in the air- dried state and samples of the same materials that were oven-dried before the test procedure.

The oven-dried mudstone samples showed more severe degradation than equivalent air-dried mudstones. Little

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difference was seen, however, for oven-dried or as-received sandstones in the jar slake procedure. The slake durability test was successfully used to evaluate the durability properties of the rock samples studied. The test distinguishes high durability rocks from low durability rocks and from rocks with intermediate properties. The indices range from 0 to 100%, with low indices indicating less durable rock and high indices suggesting high durability rock materials.

The second cycle slake durability index was used in the classification, as recommended by the standard method. Some rocks classified as high durability according to the scheme of Franklin and Chandra (1972) would be described as medium durable rock under the classification system proposed by Dick et al. (1994). Hence, any classification based on slake durability should also quote the system used.

Some rock samples classified as high or medium durability (depending on the system) may nevertheless be broken up into small pieces during the slake durability test, although the fragments are still large enough to be retained on the 2 mm used in the slaking apparatus. Despite its high slake durability index, this type of rock material may not be suitable for some engineering projects. It could not, for example, be used as riprap. Therefore, in the study of rock slaking and durability, the type of disintegration should be noted in the report as well as the durability index.

The water absorption test could be used as a guide to rock durability assessment. Rocks with high degree of water absorption tend to have lower durability indices.

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The results obtained from the drill core samples, in terms of slake durability index and mode of disintegration, are consistent with those obtained from the outcrop samples. This suggests that the use of core samples in the durability study provides results that are comparable to the behaviour of the Patonga Claystone in near-surface excavations. Storage of the core samples seems to have had no significant influence on rock durability.

CHAPTER 5

OTHER GEOTECHNICAL PROPERTIES

5.1 Introduction

This chapter deals with previous engineering geology studies of the Patonga Claystone as well as engineering geology, testing procedures and results of additional laboratory tests conducted for the present study. It concentrates on geotechnical properties other than the slake durability and water sorption characteristics, which are discussed in Chapters 4.1 and 4.2.

5.2 Previous Studies

The Electricity Commission of New South Wales carried out site investigation for Mardi Power Station and associated water circulating system in 1983 (Figure 5.1) (ECNSW 1983a and b). The power station site was located on Deep Creek, 5 km west of Tuggerah Lake and 3 km west of Wyong. For circulation of cooling water it was planned to drain water from and return heated water to Chittaway Bay in Tuggerah Lake.

Point load strength index testing was performed on samples that had been immediately placed into plastic sleeves after removal from the core barrel, and samples were tested in an air-dried condition for Uniaxial Compressive Strength (UCS). The Patonga Claystone materials were grouped into four subgroups according to 225

colour, grain size and lithology: red-brown mudstone, sandstone, green-grey mudstone/siltstone, and interbedded siltstone/sandstone (ECNSW, 1983). The results of point load strength index and UCS tests performed by the Electricity Commission of New South Wales are summarized in Table 5.1.

Figure 5.1: Location map showing areas of previous study.

The natural moisture content (NMC or MC) of completely weathered mudstones from the Patonga sequence was reported as 20.5, 23.3 and 17.7 %, with a plasticity index (PI) of 24, 27 and 24 % respectively (ECNSW, 1983a). These 226

properties suggest a high clay content and a high porosity for the Patonga Claystone.

Table 5.1: Summary of mean point load and UCS test results for rocks from the Patonga Claystone (ECNSW, 1983).

Rock type and Point load Is(50) Mpa UCS Weathering grade Diametral Axial MPa Red-brown mudstone MS 0.2 0.2 - SW 0.3 0.3 5.7 FS 0.4 0.4 - FR 0.5 0.5 9.2

Sandstone HW 0.3 0.4 - MW 0.6 0.9 8.6 SW 1.1 1.3 26 FS 1.0 1.4 - FR 1.4 1.7 27

Green-grey mudstone/ siltstone SW - 0.1 - FR 0.5 0.5 4.6

Interbedded siltstone/sandstone FR 0.6 0.8 5.2

FR = fresh, SW = slightly weathered, MW = moderately weathered, HW = highly weathered

Table 5.1 suggests that the point load strength of freshly drilled samples of Patonga Claystone has a degree of anisotropy of approximately one. Such an anisotropy (Section 5.3.5) indicates that the rock has equal strength regardless of the direction of testing. The fresh mudstones and sandstones of the Patonga Claystone can be classified from their point load strength index as ‘low to medium’ and ‘medium to high’ strength materials respectively.

Fresh and slightly weathered mudstones, tested for uniaxial compressive strength, show slightly different 227

strength values, varying between 5.7 and 9.2 MPa (Table 5.1). This mudstone is therefore classified as ‘weak’ as suggested by IAEG (c.f. Table 5.10). Fresh and slightly weathered sandstone have higher UCS values and can be classified as ‘moderately strong’ under the same system. Moderately weathered sandstone, however, has a lower compressive strength compared to fresh and slightly weathered sandstone, and can be classified as a ‘weak’ rock material (Table 5.10). Fresh and slightly weathered mudstones have a similar strength to moderately weathered sandstone, fresh mudstone/siltstone and interbedded siltstone/sandstone (Table 5.1).

Generally the ratio of UCS to Is(50) ranges from 10 to 45 for most rocks (McNally and McQueen, 2000), or from 6 to 37 according to Chau and Wong (1996). For the Patonga Claystone test results listed in Table 5.1, the UCS appears to be within the latter range, falling between 6.5 and 23.6 times the Is(50) values.

Dispersion testing by the Pinhole test method (Sherard et. al. 1976b) was carried out on three disturbed, completely weathered mudstones by ECNSW (1983a), with results as shown in Table 5.2. The Pinhole test involes using standard cylindrical specimen (38 mm in length with a 1.0 mm diameter hole along the axis) which is subjected to hydraulic heads of 50, 180 and 380 mm (Sherard, et al., 1976b). The time elapsed and the quantity of flow through the pinhole is measured, and any turbidity observed. The enlargement of the hole due to erosion under the different hydraulic gradients is also measured. Generally, the Pinhole test result is used to divide samples into the following categories: D1, D2 (highly dispersive soil), ND1, ND2 (nondispersive soil), and ND3, ND4 (intermediate 228

dispersion). The ECNSW (1983a) tests revealed that the completely weathered mudstone is non-dispersive (ND1, ND2) in seawater, but has intermediate dispersion (ND4) properties (dispersive to non-dispersive) in fresh water. The non-dispersive behaviour of the mudstones in seawater may help to explain the differences observed in slaking characteristics of outcrops exposed to air and to seawater. Air exposed outcrops deteriorate quickly to form rock chips, while seawater outcrops form hard ground.

The difference in slaking characteristic between outcrops exposed to air and to seawater may be due to the fact that clay minerals will flocculate in saline conditions but will disperse in fresh water. This is associated with cation ion exchange reactions and and the double-layer theory. Alternatively, it may be due to the unchanged levels of of moisture content in the marine exposures, compared to those on land, or possibly due to continual washing away of any loosened debris by wave and/or wind action so that fresh rock is always exposed. The flocculation of clay minerals is thought to be a better explanation of the difference than washing away of the debris by wave action. The rock outcrops have been exposed for a very long time to sea water, but have not been eroded away to a significantly greater extent than the other strata in the area.

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Table 5.2: Dispersion test results for Patonga Claystone samples (ECNSW, 1983a).

MC P.I. Pinhole dispersion classification Sample (%) (%) Seawater Freshwater 7S 20.5 24 ND1/ND2 ND4 8S 23.3 27 ND1 ND2 10S 17.7 24 ND1 ND4 ND1, ND2 = nondispersive soil, ND4 = intermediate soil - erode slowly, MC = Moisture content %, P.I. = Plasticity Index.

One of the index tests used in the study of soil and highly to completely weathered rock is determination of the Atterberg limits (Akroyd, 1957, Chandler, 1969, Taylor and Smith, 1986, Cripps and Taylor, 1987, Dick and Shakoor, 1992). Three properties, i.e. liquid limit, plastic limit and shrinkage limit, are tested and the results widely used in geotechnical studies. The Atterberg limits depend on the proportion of clay size particles in the sample, and also on the clay mineralogy (Dumbleton and West 1966a, Taylor and Smith, 1986). High proportions of clay size material give rise to high liquid limit, high plastic index (liquid limit – plastic limit) and high shrinkage limit values. Changes in plasticity index at different depths in the same soil unit, or in the same sample under different treatment conditions, indicate changes in the proportion of clay size material and/or changes in proportion of different clay mineral types (Chandler, 1972, Grainger and Harris, 1986).

One particular test method, called the ‘Shale Test’, involves determining the change in plasticity index after one or more cycles of wet and dry accelerated weathering followed by a compaction test (Hatcher, 1963, Minty and Smith 1980, Stephens, 1994). This test, standardized by the Roads and Traffic Authority of New South Wales as Test 230

Method T103, has been designed to evaluate shale for road construction. Repeated compaction is the main part of the test, at the end of each compaction grain size analysis and the Atterberg limit determinations are performed to investigate any changes in particle size. Stephens (1994) has carried out this test on fresh mudstone and determined the plasticity index after 0, 5 10 and 15 wet/dry cycles. The plasticity index after various cycle is shown in Table 5.3. Complete degradation of the test sample occurred in this case during the 5th wet/dry cycle. From such results, it can be concluded that ‘Shale Test’ has the effect of breaking down the crushed rock fragments, but has little or no effect on the plasticity index. In other words the proportion of clay size material remains the same, based on little change of the plasticity index (Table 5.3). This test method was therefore not considered for testing the slaking behaviour of the Patonga Claystone for the present study.

Table 5.3: Change in plasticity index after change in wet and dry cycles in ‘Shale Test’ (Stephens, 1994).

Number of Plasticity index wet/dry cycles 0 18 5 21 10 20 15 21

Triaxial compression test data on the Patonga Claystone from investigations for the Kincumber/Outfall Tunnels (Figure 5.1) were also made available for the study (Table 5.4) (Golder Moss, 1974). The tests were performed on fresh sandstone, siltstone and interbedded sandstone and siltstone. The test results are listed in Table 5.4, along with the average values for siltstone, interbedded 231

siltstone-sandstone and sandstone from the Patonga Claystone samples.

Table 5.4: Residual parameters from triaxial test on Kincumber/Outfall Tunnel Project (Golden Moss, 1974).

Parameters Cr MPa φr degree Siltstone 6.2 32.5 Interbedded 6.5 27 Sandstone 4.7 36

Residual strength from the triaxial compression test

(Cr, φr) is defined as the strength in the state where there is no change in shear strength in the triaxial cell

(Akai, 1997). Residual cohesion (Cr), evaluated by the triaxial test (Table 5.4) ranged from 1.5 to 10 MPa for sandstones of the Patonga Claystone, with the residual internal friction angle (φr), ranging from 20 to 42 degrees. Interbedded rocks and siltstones both gave similar results, with residual cohesion ranging from 3.2 to 13.1 MPa and residual internal friction angle varying from 19 to 33 degrees. Only one siltstone, however, was tested for triaxial compressive strength. From Table 5.4 it can be seen that the sandstone in the Patonga Claystone has a lower residual cohesion but higher residual internal friction angle than the siltstone. These results indicate that sandstone will have fewer problems in slope excavation than siltstone or interbedded rocks, i.e. sandstone in the sequence can be cut at higher slope angles.

The elastic modulus (E) is defined as ratio of axial stress to strain and expressed in units of GPa. A strain gauge is attached to a core sample to measure changes in length in the axial direction. The strain is then plotted 232

against the axial stress at a particular point (Figure 5.2). Since the stress-strain curve for rock is rarely linear, the standard value quoted for elastic modulus is usually the slope of a tangent or a secant to the curve at a stress equal to half the maximum stress (Farmer, 1983). The steeper the slope the higher the modulus, and also the higher the rock strength.

Strong rock

Stress

Medium strength

Weak rock

Axial strain

Figure 5.2: Typical stress-strain curves in compression test (modified from Farmer, 1983).

The ratio between the elastic modulus (or deformation modulus E) and the UCS is used to define a modulus ratio (Farmer, 1983, Brady and Brown, 1985). Modulus ratio values of 200 and 500 are used to define materials with low or high modulus ratios. Rock substances with a modulus ratio of 200:1 are defined as having a low modulus ratio, while rocks with modulus ratio of 500:1 are categorized as having a high modulus ratio (Farmer, 1983).

Poisson’s ratio (µ) is defined as the ratio of the induced lateral strain to the longitudinal strain in the direction of applied axial stress. In sound and hard rocks, which are effectively incompressible, Poisson’s ratio is of a magnitude about 0.15 (Jumikis, 1979). 233

Uniaxial compressive tests with elastic modulus and Poisson’s ratio determinations were executed during the investigation work for the Kincumber Outfall Tunnels (Golder Moss, 1974). Most of the samples tested were sandstone and siltstone, ranging in uniaxial compressive strength, elastic modulus and Poisson’s ratio as listed in Table 5.5.

Table 5.5: Summary of previous UCS and related results (Golder Moss, 1974).

UCS Elastic Poisson’s Parameters MPa modulus GPa ratio Siltstone Minimum 15.4 1.2 0.18 Maximum 24.0 2.6 0.42 Average 18.7 1.8 0.40 Sandstone Minimum 32.4 3.3 0.16 Maximum 62.0 8.8 0.40 Average 43.3 5.8 0.30

Siltstone and sandstone at the site had uniaxial compressive strengths ranging from 15.4 to 24.0 and 32.4 to 62.0, with average values of 18.7 and 43.3 MPa respectively (Table 5.5). The average elastic modulus for siltstone and sandstone were 1.8 and 5.8 Gpa, and average Poisson’s ratios were 0.40 and 0.30 respectively (Table 5.5).

Based on these uniaxial strength values, the siltstones and sandstones fall into the ‘moderately strong’ category as suggested by IAEG (c.f. Table 5.10). Modulus ratio was evaluated from the deformation modulus and the UCS; average values for siltstone and sandstone were 96 and 234

133 respectively. Therefore the Patonga Claystone can be classified as having a low modulus ratio (Farmer, 1983).

Permeability testing was carried out during the investigation work for the Gosford – Kincumber Tunnels using packer test procedures (Golder Moss, 1974). The test data, reported in permeability units of metres per second (m/sec), were obtained from sections with various degrees of weathering, ranging from fresh to slightly weathered to highly weathered rock. Permeability test results from that investigation ranged from 10-6 to 10-8 m/sec (1.5 to 160 metres per year). The degree of weathering does not seem to play a role in the variation of permeability. McNally (1995) also indicates that the upper layers of the weathered Patonga Claystone have low permeability values, in the range of 10-6 to 10-7 m/s.

Indirect tensile strength determination by the Brazilian method was carried out during investigation work for a new alignment of river water transfer from Mangrove Creek Dam to Wyong by Longworth & McKenzie Pty. Limited (Figure 5.1) on behalf of the Public Works Department of New South Wales in 1986 (Public Works Department, 1986). The indirect tensile strength ranged from 3.4 to 6.0 MPa, with an average of 4.5 MPa. UCS and tensile strength by the Brazilian test were also determined from equivalent- depth samples in this study; the average ratio of UCS to Brazilian strength was 8.8:1.

A major landslide, which cost $3 million to repair after failure (Fell et al., 1987), occurred on the F3 Freeway (Sydney - Newcastle) at Hue Hue Road, outside Wyong (Figure 5.1). A cutting about 600 m long, with a maximum depth of 20 m, was excavated at relatively flat (3:1 235

horizontal to vertical) batter slopes through completely to highly weathered Patonga Claystone (Fell, et al., 1987). Three years after the construction, due to heavy rainfall, the cutting collapsed as a landslide on a low strength- bedding plane.

Rock strength parameters used in the design of the original cutting were found to be different from the back analyzed results after failure. During the original investigation, laboratory tests of shear strength indicated that the rock unit had cohesion (c’) and internal friction angle (Ø’) values as shown in (Table 5.6):

Table 5.6: Shear strength parameters used in F3 Freeway at Hue Hue Road original design (Fell, et al., 1987).

Parameters c’- kPa Ø’- degree Extremely weathered claystone 10 15 Highly weathered claystone, - along bedding planes 10 15 - in other directions 30 23

Back analysis is a process of re-calculation of a slope design from known slope geometry, after such a failure, at a safety factor of one (1) to acquire the geotechnical properties. The results from back analysis are listed in Table 5.7. Note that the design slope was originally designed at safety factor of 1.5. However, the back analysis was calculated at a safety factor value of 1. Another factor that contributed to the slope failure was that highly to completely weathered mudstone/claystone occurred at a greater depth than expected in the original design. The lower cohesion angle and low internal friction angle, together with heavy rain and an ineffective drainage 236

system, made the cut slope fail. This indicates that slope failure can occur in weathered mudstone/claystones of the Patonga Claystone, even at slope angles as low as 6º (Fell, et al., 1987, McNally and Whitehead, 1994).

Table 5.7: Back analysis results (Fell, et al., 1987).

Parameters c’- kPa Ø’- degree On slide plane 0 10 In overlying material 10 15

The remedial works for this slope failure are quite interesting. As a result of the low strength and poor water drainage, free draining rock fill was used to support the slope cut as well as to drain water underneath. Details of the slope stabilization work are shown in Figures 5.3 and 5.4.

Figure 5.3: Slope stabilization for Sydney Newcastle Freeway at Hue Hue Road (Fell et al., 1987).

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Figure 5.4: Remedial work for Sydney Newcastle Freeway at Hue Hue Road.

5.3 Tests Used in the Present Study

Most of samples for the present study were taken from cored drilled holes, sunk for coal exploration in 1997 or earlier. After geological logging and related work had been performed, however, the drilled cores were left in their aluminium core boxes in the core shed. Air slaking and moisture changes may have affected some parts of the cored intervals. The sampling program for the present study started in 1998. The locations of the drill holes and the depths of the samples taken are given in Chapter 1.

Sections of drilled core with good recovery were taken and wrapped in plastic, and then wrapped in paper to avoid breaking up during transportation from core shed to laboratory. Since core had been kept unprotected for some time after completion of the drill hole, cutting to particular sizes and shapes was very difficult because of 238

the brittle nature of the mudstone itself and possibly because of moisture content changes. Sandstone samples were sawn more easily into the sizes and shapes required for geotechnical testing.

Problems occurred in preparing the mudstone samples, because the rocks broke up easily with uptake of water during diamond sawing. Sawing without using water in the cooling system was used to solve this problem. Dust from dry sawing was extracted using a vacuum cleaner.

The cut samples had to be ground to obtain smooth surfaces as required by the test methods. Because of the rocks’ sensitivity to water, grinding was performed using abrasive powder with kerosene. Even using these techniques, few samples could be sawn adequately to size. The core recovery did not provide sufficient material to run every test on samples from the same depth interval. For example, the slake durability and UCS tests each require samples about 15 cm in length. The Brazilian test requires samples about 3 cm in length per test. Some tests, however, such as water absorption, were run on materials from the same depth intervals as those for slake durability testing since these tests can be performed on small irregular lumps of rock material.

The aim of the study was to investigate the slaking characteristics of the Patonga Claystone. Rocks that appeared to be sound, even after long-term storage, were considered to be most suitable for such a study.

Accelerated weathering by repeated compaction and remoulding or ‘shale test’ procedures (Hatcher, 1963, Minty and Smith 1980) was performed on weathered mudstones from 239

the Patonga Claystone by Stephens (1994). The plasticity index of crushed rock differed significantly from that of naturally weathered rock (Stephens, 1994). Ground rock, produced either by mortar and pestle or grinding machine, could not represent of real particle size distribution in the rock specimen (e.g. non-plastic mineral such as quartz could be too finely ground). Therefore the geotechnical properties of soil from this accelerated weathering were not expected to be similar to those of rock in the naturally weathered state. Soil properties of the materials will be referred to where applicable, but these properties are not a main concern in the present study.

Most of the test methods used in the study followed available Standards, such as International Society for Rock Mechanics (ISRM) and American Society for Testing and Materials (ASTM) procedures where appreciable. Some modification of these standards was carried out, however, to suit the condition of the rock samples. These are discussed in detail in the relevant section below.

5.3.1 Specific gravity, density and porosity

Background

Specific gravity, a unitless index, is the ratio of the mass of material to that of an equal volume of water at a specified temperature (Bell, 1992d). The density of a material, expressed in units of gm/cm3, t/m3 or kN/m3, is therefore defined as its mass per unit volume.

The specific gravity of rock materials is usually determined according to the procedure outlined by the ASTM (1990a). Oven dried rock samples are immersed in water 240

until no air bubbles were expelled from the sample. The saturated sample is weighed in air and in water, and the specific gravity calculated from:

Md Gs = sa − MM sw where

Md = mass of dry specimen

Msa = mass of saturated specimen in air

Msw = mass of saturated specimen in water.

The porosity of a material can be defined as ratio of the volume of pore space to the total volume. It is usually expressed as a percentage of the total rock volume.

The porosity and density of a rock material are among the most fundamental properties. Mineral composition and void space influence the density of a rock. If void space increases the density decreases. Term ‘unit weight’, the weight per unit volume (kN/m3), is used instead of density for many engineering purposes.

In the case of regularly shaped rock samples, the volume can be determined by direct measurement of the relevant dimensions. In the case of an irregular rock lump, water displacement has to be used for volume determination.

The volume of irregular rock samples in the present study, and hence the dry unit weight, were calculated from:

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− MM V = sa sw density waterof

M =ρ d d V

Porosity was calculated from:

− MM n = sa d × 100 (%) sa − MM sw where V = volume of specimen

ρd = dry density n = porosity.

Density Results

The standard method for rock density determination (ASTM, 1990a) was found to be impractical for the present study. For volume determination by the standard method, the rock specimen must be left in water until saturated (about 48 hours). Submerging of dispersive and slaking- prone rock samples directly into water was found to cause uncontrolled errors in weighing in the submerged state, due to breaking off of chips or flakes during saturation, and also to clay dispersion, which led in some cases to incorrect submerged weight measurement and hence errors in volume determination.

Several alternatives, such as coating the sample with paint and displacement of uniform sand rather than water, were considered as substitutes for the water submergence 242

procedure. The difficulty of each alternative and the relevant sources of error are discussed as follows.

Aerosol paint coating would be expected to block the infiltration of water into the rock specimen, and hence the rock specimen tested would not be in a saturated condition, even though the specimen size would remain unchanged.

Uniform sand replacement is time consuming and less accurate. The density of the uniform sand has to be calibrated first, then the rock specimen and sand are filled into a mold of known volume. The difference in weight between [mold + uniform sand + sample] and [mold + uniform sand] is then used to calculate the volume of the rock specimen. Errors may occur during filling and shaking of the sand mold, or the uniform sand may be not completely fill the space underneath the rock specimen.

Water displacement, where the sample is placed into a beaker filled with water and the volume of the overflow water is taken as the volume of the sample, was also considered less accurate.

Enclosure of the sample in a ‘geotextile’ or ‘geofabric’ was evaluated as another alternative. Depending on the properties of the geotextile, water can infiltrate through the fabric, but fragments of the rock, even if detached, should not pass through this confining membrane. An attempt was made to test by this method by wrapping an irregular specimen with geotextile and immersing it in water for 48 hours as for the standard method (ASTM, 1990a). Unfortunately the openings in the available geotextile were found to be too large to hold the dispersed clay from the samples under water immersion. It 243

was found that dispersed sediment still fell off through the opening, with only some adhering to the fabric. This characteristic is considered as an uncontrolled source of error. Moreover specimen wrapped with geotextile may be lighter than usual, because air pockets apparently made the specimen float. Errors in weight and volume determination occur, leading to errors in density evaluation.

Fortunately, some core samples could be cut to specific sizes and shapes (Section 5.3), therefore allowing direct measurement of their dimensions to be made and used in volume and density determination. The density results listed in Table 5.8 were determined by this method.

Table 5.8: Unit weight and dry unit weight of rock samples.

Unit weight Dry unit weight Sample Rock type gm/cm3 gm/cm3 137 2.58 2.53 Intercalated 201 2.24 2.23 Sandstone 309 2.32 2.30 Sandstone 313 2.54 2.47 Mudstone 401/1 2.16 2.15 Sandstone 404 2.50 2.48 Sandstone 422 2.36 2.35 Sandstone 507 2.60 2.54 Mudstone 604 2.38 2.36 Sandstone 701 2.60 2.53 Mudstone 702 2.58 2.53 Mudstone 703 2.59 2.54 Mudstone 704 2.58 2.53 Mudstone 705 2.58 2.52 Mudstone 706 2.59 2.54 Mudstone 708 2.45 2.40 Sandstone 812 2.42 2.40 Sandstone 815 2.56 2.52 sandstone

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From Table 5.8, the mudstone samples tested seem to have a greater bulk density than the sandstone samples. The average density of the mudstones is 2.59 gm/cm3 (10 samples), compared to 2.38 gm/cm3 for the sandstones (9 samples). In general sandstone tends to have a higher unit weight than mudstone or claystone (Lama and Vutukuri, 1978). In the Patonga Claystone, the greater density of the mudstone is probably caused by the hematite content, together with the well-compacted nature of the clay minerals. The sandstone also has bigger and more open pore spaces, leading to a lower dry density.

In determination of bulk density, without porosity and water absorption determination, coating of the samples with paint is considered to give a reasonable result. The oven- dried sample is weighed first, then coated with paint and weighed again. The coated specimen is immersed in water to determine the weight in water and hence the volume, and then weighed in air to determine the mass.

Not much difference was found between bulk density and dry density. This is because the samples had been dried out before the test commenced.

Porosity

The porosity of the rock specimens was evaluated as a potential basic property controlling the slaking behaviour of the mudrock materials. Some experiments were carried out to determine the porosity of selected rock samples. The weights of saturated rock specimens in air and in water, and the oven-dried weight were used in porosity calculations as listed in Section 5.3.1. It was found that not only the primary porosity is measured. As a result of 245

rock fracturing during water immersion, secondary porosity (fractures in this case) is also developed. The secondary pore also hold water, leading to higher porosity values than usual. The relation of porosity and water absorption (Chapter 4.2), as shown in Figure 5.5, indicates that the water absorption of the mudrocks is about 10% greater than the porosity.

50 y = 0.85x - 5.55 R2 = 0.80 40

20 Absorption 10

0 0 1020304050 Porosity %

Figure 5.5: Higher porosity caused by rock fractures.

5.3.2 Indirect tensile strength

Background

The tensile strength is defined as the maximum stress developed in a given specimen of a material in a tension test performed to rupture under specified conditions (Jumikis, 1979).

Tensile strength can be tested by either direct or indirect methods. Direct tensile testing, e.g. bending of beams, loading in tension and failure of rock by bending, was considered to be difficult in sample preparation and 246

complexity of the equipment. Indirect tensile strength determination, using the method known as the Brazilian test, was performed in this study. In this type of testing, a cylindrical rock specimen, lying on its side, is loaded diametrically with a compression load P, as sketched in Figure 5.6. The tensile strength σt of the rock in this test is computed from:

P2 =σ t πdh where, d = diameter of specimen in mm, h = height of the specimen in mm, and P = maximum load in kN.

Figure 5.6: Indirect (Brazilian) tensile strength test (Jumikis, 1979).

The results are reported in units of kN/mm2 or Mpa. The thickness to diameter ratio of the test specimen used in this study followed the standard method (ASTM, 1990b), which suggests values between 0.2 and 0.75. Rock in its natural state is relatively weak in tension (Jumikis,

1979), and so the tensile strength (σt) of a rock is much less than its compressive strength (σc). The tensile 247

strength of rock is generally about 10% of its compressive strength (Jumikis, 1979).

Results

Brazilian test procedures were performed on selected mudstone and sandstone samples from the Patonga Claystone. The setup for the testing apparatus is shown in Figure 5.7. The indirect tensile strength results obtained are listed in Table 5.9.

Figure 5.7: Indirect Tensile Testing (Brazilian Test).

From Table 5.9, it can be seen that the mudstone samples had a tensile strength that ranged from 2.5 to 7.4 MPa, with an average of 4.5 MPa. For the sandstones the values ranged from 3.3 to 14.0 MPa, with an average of 6.6 MPa. This indicates that sandstones have a higher tensile strength than the mudstones.

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Table 5.9: Brazilian Test results.

Tensile Sample no. Rock type MPa 201 4.6 sandstone 313 3.4 mudstone 404 3.3 sandstone 419 4.2 sandstone 507 7.4 mudstone 604 4.6 sandstone 612 6.7 sandstone 701 2.5 mudstone 702 5.6 mudstone 704 4.0 mudstone 705 3.6 mudstone 706 5.0 mudstone 708 6.6 sandstone 812 8.7 sandstone 815 14.0 sandstone

5.3.3 Uniaxial compressive strength

Background

The uniaxial compressive strength or unconfined compression test can be performed on cylindrical, prism, or cube shaped rock specimens by compressing or loading them to failure. Upon failure, the rock specimen usually fractures by axial, brittle splitting, or fails in shear, depending upon the degree of constraint at the ends of the specimen offered by the platens of the testing machine and the surface quality of the parallel ends of the rock specimen receiving the load (Jumikis, 1979; Franklin, 1989). Relatively short specimens, e.g. length-to-diameter ~1), tend to have end constraint problems leading to unrealistically high strength values (Franklin, 1989). To 249

avoid the end constraint problem, rock cores with height- to-diameter ratios of 2.5 to 3.0 were used in the present study.

Table 5.10: Various UCS strength classification systems (Bell, 1992d).

Geological Society IAEG ISRM Term Mpa (1) Term MPa (1) Term MPa (1) Very weak < 1.25 Very low Under 6 Weak 1.25-5.00 Weak Under 15 Low 6-20 Moderately weak 5.00-12.50 Moderate 20-60 Moderately strong 12.50-50 Moderately strong 15-50 Strong 50-100 Strong 50-120 High 60-200 Very strong 100-200 Very strong 120-230 Very high Over 200 Extremely strong > 200 Extremely strong Over 230 (1) Uniaxial compressive strength in MPa.

Various systems are used to describe rock strength based on UCS parameters (Bell, 1992d). The terms and range of strength values differ from system to system (Table 5.10), and hence any strength term should be used only in conjunction with the name of the relevant classification system.

All of the classification systems separate the rocks into classes from low to high rock strength. The defining terms used are quite similar, but differ in their lower and upper boundaries and the ranges of strength values in the classification. For example, consider a rock specimen having a UCS of 110 MPa. The rock is classified as ‘very strong’ under the Geological Society system, ‘strong’ under the IAEG system or of ‘high strength’ in the ISRM system (Table 5.10).

250

Results

Some core intervals had sufficient recovery for UCS testing to be carried out as well as for testing of slake durability properties.

Loading of the rock sample up to 75% of the expected maximum stress, with regular reading of the axial strain, was also employed in this study to measure the Young’s modulus of the samples. This test was run separately from UCS test, so only four (4) samples were selected for the Young’s modulus test while all 13 available samples were subjected to UCS determination. Tests were performed in the ‘as sampled’ moisture content state.

Figure 5.8: Equipment set up for Young’s modulus determination.

Figure 5.8 shows the setup of a rock sample for Young’s modulus determination. Typical stress/strain plots obtained in this study are shown in Figure 5.9. Young’s modulus was calculated from either the secant or the tangent at a fixed percentage (e.g. 50 or 75%) of the 251

ultimate strength, or on the linear portion of the stress- strain curve (Farmer, 1983; Brady and Brown, 1985). UCS and Young’s modulus values are listed in Table 5.11.

60 404 604

40 137 703

20 Axial Stress

0 0.00 0.20Axial Strain 0.40 0.60

Figure 5.9: Stress – Strain curves of typical rock samples.

Table 5.11: Uniaxial compressive strength and Young’s modulus results.

Sample UCS Young’s modulus Rock type Numbers MPa (E) GPa 137 69.8 7.9 Intercalated 201 69.1 Sandstone 313 39.9 Mudstone 404 > 102 10.0 Sandstone 422 87.9 Sandstone 507 69.1 Mudstone 604 76.6 12.3 Sandstone 702 65.4 Mudstone 703 61.9 7.1 Mudstone 706 72.6 Mudstone 708 81.5 Sandstone 812 70.8 Sandstone 815 > 102 Sandstone

252

Four core samples (137, 404, 604 and 703) were selected for the Young’s modulus test. Sample numbers 404 and 604 were fine to medium grained greenish gray sandstone, number 137 was intercalated red mudstone and fine greenish gray sandstone, and sample 703 was a red brown mudstone. A secant at 50% of the ultimate strength was used for Young’s modulus determination in the present study. From Figure 5.9 and Table 5.11, it can be seen that the sandstone has a higher Young’s modulus value than the mudstone or the intercalated sandstone and mudstone. The sandstone has less compressibility for a given stress than the mudstone, because of the greater grain-to-grain contact of the quartz framework and the lower clay content.

The uniaxial compressive strength of the mudstone ranged from 39.9 to 72.6 MPa, with an average of 63.1 MPa (6 samples). For sandstone the strength ranged from 69.1 to greater than 102 MPa, which was beyond the capacity of the testing machine. The approximate average UCS of the sandstone is 84.3 MPa. Most of the rock samples, excluding sample number 313, are classified as ‘High Strength’ following the ISRM classification system. Rock sample number 313 is classified as ‘Moderate Strength’ under the same system.

The modulus ratio (E/UCS) was also calculated for the 4 samples tested for Young’s modulus. The modulus ratio is an index of stiffness/strength characteristics, used in predicting failure behaviour (McNally and McQueen, 2000). Brittle rock has a high modulus ratio while the ratio is low in plastically deformed rock.

The Patonga Claystone samples used in this study have a modulus ratio of 160 for sandstone (slightly weathered to 253

fresh), 137 for intercalated mudstone and sandstone (moderately to slightly weathered) and 114 for mudstone (moderately weathered). These results are consistent with the results reported by McNally and McQueen (2000) on sandstones of the Sydney Basin, which indicate that weathered sandstones exhibit ratios of 100-200 and unweathered sandstones fall in range of 200-300.

Both sandstone and mudstone rocks fail with brittle fracture (Figure 5.10). Brady and Brown (1985) define brittle fracture as the process of sudden loss of strength occurs across a plane following little or no permanent (plastic) deformation.

0 5 10 15cm 0 5 10 15cm

Figure 5.10: Mode of failure of sandstone sample (left) and mudstone sample (right).

5.3.4 Ultrasonic velocity

Background

Sonic velocity determination (ISRM 1979), a non- destructive test method, was performed on the rock specimens before they were tested for uniaxial compressive strength (UCS). The setup for velocity determination, using both compression or primary (P) waves and shear or 254

secondary (S) waves, is illustrated in Figure 5.11. The receiver can be set at the other end (Figure 5.11a) or at any distance (Figure 5.11b) from the ultrasonic sound transmitter.

Figure 5.11: Position of transmitter and receiver for ultrasonic velocity determination (ISRM, 1979).

In the present study, the receiver was set at the end of rock specimen (Figure 5.11a), to compensate for overall internal defects. The measured travel time was recorded in microseconds (10-6 second). The velocity was calculated from the length of the specimen (transmitter to receiver) divided by the travel time and reported in m/sec.

The dynamic modulus of elasticity and Poisson’s ratio were calculated from this determination by using the following equations (Lama and Vutukuri, 1978, Goodman, 1980, Farmer, 1983):

⎛ − ( V/V43 ) 2 ⎞ Eρ= V2 ⎜ ps ⎟ s ⎜ 2 ⎟ ⎝ − ()V/V1 ps ⎠

− ( V/V5.0 ) 2 =µ ps 2 − ()V/V1 ps

255

where: E = dynamic deformation modulus µ = Poisson’s ratio ρ = material density

Vp = velocity of Primary or Compression Wave

Vs = velocity of Secondary or Shear Wave.

Results

Ultrasonic velocity results, dynamic deformation modulus and Poisson’s ratio values for the samples tested are listed in Table 5.12. Unfortunately, during the second series of ultrasonic velocity determinations, the S-Wave measurement apparatus was not available. Only P-Wave velocity was therefore measured on some of the rock specimens.

The mudstone has a P-wave velocity that ranges from 1470 to 2980 m/s, while the sandstone has a velocity that ranges from 2450 to 3170 m/s. Sound waves appear to travel faster in sandstone because of the grain-to-grain contact of the quartz framework, as suggested by Dobrin and Savit (1988), Telford et al. (1990), Kearey and Brooks (1991).

256

Table 5.12: Primary and Secondary Wave Velocity, Deformation Modulus and Poisson’s Ratio.

Sample Vp m/s Vs m/s E GPa µ Remark No. 137* 2480 mudstone 201 2460 1770 1.4 -0.04 sandstone 309 2450 1600 1.4 0.13 sandstone 313* 1470 mudstone 404 2640 1710 1.7 0.14 sandstone 419 2860 1870 1.9 0.13 sandstone 422 2810 2040 1.9 -0.06 sandstone 426 2460 1530 1.3 0.18 sandstone 507* 1230 mudstone 604 3040 2260 2.1 -0.12 sandstone 702* 2390 mudstone 703* 2980 mudstone 706* 2650 mudstone 708* 2500 sandstone 812* 3170 sandstone 815* 3010 sandstone

Notes: The calculated velocities are round up to the nearest ten. * - tested on Pundit apparatus (Akai, 1997), only P-wave data available.

Some other parameters related to sonic velocity are velocity index, fracture frequency and Rock Quality Designation (RQD) (Goodman, 1980, Farmer, 1983).

The velocity index is defined as the square of the ratio between field and laboratory seismic velocities (i.e. 2 (VF/VL) ) (Goodman, 1980, Farmer, 1983). The field seismic velocity of a rock formation, determined from seismic surveys or down-hole well logs, depends on the porosity, density, frequency of fractures, opening width and filling material of fractures, degree of weathering etc (Dobrin and Savit, 1988, Telford et al., 1990, Kearey and Brooks,

1991). A velocity index of one, i.e. VF = VL, indicates that the in-situ rock has very few fracture (low fracture 257

frequency index) and is a very sound rock (good RQD). The fracture frequency index indicates total number of fractures per unit length (Farmer, 1983), such as 15 fractures per metre. RQD was originally set up for assessing the degree of weathering of a recovered borehole core (Goodman, 1980, Farmer, 1983; Brady and Brown, 1985), and then adapted to outcrop mapping by using scan line techniques. The RQD expresses rock quality as the percentage of summation of core length greater than 0.1 meters to the total length of the cored interval. Relations of these parameters are listed in Table 5.13.

Table 5.13: Relation of RQD, fracture frequency and velocity index (modified from Farmer, 1983).

Fracture Quality Velocity index RQD (%) frequency (per classification (VF/VL)2 metre) Very poor 0-25 >15 0-0.2 Poor 25-50 15-8 0.2-0.4 Fair 50-75 8-5 0.4-0.6 Good 75-90 5-1 0.6-0.8 Excellent 90-100 1 0.8-1.0

From Table 5.13, rock with a velocity index of between 0 and 0.2 would be expected to have greater than 15 fractures per metre. Such a rock formation would be defined as ‘very poor’, with the RQD value, when drilled, expected to be between 0 and 25%. In other words, the in- situ rock would have several fractures, including open fractures and/or fractures with some sort of filling material. ‘Excellent’ rock contains less fractures, and also has closed or unfilled fractures.

258

Seismic surveys of the Patonga Claystone (ECNSW, 1983a and 1983b), have found that the field velocities depend on the weathering status of the rock foundation. Values range from 900 to 1550 m/s in weathered bedrock, from 1900 to 2400 m/s in jointed, moderately weathered bedrock, and above 2400 m/s on slightly weathered to fresh rock.

The average laboratory velocity for the primary wave in the present study is 2670 m/s. This was used for calculation of the velocity index, taking the field velocity as that of slightly weathered to fresh rock at 2400 m/s. The velocity index of the Patonga Claystone is thus around 0.8, suggesting material between ‘good’ and ‘excellent’ in quality.

Note that this field velocity represents the sandstone units of the Patonga Claystone. From the velocity index value, the sandstone units would be expected to have a fracture frequency of between 1 and 5 fractures per meter, or in terms of RQD 75 and 100 cm core recovery per meter length. From visual observation of the core samples during the sampling program, the number of fracture ranges between 1 and 5 to no fracture, per meter. This observation of RQD characteristics suggests 100% core recovery of sandstone in most of the formation.

5.3.5 Point load strength

Background

The point load test (Broch and Franklin, 1972) is a very useful method to indicate rock strength, due to the fact that irregular rock lumps can be used in testing. Since the slaking prone rock samples in this study are 259

difficult to cut into specimens with a given size or height/diameter ratio, the point load test was used as an alternative for strength determination.

The point load test is one of the methods used in determining indirect tensile strength. With core samples, the test can be performed in either a diametral or axial direction. With vertical holes in horizontally bedded core, diametral tests will normally give a set of lower bounding strength values, i.e. strength parallel to the main planes of weakness. Generally, in bedded rock, tests should be carried out in both the weakest and strongest directions (Broch and Franklin, 1972; ISRM, 1972 & 1985; Australian Standard, 1993). The Strength Anisotropy Index

(Ia(50)) is defined as the ratio of corrected strength indices for tests perpendicular and parallel to planes of weakness (Broch and Franklin, 1972; ISRM, 1972 & 1985;

Australian Standard, 1993). This Ia(50) index has a value close to 1 for isotropic rocks and more than 1 in anisotropic rocks.

The different types of point load index test are illustrated in Figure 5.12, with the geometry or limit ratios of the rock samples also being indicated.

Figure 5.12: Type of point load test, with the geometry of the sample: diametral test (left); axial test (middle) and irregular lump test (right) (ISRM, 1972 & 1985). 260

For each test, both the load at failure (P) and the distance (D) between the platens at failure are recorded. The point load strength index (Is) is calculated as the ratio of P/D2, and reported in units of MN/mm2 or MPa.

In the present study, each Is value for a series of tests was calculated. The strength at the median value was selected and then corrected to Is(50), i.e. the point load strength index at a platen spacing of 50 mm, by either graphical methods (Figure 5.13) (Broch and Franklin, 1972; ISRM, 1972 & 1985; Australian Standard, 1993) or by using the following equation (Broch and Franklin, 1972; Australian Standard, 1993):

45.0 ⎛ D ⎞ Is = *Is ⎜ ⎟ )50( ⎝50⎠

where: Is(50) = point load strength index Is = uncorrected point load strength (MPa) D = platen separation (mm).

The above expression implies that a point load strength index tested at a platen separation less than 50 mm will give a lower strength index when the correction is applied. The opposite happens to point load strength test data obtained from samples having a platen separation greater than 50 mm. As illustrated in Figure 5.13, where sample A has a platen separation (D) of 40 mm and Is of 1

Mpa, and sample B a spacing of 60 mm and Is of 1 MPa, samples A and B will have Is(50) strength values of 0.9 and 1.1 MPa respectively when the correction is applied.

A rock strength classification system based on point load strength index has been proposed by Broch and Franklin 261

(1972). This ranges from extremely high strength to extremely low strength as listed in Table 5.14.

Figure 5.13: Correcting chart for Point Load Strength Index (Broch and Franklin, 1972).

262

Table 5.14: Point load strength classification (Broch and Franklin, 1972)

Point Load Strength Terms Index (MPa) Extremely high strength Over 10 Very high strength 3 – 10 High strength 1 – 3 Medium strength 0.3 – 1 Low strength 0.1 – 0.3 Very low strength 0.03 – 0.1 Extremely low strength Less than 0.03

Results

Point load testing was used for two purposes in this study: 1) to determine tensile strength (which can be converted by empirical relationships to uniaxial compressive strength), and 2) to break up the rock samples for the slake durability test. A diametral test could not be performed on most of the rock samples, due to the very low (mostly zero) tensile strength in this direction. Most of the rock samples tested, with some exceptions, also have ‘very low’ to ‘low’ strength in axial tests.

The test results, corrected to Is50, are listed in Table 5.15. Generally, point load strength index is reported as only one decimal place (Broch and Franklin, 1972), but in this study two decimal places were used for comparison purposes.

263

Table 5.15: Results for point load strength index.

Is50 UCS Is50 UCS Sample UCS/Is(50) Sample UCS/Is(50) MPa MPa MPa MPa 130 0.14 311 0.14 131 0.86 312 0.21 132 0.28 313 0.31 39.9 129 133 0.28 409 0.65 134 0.22 414 0.21 135 0.21 501 0.31 136 0.22 502 0.55 137 0.45 69.8 155 506 0.16 138 0.56 508 0.21 139 0.21 512 0.35 140 0.30 513 0.25 141 0.22 605 0.40 142 0.20 606 0.07 143 0.21 608 0.25 144 0.31 609 0.38 145 0.29 613 0.03 146 0.23 615 0.08 203 0.18 702 0.30 65.4 218 211 0.25 703 0.30 61.9 206 212 0.38 704 0.18 213 0.28 705 0.22 214 0.11 706 0.33 72.6 220 215 0.31 708 0.24 81.5 340 216 0.24 815 1.09 > 102 94 217 0.14 820 0.68 310 0.11

Depending on core size, McNally and McQueen, (2000) suggest that the range for the ratio of uniaxial compressive strength to point load strength index varies from 10 to 45 for most rocks. However, from the actual UCS tests indicate a ratio greater than 45 in all the available data set (Table 5.15). The greater ratio of UCS to Is50 in the present study, compared to work done by ECNSW (1983) (Table 5.1) and commented on by McNally and McQueen (2000), is probably due to difference in storage time of the core samples. Strength tests by ECNSW (1983) were performed on freshly drilled samples, while the samples for the present 264

study were tested about three years after drilling. Long- term keeping of the drilled samples, especially the slaking prone ones, can reduce the rock strength. Hair cracks can develop parallel to the bedding planes, and hence reduce the point load strength when tested in the diametral test (Figure 5.12). The point load tester uses only small rock lumps and is only loaded at a conical point, therefore internal defects such as hair cracks have more effect on the rock strength. Uniaxial compressive strength testing use a larger specimen, which is compressed by a plate; internal defects could be compensated under these conditions.

As revealed by the diametral tests for the present study, the rock specimens had no strength along the diameter (in other words along the bedding plane). Only axial test could be performed. Therefore the strength anisotropy index for rock samples used in the present study is effectively infinite.

Point load strength indices for the different rock types are summarized in Table 5.16.

Table 5.16: Point load strength index of mudstone and sandstone samples.

Parameters Mudstone Sandstone Minimum 0.03 0.25 Maximum 0.65 1.09 Average 0.25 0.58 Standard Deviation 0.12 0.32

265

The mudstone in the Patonga Claystone is classified as ‘low strength’, while the sandstone is a ‘medium to high strength’ rock.

Point load strength index determination is ideally limited to rocks with a point load strength index above 1 MPa (UCS above 25 MPa), and Broch and Franklin (1972) suggest using direct uniaxial compressive strength values in low strength rock. As a result of the difficulty in cutting the rock samples in this study to suitable size for UCS determination, point load data were used as an alternative method for strength assessment, except in those cases where the core sample could be sawn for direct UCS determination.

Figure 5.14: Histogram showing point load strength index for the present study.

Most of the point load strength indices occur in the range of 0.26 to 0.34 MPa, as shown in Figure 5.14. The second most common strength index ranges from 0.16 – 0.26 MPa.

266

5.4 Relationships to Mineralogy and Slaking Characteristics

Rock strength in this study has been found to be related to the moisture content of the rock, and also to mineralogy as determined by XRD, particularly the proportion of quartz plus feldspar. Slake durability properties are also related to rock strength.

5.4.1 Moisture Content

Broch and Franklin (1972), Brady and Brown (1985), Franklin (1989), Bell (1992a) and Akai (1997) suggest that the amount of moisture present governs the strength of a rock material. Same rock samples with differences in moisture content exhibit differences in rock strength, i.e. rocks with high moisture content tend to have lower strength than drier rocks. However, the UCS has some degree of correlation to point load strength index. Therefore a relationship between moisture content and point load strength index may exist, and this was determined for the present study. Graphs between point load strength index (Table 5.15) and moisture content (Table 4.2.2) are shown in Figure 5.15a) for mudstone and Figure 5.15b) for sandstone.

A plot of moisture content against Is50 for mudstone (Figure 5.15a) gives a poor, scattered relationship. R2 is low (0.06), which suggests that point load strength index has no particular relation to moisture content for the mudstones used in this study, or possibly that the samples had previously dried out. The broad trend shown by the plot, however, indicates that rocks with high moisture contents have relatively low strength and vice versa. 267

5.0

4.0

3.0

2.0

1.0 a) 2

Moisture content % R = 0.06 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Is50 MPa

3.0

2.0

y = -0.53x + 2.45 2 Moisture content % Moisture content b) R = 0.35 1.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Is50 MPa

Figure 5.15: Relationship between point load strength index

(Is50) and moisture content of a) mudstone and b) sandstone.

A stronger correlation (R2 = 0.35) is seen in the plot of point load strength index against moisture content for the sandstone samples (Figure 5.15b). Moisture content clearly has some relation to the rock strength. This may be because high moisture content, due to a combination of high porosity and/or a high number of fractures, indirectly indicates that the rock strength will be low (Broch and 268

Franklin, 1972, Brady and Brown, 1985, Franklin, 1989 and Bell, 1992a).

5.4.2 Water absorption

The relation between the percentage of water absorption of the rock substance has been worked out by plotting the water absorption (Section 4.1.7.2) against the point load strength index (Is50) values. The results are plotted separately for mudstone and sandstone as shown in Figure 5.16.

30.0 a)

20.0

10.0 Water Absorption %

0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Is50 MPa

5.0 b)

4.0

y = -0.94x + 4.62 2 Water Absorption % R = 0.49

3.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Is50 MPa

Figure 5.16: Water absorption percentage plotted against

Is50 as a) mudstone and b) sandstone. 269

The plot for mudstone shows no correlation between water absorption and the strength property, although the plotted points broadly indicate that rocks with low water absorption will have low strength. This is doubtful, however, because rock with low water absorption, reflecting low porosity and low fracture density, should have higher strength than rock with high porosity and high fracture density.

The plot of point load strength index against water absorption for the mudstones gives a cluster of plotted points, indicating no relation between these two parameters. However, similar data for the sandstones shows a negative correlation between Is50 and water absorption, with an R2 value of 0.49. Figure 5.16b suggests, as might be expected, that rock with low water absorption values will have high strength, while rock with a high water absorption will have low strength. This is probably because water absorption is related to the availability of voids, including porosity and fractures. Sandstones with low proportions of void space are undoubtedly well-cemented materials. The cementation plus the grain-to-grain contact of the framework therefore probably combine to increase the rock strength, as suggested by Farmer (1983).

270

4.0

3.0

2.0

y = 0.04x + 2.28 Moisture content % R2 = 0.32

1.0 0102030 Water absorption %

Figure 5.17: Relationship between moisture content and water absorption of mudstone.

Moisture content (Table 4.2.2) is also plotted against water absorption (Table 4.2.8) for mudstones, as shown in Figure 5.17. The relationship indicates that high water absorption is related to high “as tested” moisture content. From Figure 5.17, it can be concluded that moisture content is a function of porosity, but the water absorption indicates the amount of water that is held by the porosity plus water held on the fracture surfaces.

5.4.3 Mineralogy

Many workers (e.g. Attewell and Farmer, 1982, Farmer, 1983, Brady and Brown, 1985) have suggested that rock strength may be controlled by or related to mineral content. The relative percentages of various minerals for rocks of the present study, evaluated by quantitative XRD analysis (Section 3.7) were plotted against the respective UCS values. Figure 5.18 shows the relationships of total clay content (Figure 5.18a), illite plus mixed layered I/S 271

(Figure 5.18b), quartz (Figure 5.18c) and quartz plus feldspar (Figure 5.18d) contents to uniaxial compressive strength. All of the plots give some degree of correlation between the respective parameters. The best relationship is seen in the plot of quartz plus feldspar against UCS (Figure 5.18d).

60 40 a) b)

50 30

40 20 Illite + I/S R2 = 0.49 R2 = 0.22 Total Clays content 30 10 20 40 60 80 100 120 20 40 60 80 100 120 UCS MPa UCS MPa

50 60 c) d)

40 50

2 2 R = 0.52

R = 0.02 Quartz + Feldspar Quartz content % 30 40 20 40 60 80 100 120 20 40 60 80 100 120 UCS MPa UCS MPa

Figure 5.18: Relationship between key minerals and uniaxial compressive strength.

Figure 5.18a shows that rocks with high total proportions of clay minerals have low rock strength, and Figure 5.18b suggests rocks with high proportion of illite plus mixed layer I/S also have low strength. Of the clay minerals used in the correlations, illite plus mixed layer I/S reveals a better coefficient of determination than the total clay mineral content. This probably indicates that illite and mixed layer I/S promote a greater softening characteristic. The minerals used in plotting Figures 272

5.18a and b are considered as the soft part of the studied rock samples, while those in Figures 5.18c and d are considered as forming rigid framework grains. When plotted against UCS, the difference is indicated by the contrast in the sign of the slope between Figures 5.18a and b and Figures 5.18c and d. Rocks with a high proportion of quartz (Figure 5.18c) and quartz plus feldspar (Figure 5.18d) tend to have high strength values. However, the plot of quartz content against UCS gives a flatter slope and lower R2 value than quartz plus feldspar content. This is because quartz and feldspar form relatively rigid framework particles, and an abundance of the grains may help that framework to resist the applied loads. The rock strength of the Patonga Claystone is thus mainly governed by the quartz plus feldspar content.

Key minerals determined by XRD have also been plotted against water absorption (Figure 5.19) and moisture content (Figure 5.20).

273

30 30 a) R2 = 0.05 b) R2 = 0.17

20 20

10 10

0 Water absorption % 0 Water absorption % 20 30 40 50 30 40 50 60 Quartz content % Quartz + feldspar content

30 30 c) d)

20 20 R2 = 0.12

10 10

R2 = 0.18 Water absorption % Water absorption % 0 0 30 40 50 60 0 10203040 Total clays content % Mixed layer I/S

Figure 5.19: Relationship between key minerals and water absorption percentage.

Quartz content (Figure 5.19a) does not appear to be related to water absorption as well as the quartz plus feldspar proportion (Figure 5.19b) or the total clay content (Figure 5.19c). The best relation between key minerals and water absorption is obtained from the plot of the mixed layer I/S content to water absorption (Figure 5.19c). A difference in slope trends can be seen between Figures 5.19a and b and Figures 5.19c and d. These indicate that the key minerals used in the plots have different effects on water absorption. Quartz and feldspar absorb less water than the clay minerals, and in particular the mixed layer I/S. The correlation between water absorption and mixed layer I/S suggests that the mixed layer I/S absorbs more water than the other minerals during water immersion.

274

5 5 a) R2 = 0.01 b) R2 = 0.15 4 4

3 3

2 2 Moisture content % Moisture content % 1 1 20 30 40 50 20 30 40 50 60 Quartz content % Quartz + feldspar contents %

5 5 2 c) R = 0.05 d) R2 = 0.22 4 4

3 3

2 2 Moisture content % 1 Moisture content % 1 30 40 50 60 0 10203040 Total clays content % Mixed layer I/S %

Figure 5.20: Relationship between key minerals and moisture content.

As with water absorption, quartz and feldspar have different water retention properties, and hence induce different moisture contents, as indicated by the different slope direction from similar plots of the clay minerals against moisture content. Quartz (Figure 5.20a) has a lower coefficient of determination to moisture than quartz plus feldspar (Figure 5.20b). The best coefficient of determination to moisture content is again indicated by the proportion of mixed layer I/S (Figure 5.20d). From the plots, clay minerals, and in particular mixed layer I/S, seem to retain more water in the samples than non-clay minerals.

275

5.4.4 Seismic Velocity

Generally the velocity of sound wave propagation in a rock or earth material is directly related to the density of the material (Farmer, 1983, Dobrin and Savit, 1988, Telford et al., 1990, Kearey and Brooks, 1991). However, a plot of P-wave velocity against rock density, as shown in Figure 5.21, suggests a more doubtful relationship. The 1 relation suggested by the Excel software indicates that the rock samples tend to have high velocity at low density, or that no relationship between these two parameters exists at all in the Patonga Claystone.

3.0

2.5 density gm/cc

2.0 0 1,000 2,000 3,000 4,000 Vp m/s

Figure 5.21: Inverse relation between unit weight and velocity.

The rock density test results for the Patonga Claystone suggest that density is probably related to Fe content rather than to quartz and feldspar content. In other words, rocks with high haematite content have higher density than rocks with only minor or no Fe minerals. The

1 Excel is Trade Mark of Microsoft Corporation 276

velocity and density determinations conducted for the present study suggest that higher density is related to Fe content and has no relation to velocity. The grain-to- grain contact and porosity seem to play a role in wave propagation, rather than the presence of denser grain or matrix minerals.

A more positive relationship has been identified between UCS and velocity. Figure 5.22 shows the plot of UCS against primary wave velocity.

120

80 UCS MPa 40

y = 0.02x + 32.34 R2 = 0.22

0 0 1,000 2,000 3,000 4,000 Vp m/s

Figure 5.22: Relation of UCS and P-wave velocity.

Again, this plot suggests that UCS and velocity are both related to grain contact in these rock samples. Grain contact can transfer load more effectively through the rock (Attewell and Farmer, 1982, Brady and Brown, 1985) and also quickly transmit sound waves (Dobrin and Savit, 1988, Telford et al., 1990). The data confirm that rock with good grain contact has higher rock strength and higher sonic velocity properties.

277

5.4.5 Slake Durability

Seven rock samples provided enough material to test both UCS and slake durability properties. Plots of the UCS (Table 5.11) against the slake durability index (Table 4.2.2) are shown in Figure 5.23.

From the plot of UCS against slake durability (Figure 5.23), a good positive correlation (R2 about 0.6) is indicated for all slake durability test cycles. This suggests that the durability property is related somewhat to the rock strength. It is clear from Figures 5.23a, b and c that rock with a UCS less than 80 MPa tends to deteriorate more rapidly than rock with a UCS greater than 80 MPa, in other words rock with a high UCS value tends to have a high slake durability index. This finding is in agreement with the work of Koncagul and Santi (1999).

278

120 a).

80 UCS MPa 40

y = 5.38x0.58 R2 = 0.65

0 0 20406080100 Id2 %

120 b).

80 UCS MPa 40

y = 27.17x0.23 R2 = 0.62 0 0 20406080100 Id3 %

120 c).

80 UCS MPa 40

y = 49.12x0.10 R2 = 0.60 0 0 20406080100Id5 %

Figure 5.23: Relationship between UCS and (a) 2nd cycle, (b) 3rd cycle and (c) 5th cycle slake durability index. 279

5.5 Keuper Marl

The extensively studied Keuper Marl in Britain has some characteristics in common with the Patonga Claystone, such as an overall red bed facies, and similar geotechnical behaviour, e.g. slaking characteristics (McNally, 1998). The geological background and geotechnical properties of the Keuper Marl are briefly discussed in this section, and a comparison will be made between these rock formations, allowing the extensive studies of the Keuper Marl to aid in explaining the slaking behaviour of the Patonga Claystone.

5.5.1 Geology and Mineralogy of Keuper Marl

The Keuper Marl is a sequence of red-brown mudstones and silty mudstones of Triassic age, with a number of sandstones and abundant siltstone beds. The Keuper Marl crops out as two limbs on either side of the Pennines, a low mountain range in the Midlands of England that extends southwest to the Bristol Channel (Figure 5.24) (Chandler, 1969).

The maximum thickness of the unit (1200-1500 m or 4000-5000 feet) is located in the west of the Pennines in the Shropshire-Cheshire Basin. The thinnest part of the unit (225 m or 750 ft) is found in the east of the Pennines in the Nottingham area.

The depositional conditions that formed the Keuper Marl were complex, and at present are poorly understood. It has been suggested that the sediments accumulated in an arid inland basin, in alkaline saline and supersaline waters. The alternation of fine and coarse-grained material was developed through variations in transport and 280

deposition by wind and water, forming marl, siltstone and sandstone.

Sellwood and Sladen (1981) indicate that the argillaceous beds of the Keuper Marl are locally heterogeneous, and contain sandstones and limestones as well as mudrocks. Sporadic bands of evaporite, including gypsum, rock-salt and celestine, are found intercalated between the marls.

The grain size of the sediment averages less than 64 µm, with the mineralogy containing in excess of 60 percent clay minerals. Davis (1967) suggests that carbonate is the main cementing material, reported to be as much as 30% of the total rock sample.

Figure 5.24: Exposure of the Keuper Marl (Chandler and Davis, 1973). 281

The clay mineral assemblages of the Keuper Marl reflect the hot dry depositional conditions indicated by the overall sedimentary facies. All the clay minerals found in the unit are rich in magnesium and silica. Illite and chlorite are universal, and much of the chlorite (>50%) is of the swelling type. Table 5.17 shows a selection of quantitative mineralogical analyses, obtained by X-ray diffraction. These samples are taken from the M50 Motorway (Worcestershire and Gloucestershire), M5 Motorway (Worcestershire) and Blaby in Leicestershire. As can be seen from the table, all the materials studied have a broadly similar mineralogical composition.

Table 5.17: Keuper Marl - Mineralogical composition of whole material (percent) (Dumbleton, 1967).

Sample Illite Chlorite Sepio Palygor Hematite Quartz Dolomite Calcite lite ksite M15 Motorwy, Worcestershire A 54 32(0.7) 1 8 1 4 B 51 12(0.5) 2 24 1 10 C 49 19(0.6) 2 17 3 10 D 39 35(0.6) 19 1 6 E 28 11(0.9) 41 1 10 1 8 F 31 33(0.9) 11 2 23 G 56 * 2 18 24 Blaby, Leicestershire H 29 15(0.5) 6 2 31 9 8 J 33 8(0.5) 8 1 35 4 11 K 29 18(0.5) 5 2 30 9 7 M50 Motorway (Ross Spur), Worcestershire and Gloucestershire L 54 32(0.6) 1 7 3 4 M 47 39(0.7) t 2 12 N 40 17(0.5) 10 2 15 5 11 Notes 1. t = trace 2. * = chlorite was detected in the clay fraction of this sample 3. proportion of swelling chlorite is given in brackets.

282

The Keuper Marl, in general, is associated with a number of problems in engineering works. These include:

- it resembles rock when first excavated; - it weathers to heavily overconsolidated clays of low plasticity; - it softens to a weak state when it is exposed by excavation, and causes problems under poor drainage conditions.

5.5.2 Geotechnical Properties of the Keuper Marl

Bell and Culshaw (1990) studied the geotechnical properties of the Keuper Marl based on samples taken from drill holes in Nottinghamshire. The test results reveal that the particles are mainly of silt size. Density, rock strength, Young’s modulus and durability increase with depth, but porosity decreases with depth. Rock strength in the unit ranges from moderately weak to moderately strong and durability index ranges from fair to very good.

A study of Keuper Marl geotechnical properties by Dumbleton (in Davis, 1967) found a difference between the percentage of clay minerals as determined by mineralogical analysis and the percentage of clay-size (< 2µ) particles as determined by sedimentation analysis. This difference may be attributed to the presence of a cementing or aggregating agent, causing aggregation of the clay particles into larger, silt size or ‘pseudo-silt’ units. Aggregation or pseudo-silt formation will affect engineering parameters such as Atterberg limits and shear strength compared to sample with more dispersed clay-sized particles.

283

The aggregation ratio, Ar, a parameter proposed by Davis (1967), can be defined as the percentage weight of clay mineral particles as determined by mineralogical analysis to the percentage weight of clay size (< 2µ) particles as determined by standard particle size analysis methods, i.e.

eralminclay% particles Aggregatio A,Ration = r of% particles 2µ<

The aggregation ratio is used to identify the existence of pseudo-silt particles in a rock sample. A ratio of one indicates that the clay-size particles (by sieve analysis) are entirely made up of clay minerals (determined by mineralogical analysis). Soils with clay particles larger than 2µ (pseudo-silt particles) have an aggragation ratio greater than one. Most of the test results performed on Keuper Marl indicate a medium to strong aggregation (Davis, 1967).

The Keuper Marl can be classified as an inactive to normal clay, with activity indices ranging from 0.145 to 1.17 (Davis, 1967). The activity index can be defined as the ratio of plasticity index over weight percentage of clay size particles (Skempton, 1953), i.e. for a given proportion of clay-size material of the soil sample, a clay with a higher PI is more active than a clay with a lower PI.

284

5.5.3 Comparison to the Patonga Claystone

5.5.3.1 Mineralogy

Illite is the dominant mineral in Keuper Marl while quartz is the most abundant mineral in Patonga Claystone. The chlorite content of the Keuper Marl is high (Dumbleton, 1967), with more than half of the chlorite being a swelling chlorite. The chlorite content of the Patonga Claystone is quite low, and consists mainly of a non-swelling type. Instead of having swelling chlorite, the Patonga Claystone contains an expandable clay mineral of randomly interstratified illite-smectite.

The hematite content also differs between these two rock formations. The Keuper Marl has low proportion of hematite while the Patonga Claystone contains slightly more. Clay minerals found in the Keuper Marl but not found in the Patonga Claystone are sepiolite and palygorksite. Some Keuper Marl samples contain large proportions of sepiolite.

5.5.3.2 Engineering properties

Efforts have been made to compare the published engineering or geotechnical properties of the Keuper Marl to those of the Patonga Claystone (Table 5.18). The geotechnical properties of the Patonga Claystone were collected from literature review as well as from the present study.

There is a wide range for some Patonga Claystone properties, e.g. density, liquid limit, etc., depending on 285

the degree of weathering. A higher degree of weathering is usually associated with higher Atterberg limits but lower density and strength. The uniaxial compressive strength and point load strength index for the Patonga Claystone are quoted only from tests on mudstone materials within the rock unit.

The natural moisture contents reported for rocks of the two rock formations are quite different. However, these differences may be due to differences in the humidity and/or weather in the areas concerned.

Table 5.18: Comparison of engineering properties.

Properties Keuper Marl Patonga Claystone UCS (Mpa) 4.6-9.2 Undrained shear strength (kN/m2) 250-1450

Point load strength (Mpa) 0.2-0.5 Slake durability (2nd cycle) 8.1-96.3 Triaxial Natural moisture content (%) 5-35 13-26 Bulk density (g/cm3) 1.36-2.40 2.05-2.21 Dry density (g/cm3) 1.84-2.48 1.29-1.94 Liquid limit (%) 25-60 48-83 Plastic limit (%) 17-33 20-35 Plasticity index 10-35 25-57 Shrinkage limit (%) 10.6 Percent clay size particles 10-50 C.B.R. 0.5-5.0 Aggregation ratio, Ar 2.5-10 Activity 0.145-1.17

Many characteristics of the Patonga Claystone are similar to those of the Keuper Marl, as postulated by McNally and Whitehead (1994). Both formations have an aggregate clay structure; however, variable cementation of these aggregates has not been shown to be present in the Patonga Claystone as it has in the Keuper Marl. 286

Accelerated weathering tests on the Patonga Claystone indicate that the aggregates are better cemented than the surrounding material, being last to break down, although this may not be true for all the aggregate particles.

Mineral species common to both formations are illite, quartz, hematite and mixed layer clays, with swelling and non-swelling chlorite, corrensite, and dolomite/calcite making up the remainder in the Keuper Marl (Davis, 1967). While the composition, proportion and distribution of clay minerals is somewhat different, both formations contain a high percentage of expanding clay minerals, making them susceptible to slaking. This explains the similar weathering nature of both formations.

The Keuper Marl was deposited under arid oxidizing conditions in hypersaline waters (Cripps and Taylor, 1987), while the Patonga Claystone was deposited under oxidizing conditions in a terrestrial or possibly shallow marine environment. The similar clay structures are a product of the oxidizing saline conditions that existed during deposition of both formations. More arid and saline conditions are responsible for the evaporite minerals in the Keuper Marl, while some of the other differences in the mineral assemblages were probably caused by differences between their source rocks. The over-riding factor responsible for the similarities between the Patonga Claystone and the Keuper Marl is the common oxidizing and possibly saline conditions that existed during their deposition.

287

5.6 Concluding Summary

The Pinhole test results reveal that the Patonga Claystone behaves as a non-dispersive material in sea water. Flocculation of the clay minerals in the saline water may be responsible for this non-dispersive behaviour of the Patonga Claystone in coastal outcrops and similar settings.

During the fieldwork, it was also observed that the Patonga Claystone exposed below the groundwater table, i.e. rock material that is always in a saturated condition, remains unchanged or has less slaking behaviour than other exposed beds. The rock material exposed above the water table, i.e. where the moisture conditions change frequently with time, however, shows evidence of severe breakdown. This finding supports the theory, used in explaining the behaviour of rock material subject to alternate cycles of wetting and drying, where the oven dried samples seem to suffer more severe slaking than naturally dried rock samples.

The moisture condition of the samples used in the study has changed, i.e. moved to a naturally dried condition, since the completion of the original exploration drill holes. When these rock samples are subjected to moisture change during preparation by wet sawing, the rock samples break up easily making cutting more difficult. Dry sawing with an aid of a vacuum cleaner can be used in sample preparation for this kind of rock material. Kerosene, rather than water, should be used, together with corundum as a grinding agent, to smooth the cut surfaces (Section 5.3).

288

Since the rock samples used in the present study are slaking prone, this makes the determination of geotechnical properties related to water uptake more difficult. The rock samples could not be directly immersed in water, i.e. for unit weight and water absorption determination. Several methods were tried to overcome this limitation (Section 5.3.1). Use can be made of geotextile enclosure, allowing saturation conditions to be achieved, but some colloidal material escaped from the rock and passed through the geotextile membrane. The use of paint coating gives a far less reliable result, because saturation conditions could not be achieved. The jar slake test (Section 4.1.8.1), moreover, could be used for water absorption determination.

The high hematite content, together with the well- compacted nature of the clay minerals, makes the mudstone density (2.59 gm/cm3 on average) greater than the sandstone density (2.38 gm/cm3 on average). The sandstones tend to have bigger and more open pore spaces (Section 5.3.1).

The relationship of porosity and water absorption (Figure 5.5, Section 5.3.1) indicates the existence of secondary pore spaces or fracture surfaces to hold water, such that the water absorption values tend to be greater than the porosity.

Brazilian tests (Section 5.3.2) indicate that the Patonga Claystone rock samples have average tensile strengths of 4.5 and 6.6 MPa for mudstone and sandstone respectively.

Based on the uniaxial compressive strength, the rock samples used in the present study can be classified as 289

‘Moderate to High Strength’ (Table 5.11). Young’s modulus was found to be between 114 and 160 in the rock samples (Table 5.11).

Evaluation of the velocity index for the tested samples in comparison to field determinations of seismic velocity suggest a consistency between field conditions, in terms of fracture frequency and rock quality designation of the sandstones, to the actual cored sample materials (Section 5.3.4).

The mudstone in Patonga Claystone, as tested by Point Load Strength Index, can be classified as a ‘Low Strength’ rock (Table 5.16). By the same classification, the sandstone is classified as ‘Medium Strength’.

A relationship between point load strength index and moisture content was found to exist with some degree of reliability. Sandstone (Figure 5.15b) shows a better relation of point load strength to moisture content than mudstone (Figure 5.15a). Air slaking and the naturally dried conditions of the samples are probably responsible for the reduction of point load strength in the mudstones, while moisture change appears to have had less effect on sandstone strength.

Water absorption, in particular for the sandstones, shows a good correlation with point load strength index

(Is50) (Section 5.4.2, Figure 5.16b). For mudstone, air slaking probably reduces the point load strength, especially parallel to the bedding plane (Section 5.4.2, Figure 5.16a). This phenomenon is confirmed by the test results performed on freshly drilled core samples compared to tests on samples carried out 3 years after drilling. 290

A series of correlations between different mineral proportions and rock strength was identified. Quartz and feldspar gave a better coefficient of determination than quartz itself (Section 5.4.3, Figure 5.18), since both combine to form the rigid structural framework of the rock materials. The grain-to-grain contacts between these materials resist the applied load, and therefore high rock strength occurred in samples containing high proportions of quartz plus feldspar.

The seismic velocity of the primary wave suggests a broadly inverse relation to unit weight, i.e. high velocity at low density (Figure 5.21, Section 5.4.4). This is probably due to the Fe content, especially in the mudstones, leading to high density but having no relation to velocity. Grain-to-grain contact, especially in the sandstones, plays a more significant role in wave propagation.

However, the primary wave velocity suggests a direct relation to the uniaxial compressive strength, i.e. high wave velocity high rock strength (Figure 5.22, Section 5.4.4). This also confirms the effect of grain-to-grain contact on wave propagation, as well as on load resistance. Rock material with good grain-to-grain contact, e.g. sandstone, allows seismic waves to travel faster and also to have higher rock strength.

Although only a small number of samples have been tested by both uniaxial compressive strength (UCS) and slake durability, UCS also appears to be related to the slake durability index (Section 5.4.5). Therefore it can be concluded, at this stage, that the grain-to-grain contact associated with quartz and feldspar leads to the 291

high UCS values which in turn leads to high slake durability index values of the rock samples tested in the present study. In other words, the proportion of quartz plus feldspar is a major factor controlling the slake durability of the Patonga Claystone.

The relationships of the other factors such as mineralogy and chemical composition to slake durability will be discussed in the next chapter. CHAPTER 6

RESULTS OF THE STUDY

6.1 Introduction

As indicated in Chapters 4.1 and 4.2, the slake durability test was selected as the principal index test for slaking of the Patonga Claystone in this study. Other tests and analyses, such as X-ray diffraction (XRD), X-ray fluorescence (XRF), loss on ignition (LOI), moisture content, water adsorption and water absorption, were also carried out and used in the overall comparative study. The results of these investigations were then evaluated against the slake durability data. Linear regression analysis, using Excel, was performed on the data sets to define any relationships and obtain the relevant coefficient of determinations (R2).

The results of these evaluations are discussed in this Chapter, including the mineral content evaluated by Siroquant, the chemical composition by XRF and the various physical properties, for the different rock types involved. A discussion of the significance of these results, and of the relevant correlations between them, is given in Chapter 7.

293

6.2 Relation of Rock Mineralogy to Slake Durability

The results of XRD analysis, in conjunction with Siroquant processing (Chapter 3), have allowed quantitative percentage data on the minerals present to be related to the wetting and drying behaviour of the rock samples as shown by the slake durability data (Chapter 4.2). The percentage of each mineral as determined by Siroquant (Table 3.12) was plotted against the slake durability index (2nd, 3rd and 5th cycle) (Table 4.2.2) to evaluate the relationships between these two parameters. The ASTM (1992), recommends that slake durability index from the second test cycle (Id2) be reported as standard value for comparative purposes. However, a total of five (5) cycles of wetting and drying through the slake durability test have been used for this study, to observe more fully the slaking behavior of the Patonga Claystone materials. The second, third and fifth slake durability cycle results were therefore used in the data evaluation and analysis. The second cycle was chosen because this is the standard value for general comparison, the third cycle was selected as representing moderate slaking conditions and the fifth cycle was taken as a worst-case condition for evaluation purposes.

The coefficient of determinations from statistical analysis of slake durability index against the principal mineral percentages evaluated from Siroquant are listed in Table 6.1.

294

Table 6.1: Coefficient of determinations between key mineral percentages and slake durability results.

R2 Variable Id2 Id3 Id5 Kaolinite 0.02 0.03 0.06 Illite 0.02 0.02 0.04 Mixed layer clays 0.16 0.24 0.27 Quartz 0.10 0.14 0.16 Quartz + feldspar 0.23 0.32 0.37 Total clay minerals 0.17 0.23 0.25

The results are somewhat scattered, with low coefficient of determinations partly reflecting error ranges in both sets of determinations. The highest coefficient of determinations were found from the relationship between slake durability and quartz plus feldspar, with R2 values of 0.23, 0.32 and 0.37 for the 2nd, 3rd and 5th slake cycles respectively. Plots of the mineral percentages against slake durability index are shown in Figures 6.1 to 6.6 and discussed more fully below.

6.2.1 Kaolinite and slake durability

A plot showing the percentage of kaolinite evaluated from Siroquant (Table 3.12) against the slake durability indices (Table 4.2.2) is shown in Figure 6.1. Although a slight positive correlation is suggested, implying that rocks with a high percentage of kaolinite tend to have a high slake durability index, the R2 values for the 2nd, 3rd and 5th slake durability cycles against kaolinite are only 0.02, 0.03 and 0.06 respectively (Table 6.1 and Figure 6.1). From the graph, the few samples containing more than 20% kaolinite tend to have high durability values. Samples with kaolinite contents less than 20%, however, may have 295

either a high or a low durability index, and no particular trend is apparent.

Overall, it is concluded that the total kaolinite content of the Patonga Claystone, especially if less than 20%, has no particular relationship to the slake durability index.

296

30 R2 = 0.02 Id2

% Kaolinite - SiQ 0 0 20406080100 Id2 %

30 Id3 R2 = 0.03

10 % Kaolinite - SiQ 0 0 20406080100 Id3 %

30 Id5 R2 = 0.06

10 % Kaolinite - SiQ 0

0 20406080100Id5 %

Figure 6.1: Plots of kaolinite percentage against slake

durability Id2, Id3 and Id5.

297

6.2.2 Illite and slake durability index

The plot of illite content as determined by Siroquant (Table 3.12) against slake durability index (Table 4.2.2), shown in Figure 6.2, has a greater scatter than the kaolinite plot (Figure 6.1). Low coefficient of determinations are apparent for this relationship, with R2 values for the 2nd, 3rd and 5th cycles of 0.02, 0.02 and 0.04 respectively (Table 6.1 and Figure 6.2). A very slight negative slope is possibly developed in the correlation line, suggesting that illite may assist the slaking process, in other words, rocks with higher percentages of illite tend to be less durable. However, the high scatter and low coefficient of determinations suggest that, overall, the slaking properties of the Patonga Claystone are also unrelated to its illite content.

6.2.3 Mixed layer clay and slake durability index

The plot showing the percentage of mixed-layer or expandable clay minerals as evaluated by Siroquant (Table 3.12) against the slake durability index (Table 4.2.2) is given in Figure 6.3. These show a general negative correlation, especially for the 5th cycle slake durability index. The fifth cycle slake index has an R2 value of 0.27 (Table 6.1 and Figure 6.3) whereas the R2 values for the 2nd and 3rd cycles are 0.16 and 0.24 respectively. The negative slope implies that higher proportions of mixed layer clay minerals in the rock samples are associated with lower slake durability index values. In particular, for the 5th cycle test series, samples with < 20% mixed-layer clay (I/S) tend to have slake durability values above 60%, while those with > 20% I/S tend to have Id5 values below 60%. 298

30 Id2 R2 = 0.02

10 % Illite - SiQ

0 20406080100Id2 %

30 2 Id3 R = 0.02

10 % Illite - SiQ

0 0 20406080100 Id3 %

30 2 Id5 R = 0.04

10 % Illite - SiQ

0 20406080100Id5 %

Figure 6.2: Plot of the illite percentage against slake

durability Id2, Id3 and Id5.

299

40 Id2

R2 = 0.16 % Mixed layer - SiQ 0 0 20406080100 Id2 %

40 Id3

10 R2 = 0.24

% Mixed layer - SiQ 0

0 20406080100Id3 %

40 Id5

R2 = 0.27 % Mixed layer - SiQ 0 0 20406080100 Id5 %

Figure 6.3: Plot of the mixed layer clay mineral content

against slake durability Id2, Id3 and Id5.

300

6.2.4 Quartz and slake durability

The plot of quartz content (Table 3.12) against slake durability index (Table 4.2.2) is shown in Figure 6.4. Although only low coefficient of determinations are 2 involved (R = 0.10, 0.14 and 0.16 for Id2, Id3 and Id5 respectively), the quartz content of the rock samples shows a slight positive correlation with slake durability, supporting the idea that quartz assists the durability of the rock materials. The correlation is best seen with the 5th cycle slake durability results, although the small variation in quartz content (30–50%) and the errors associated with both the quartz and Id determinations combine to produce the overall low R2 value.

6.2.5 Quartz plus feldspar and slake durability

A plot of sum of the quartz and feldspar percentages (Table 3.12) against slake durability index (Table 4.2.2) reveals a similar relationship, but with higher R2 values of 0.23, 0.32 and 0.37 for the 2nd, 3rd, and 5th cycles respectively (Table 6.1 and Figure 6.5). From the graph, it seems that rock samples having a combined quartz and feldspar percentage equal to or greater than 42% tend to be highly durable rock materials.

The positive correlation suggests that the quartz and feldspar act as rigid framework particles, resistant to the slaking process.

301

Id2

R2 = 0.10 Quartz content - SiQ 0 0 20406080100 Id2 %

Id3

R2 = 0.14 Quartz content - SiQ 0

0 20406Id3 % 080100

60 Id5

Quartz content - SiQ R = 0.16 0 0 20406080100 Id5 %

Figure 6.4: Plot of total quartz percentage against slake

durability index (Id2, Id3 and Id5).

302

80 Id

R2 = 0.23 Quartz + Feldspar - SiQ 0

0 20406Id2 % 080100

Id3

Quartz + Feldspar - SiQ R = 0.32 0

0 20406Id3 % 080100

Id5

Quartz + Feldspar - SiQ R = 0.37 0

0 20406Id5 % 080100

Figure 6.5: Plot of quartz plus feldspar against slake

durability index (Id2, Id3 and Id5).

303

6.2.6 Total clay minerals and slake durability

The total proportion of clay minerals, kaolinite, illite and mixed layer I/S, determined from Siroquant (Table 3.12), is plotted against the slake durability index (Table 4.2.2) in Figure 6.6. Although similar plots for kaolinite and illite show little if any significant correlation to the slaking properties, the total clay mineral percentage shows a negative correlation, with R2 values very similar to those obtained for the mixed layer clay or I/S component. Rock samples with total clay contents of less than 50 percent tend to have high durability, regardless of the nature of the clay minerals. The combination of Figures 6.1, 6.2, 6.3 and 6.6 suggests that the expandable, mixed-layer I/S in the Patonga Claystone is the principal mineral responsible for the slaking characteristics of the rock unit. The relationship is more easily seen from the total clay plot, i.e. the inverse proportion of quartz plus feldspar as already discussed in Section 6.2.5, than from those of the individual clay minerals. R2 values are 0.17, 0.23 and 0.25 for 2nd, 3rd, and 5th cycle (Table 6.1) respectively.

304

Id2 65

Total clay - SiQ 35 R2 = 0.17 25 0 20406080100 Id2 %

Id3 65

35 Total clay - SiQ R2 = 0.23 25 0 20406080100 Id3 %

75 Id5 65

35 Total clay - SiQ R2 = 0.25 25 0 20406080100 Id5 %

Figure 6.6: Plot of total clay content against slake

durability index (Id2, Id3 and Id5).

305

6.3 Chemical composition

Chemical composition was determined by X-ray fluorescence spectrometry (XRF) as discussed in Section 3.6.1. From the mineralogical point of view, X-ray diffraction (XRD) was used in conjunction with Siroquant to evaluate the proportion of the various minerals in the rock samples. The XRF and XRD results are listed in Table 3.8 and Table 3.12 respectively. Mineralogy results from XRD were interpreted to infer chemical compositions as shown in Table 3.15, and these chemical compositions were compared to the observed XRF chemistry (Figure 3.28). The comparison showed a high degree of compatibility (Figure 3.28 and Table 3.16).

As well as mineralogy, the chemical composition of the rocks (Table 3.8), analyzed by X-ray fluorescence, was also plotted against the slake durability index (Table 4.2.2). Chemical composition is a more readily determined parameter in many laboratories than quantitative mineralogy. The various components, moreover, can also be determined to a higher degree of precision.

Regression analysis, mostly linear, was performed on the data using Microsoft Excel, with the coefficient of determinations listed in Table 6.2. Only 15 samples, however, were analyzed by XRF for the present study, compared to 61 samples for the XRD and Siroquant evaluations.

306

Table 6.2: Slake durability and XRF results.

R2 Variable Id2 Id3 Id5

SiO2 0.17 0.17 0.20

Al2O3 0.18 0.34 0.40

Fe2O3 0.09 0.11 0.12

K2O 0.16 0.14 0.22

SiO2 + Al2O3 0.13 0.07 0.09

SiO2 + Al2O3 + Fe2O3 0.07 0.00 0.00 Loss on Ignition 0.47 0.60 0.62

The highest R2 values from the plots of chemical composition against slake durability index are those associated with loss on ignition, with R2 values of 0.47, 0.60 and 0.62 for the 2nd, 3rd and 5th slake cycles respectively (Table 6.2). The relationships between different aspects of chemical composition and slake durability index are discussed more fully below.

6.3.1 SiO2 and slake durability

SiO2 is mainly derived from quartz with some portions from clay minerals and feldspar, i.e the total SiO2 determined by XRF analysis is not solely from quartz. The plot of total SiO2 (Table 3.8) against slake durability (Table 4.2.2) in Figure 6.7 does not show a good correlation. The coefficients (R2 values) for the relationships are 0.17, 0.17 and 0.20 for Id2, Id3 and Id5

(Table 6.2) respectively. Rocks with high SiO2 contents tend to resist slaking. For example, the two samples with

>65% SiO2 have high slake durability values. However, rocks with 60–65% SiO2 may show a wide range of slaking behaviour. The low coefficient of determinations for each index value (Id2, Id3, Id5) suggest that chemically determined SiO2 is not a useful indicator of durability for 307

the samples studied. This is probably because of SiO2 is not only derived from quartz (resists slaking) but also derived from clay minerals (assist slaking).

6.3.2 Al2O3 and slake durability

Al2O3 is a major constituent of clay minerals, i.e. a high proportion of Al2O3 implies a high proportion of clay minerals, and therefore possibly a low durability. A negative correlation is shown (Figure 6.8) between total

Al2O3 content (Table 3.8) and slake durability index (Table 4.2.2). Rock samples containing less than about 17 percent

Al2O3 tend to have high durability indices, with one exception, while those with greater than 17 percent Al2O3 may have high or low durability properties. However, probably due to the inhomogeneity of the rock material, the tested results from sample number 801 suggest high slake durability index with low Al2O3.

The durability index for rocks with low Al2O3 percentages does not greatly decrease as the number of test cycles increases. However, the index value decreases significantly with more test cycles for rocks with more than about 17%

Al2O3. This finding (Figure 6.8) confirms the significant correlation between total clay mineral percentages and slake durability index, presumably since the clay minerals are mostly high in Al2O3. As the slaking test proceeds, the clay minerals, especially the mixed-layer I/S, can be expected to swell and promote deterioration. In support of this, the coefficient of determinations (R2 values) derived from the 3rd and 5th wet and dry cycles are significantly higher, with values of 0.34 and 0.40 respectively, compared to the 2nd cycle response where R2 is only 0.18. 308

75 2 Id2 R = 0.17

65 - XRF (%) 2

SiO 60

55 0 20406080100 Id2 %

2 Id3 R = 0.17

65 - XRF (%) 2

SiO 60

0 20406080100Id3 %

75 Id5 R2 = 0.20

65 - XRF (%) 2

SiO 60

55 0 20406080100 Id5 %

Figure 6.7: Plots of SiO2 from XRF analysis against slake

durability index (Id2, Id3, Id5).

309

Id2 - XRF (%) 3 O 2 Al

801 R2 = 0.18 15 0 20406080100 Id2 %

Id3 - XRF (%) 3 O 2 Al

801 R2 = 0.34 15 0 20406080100 Id3 %

Id5 - XRF (%) 3 O 2 Al

801 R2 = 0.40

0 20406080100Id5 %

Figure 6.8: Plots of total Al2O3 content from XRF analysis

against slake durability index (Id2, Id3, Id5).

310

6.3.3 Fe2O3 and slake durability

10 Id2

5 - XRF (%) 3 O 2 Fe

R2 = 0.09

0 0 20406080100 Id2 %

10 Id3

5 - XRF (%) 3 O 2 Fe

R2 = 0.11

0 0 20406080100 Id3 %

10 Id5

5 - XRF (%) 3 O 2 Fe

R2 = 0.12 0

0 20406080100Id5 %

Figure 6.9: Plots of total Fe2O3 content from XRF analysis

against slake durability index (Id2, Id3, Id5).

311

Because the Patonga Claystone is made up mainly of red beds, the total Fe2O3 content is a significant part (4-10%) of the whole-rock chemical composition. It mainly reflects the abundance of hematite in the rock materials.

Evaluation of the relationship between total Fe2O3 (Table 3.8) and slake durability indices (Table 4.2.2), however, shows a slight negative correlation, but with only very low coefficient of determinations (0.09 to 0.12) (Table 6.2 and Figure 6.9). The negative slope of the correlation line suggests that some rocks with low Fe2O3 may be more durable than the others, but the low coefficient of determinations and the wide spread of the data points in Figure 6.9 suggest that no particular correlation at all exists between slake durability and

Fe2O3 content. While the Fe2O3 may affect the overall colour of the various rocks, it appears to be only a pigmenting agent, with no effect on the durability or slaking properties.

6.3.4 K2O and slake durability

Although some of the potassium in the Patonga

Claystone may occur in feldspar fragments, most of the K2O in the samples studied probably occurs in the illite and illite/smectite of the clay minerals. As indicated in

Figure 6.10, samples with a low K2O content (around 2%) tend to have high slake durability indices (Table 3.8 and 4.2.2). These indices, moreover, do not decrease very much as the number of wet-dry cycles increases (i.e. Id5 is similar to Id2). Rocks with higher K2O proportions, however, show a much wider range of durability index values, with significant differences in many cases between the two-cycle and five-cycle results. 312

Id2

3 O - XRF (%) 2 2 K

R2 = 0.16 1 0 20406080100 Id2 %

Id3

3 O - XRF (%) 2

K 2

R2 = 0.13 1

0 20406080100Id3 %

Id5

3 O - XRF (%) 2

K 2

R2 = 0.22 1

0 20406080100Id5 %

Figure 6.10: Plots of total K2O from XRF analysis against

slake durability index (Id2, Id3, Id5).

313

An overall negative correlation is thus developed between total K2O and slake durability index. The trend is most pronounced for the Id5 values. The coefficient of determinations for these relationships, although low, are similar to those for the correlations of I/S and total clay minerals to the slake durability properties (Section 6.2).

6.3.5 SiO2+Al2O3 and slake durability

Silica (SiO2) and alumina (Al2O3) make up most of the chemical elements in the rocks studied (75-85%) (Table 3.8). These oxides are represented by quartz, feldspar and the clay minerals. The remainder of the rocks (Table 3.9) is made up of Fe2O3 (4-9%), K2O (2-3%), MnO (0-0.1%), MgO

(1-2%), CaO (0-1%), Na2O (1-2%), TiO2 (∼1%) and the loss on ignition (H2O + CO2) (4-5%).

With some exceptions (Table 3.8 and 4.2.2), rocks in the sample suite with high total proportions of SiO2 + Al2O3 (> 80%) tend to have high slake durability indices (> 70%) that change only slightly as the number of wet-dry cycles increases. Rocks with < 80% SiO2 + Al2O3 have lower Id values, and a wider spread with increasing exposure to wetting and drying processes.

An overall positive correlation is apparent between

SiO2 + Al2O3 and slake durability (Figure 6.11). However, the range of values for SiO2 + Al2O3 is small (77-85%), and the coefficient of determinations low (0.09-0.13) (Table 6.2). This parameter, as least for the samples in the present study, therefore seems to be of limited value in predicting slake durability behaviour.

314

Id2 - XRF (%)

3 80 O 2 +Al 2 SiO

R2 = 0.13 75 0 20 40 60 80 100 Id2 %

Id3 - XRF (%)

3 80 O 2 +Al 2 SiO

R2 = 0.07 75 0 20 40 60 80 100 Id3 %

85 Id5 - XRF (%)

3 80 O 2 +Al 2 SiO

R2 = 0.09 75 0 20 40 60 80 100 Id5 %

Figure 6.11: Plot of SiO2 and Al2O3 from XRF analysis

against slake durability index (Id2, Id3, Id5).

315

6.3.6 SiO2+Al2O3+Fe2O3 and slake durability

Id2 _ XRF (%) 3

O 85 2 +Fe 3 O 2 +Al 2 R2 = 0.07 SiO 80 0 20406080100 Id2 %

Id3 _ XRF (%) 3

O 85 2 +Fe 3 O 2 +Al 2 R2 = 0.002 SiO 80 0 20406080100 Id3 %

Id5 _ XRF (%) 3 85 O 2 +Fe 3 O 2 +Al 2 2

SiO R = 4E-07 80 0 20406080100 Id5 %

Figure 6.12: Plot of SiO2 + Al2O3 + Fe2O3 from XRF analysis

against slake durability index (Id2, Id3, Id5).

316

Extension of the above relationship to include also

Fe2O3 (Table 3.8 and 4.2.2) provides a plot with almost no correlation to the slake durability data (Figure 6.12).

The rocks studied have total SiO2 + Al2O3 + Fe2O3 percentages of between 85 and 88 %, and may have either low or high durability index.

6.3.7 Loss on Ignition and slake durability

The loss on ignition of the dried rock at 1050° C, determined in conjunction with XRF analysis (Table 3.8), is plotted against slake durability index (Table 4.2.2) in Figure 6.13. Good coefficient of determinations were obtained from this plot. R2 values for the 2nd, 3rd and 5th cycles for the set of LOI determinations associated with the XRF study were 0.48, 0.74 and 0.77 respectively. LOI is thus considered as a significant indicator of the slake durability of the rock samples.

Further work was carried out to extend this aspect of the study by determining LOI values for the entire sample collection. Determinations for each sample were made in duplicate, and the average of the two values were used in the correlation study.

A plot of LOI against slake durability index for the full set of samples is shown in Figure 6.14.

317

6 Id2

4 Loss on ignition (%) R2 = 0.48 3 0 20406080100Id2 %

Id3

4 Loss on ignition (%) R2 = 0.74 3 0 20406080100Id3 %

Id5

4 Loss on ignition (%) R2 = 0.77 3 0 20406080100Id5 %

Figure 6.13: Plot of loss on ignition against slake

durability index (Id2, Id3, Id5) for samples studied by XRF analysis.

318

7.0

Id2

5.0 LOI %

R2 = 0.47 3.0 0 20406080100 Id2 %

7.0

Id3

5.0 LOI %

R2 = 0.60

3.0

0 20406080100Id3 %

7.0

Id5

5.0 LOI %

R2 = 0.62 3.0

0 20406080100Id5 %

Figure 6.14: Plot of LOI for full range of samples against

slake durability index (Id2, Id3, Id5).

319

The plot of slake durability index and all the LOI values gives slightly lower coefficient of determinations, with values of 0.47, 0.60 and 0.62 for the 2nd, 3rd and 5th wet and dry cycles respectively. Both plots have negative slopes, showing that when LOI is low the slake durability index is high. Durable rocks have lower LOI figures.

The loss on ignition of the oven-dried samples at 1050° C represents the loss of mass from each sample due to dehydroxylation of the clay minerals, expulsion of CO2 from any carbonates, and driving off of H2O from any hydroxide components. It also includes loss of sulphur from any pyrite present, and the destruction of any organic matter in the rock samples.

Based on mineralogical data (Section 3.7), the main factor controlling the loss on ignition for the Patonga Claystone is probably dehydroxylation of the clay minerals. Little, if any, carbonate (e.g. siderite), sulphide or hydroxide minerals (e.g. goethite) are indicated in the samples by the XRD investigation (Section 3.4), and organic matter is minimal due to the red-bed nature of the sediment. Although the proportion of weight lost due to dehydroxylation would be expected to vary among the different clay minerals involved (e.g. kaolinite loses around 14% on dehydroxylation, illite only 5% (Eslinger and Pevear, 1988), the LOI value is therefore mainly an expression of the total clay mineral content of the rock samples.

The trends shown by the LOI plots (Figure 6.14) are therefore similar to those shown by the plot of total clay mineral content as shown in Figure 6.6. The higher coefficient of determinations in the LOI plot are probably 320

a reflection of the greater precision associated with the individual determinations, compared to the XRD interpretation process.

6.4 Cation Exchange Capacity

Cation exchange capacity (CEC) properties have been used extensively in evaluating the expansive and dispersive behaviour of earth materials (e.g. Bell and Maud, 1994). The CEC is expressed in milli-equivalents per 100 grams of dried soil, i.e. meq/100 g. Soils with high CEC values may disperse even in pure water (Bell and Maud, 1994) to form colloidal suspensions. This section deals with the relation of CEC and clay minerals and any relation between CEC and slaking behaviour of the studied rock samples.

6.4.1 Relation of Clay Minerals and CEC

The set of samples analyzed by XRF was also subjected to determination of cation exchange capacity (CEC) using the ammonium acetate method (see Section 3.8). The results obtained (Table 3.18) were found to correlate well with the total percentage of clay minerals (R2 = 0.63) in the respective samples (Figure 6.15). Although the different clay minerals undoubtedly also have different individual CEC values, such a correlation suggests that the clays are the main source of exchangeable cations in the samples, and suggests that determination of one parameter can be used to estimate the other in situations where both techniques cannot be applied.

321

CEC meq/100 grams R2 = 0.63 0 35 40 45 50 55 60 65 Total percentage of clay minerals

Figure 6.15: Plot of CEC against total clay minerals.

6.4.2 Dispersion potential

Earth materials (clayey soil) with high CEC and exchangeable sodium percentage (ESP) tend to behave as very dispersive materials. Such clays have a higher concentration of sodium in their pore waters than other soils (Bell and Maud, 1994). By contrast, clays having low CEC and ESP will be non-dispersive. ESP can be expressed in form of:

exchangeable sodium ESP = 100* cation exchange capacity

Exchangeable Na+ was determined by ICP analysis of the extract from the CEC determination. The CEC determination was outlined in Section 3.8. The exchangeable sodium percentage (ESP) was calculated and then plotted against CEC on a dispersion potential graph proposed by Bell and Maud (1994) as shown in Figure 6.16.

322

From the graph proposed by Bell and Maud (1994) (Figure 6.16), earth materials having low ESP and CEC can be categorized as completely non-dispersive while rocks or clays having very high ESP and CEC (>10% ESP and >80 meq/100 grams) are classified as very dispersive. Between these earth materials would be any dispersion potential between non-dispersive to highly dispersive, depending on ESP and CEC. Generally speaking, low ESP and low CEC earth material is classified as non-dispersive while low ESP – high CEC or high ESP – low CEC material can be either non- dispersive or highly dispersive.

Figure 6.16: Dispersion potential of Patonga Claystone samples (based on graph proposed by Bell and Maud, 1994).

The Patonga Claystone samples generally have relatively low CEC values (Table 3.18) but high exchangeable sodium, placing most of the plotted points off scale on Figure 6.16. One of the samples (number 801) is plotted in the ‘Marginal’ area on this figure, the rest of the samples plot in the ‘Dispersive’ or ‘Highly Dispersive’ portions. This is consistent with work done by the NSW 323

Department of Conservation and Land Management (1993), represented by points ‘A’ and ‘B’ in Figure 6.16. From both studies, it can be concluded that the Patonga Claystone has dispersive clay properties.

The ratio of exchangeable sodium (from ICP) to CEC (Table 3.18) of the studied rock samples was plotted against second cycle slake durability index as shown in Figure 6.17. From Figure 6.17, with some exceptions, a low Na/CEC ratio (i.e. low exchangeable Na but high CEC) is correlated with low slake durability index, while a high Na/CEC ratio (i.e. high exchangeable Na but low CEC) correlates with high slake durability index values.

0.6 R2 = 0.30

0.4 Na/CEC 0.2

0 0 20406080100Id2 %

Figure 6.17: Plots of ratio of Na/CEC against 2nd cycle slake durability index,

6.4.3 Cation Exchange Capacity against slake durability

The same set of samples that had been subjected to chemical analysis by XRF (Section 3.6.1) had also been subjected to cation exchange capacity determination (Section 3.8). Three sets of graphs are presented here: a 324

plot of CEC (Figure 6.18); a plot of the ratio of (Na + Ca) to total cation exchange capacity (Figure 6.19); and a plot of the ratio of (Na + Ca + Mg) to total cation exchange capacity (Figure 6.20) against slake durability index 2nd, 3rd and 5th cycle.

Cation Exchange Capacity (CEC) is plotted against the slake durability index from the 2nd, 3rd and 5th test cycles (Figure 6.18). The best relation between these parameters 2 is indicated by the plot of Id5 and CEC value, with an R value of 0.22 (Table 6.3).

Table 6.3: Coefficient of determinations between CEC and slake durability results.

R2 Variables Id2 Id3 Id5 CEC 0.18 0.17 0.22 (Na+Ca)/TEC 0.20 0.05 0.05 (Ca+Na+Mg)/TEC 0.04 0.07 0.03 TEC = Total Exchange Capacity

From this plot, it is seen that CEC is only broadly related to the durability of the rock samples. For example some rock samples with CEC values of about 31 meq/100 grams have slake durability that varies from 33 to 75%, while other rocks with CEC of about 31 meq/100 grams have slake durability indices of 55 to 88%.

325

Id2

20 CEC meq/100 gm

R2 = 0.18 0 0 20406080100 Id2 %

Id3

20 CEC meq/100 gm

R2 = 0.17 0 0 20406080100 Id3 %

40 Id5

20 CEC meq/100 gm

R2 = 0.22 0 0 20406080100 Id5 %

Figure 6.18: Plot of Cation Exchange Capacity against slake

durability index (Id2, Id3, Id5).

326

6.4.4 Relation of exchangeable Na and Ca to slake durability

The ratio of exchangeable [Na+Ca] to TEC is plotted against slake durability index as shown in Figure 6.19. From the graph the slake durability indices vary substantially for similar values of [Na+Ca]/TEC, e.g. rock samples having ratios of 0.75 may have slake durability indices varying from 1 to 58 percent.

The highest value for R2 is derived from the 2nd cycle slake durability test, with a value of 0.20, while the 3rd and 5th slake cycles have R2 values of 0.05 and 0.05 (Table 6.3) respectively.

6.4.5 [Ca+Na+Mg]/TEC against slake durability

Again the plot of [Na+Ca+Mg]/TEC, shown in Figure 6.20, shows no significant relation between these factors, with R2 values of only 0.04. The ratio of [Na+Ca+Mg] to TEC therefore seems to have no correlation to slake durability index. For example, one rock sample with a [Na+Ca+Mg]/TEC value of 0.87 has a 2nd cycle slake durability index of 71.7 percent, while another rock sample has a ratio of 0.97 and an Id2 value of 59.2 percent.

327

1.0

Id2

0.5 Ca+Na/TEC

R2 = 0.20 0.0 0 20406080100 Id2 %

1.0

Id3

0.5 Ca+Na/TEC

R2 = 0.05 0.0 0 20406080100 Id3 %

1.0

Id5

0.5 Ca+Na/TEC

R2 = 0.05 0.0 0 20406080100 Id5 %

Figure 6.19: Plot of [Na+Ca]/TEC against slake durability

index (Id2, Id3, Id5).

328

1.0

Id2

0.9 Ca+Na+Mg / TEC

R2 = 0.04 0.8 0 20406080100 Id2 %

1.0

Id3

0.9 Ca+Na+Mg / TEC

R2 = 0.07 0.8 0 20406080100Id3 %

1.0 Id5

0.9 Ca+Na+Mg / TEC

R2 = 0.03 0.8

0 20406080100Id5 %

Figure 6.20: Plot of [Na+Ca+Mg]/TEC against slake

durability index (Id2, Id3, Id5).

329

6.5 Behaviour of Different Rock Types

In previous sections the results were evaluated regardless of the rock type represented by each individual sample within the Patonga Claystone unit. In this section the rock samples are grouped into mudstone and sandstone, based on their overall grain size, in order to compare more fully the effects of each factor identified in the earlier discussion on the durability of the different rock types.

Table 6.4: Coefficient of determinations between key parameters and slake durability results based on rock types.

R2 Mudstone R2 Sandstone Variables Id2 Id3 Id5 Id2 Id3 Id5 Kaolinite 0.001 0.04 0.04 0.05 0.01 0.009 Mixed layer I/S 0.002 0.0004 0.003 0.09 0.06 0.05 Quartz 0.0005 6E-05 4E-06 0.22 0.24 0.23 Quartz + Feldspar 2E-05 0.003 0.009 0.08 0.08 0.08 Loss on ignition 0.45 0.57 0.51 0.02 0.04 0.05

From Table 6.4, the most significant coefficient of determinations are those derived from plots of slake durability index against loss on ignition and quartz proportion for mudstone and sandstone respectively. The other plots give coefficient of determinations close to zero. Therefore, only loss on ignition and quartz proportion will be discussed here. The remaining parameters are not considered in any detail, due to the low correlations between the parameters used in the analysis.

Plots of the kaolinite, mixed layer clay minerals, quartz and quartz plus feldspar percentages, evaluated from Siroquant, against the slake durability index are shown in 330

Figures 6.21 to 6.24. A plot of LOI against slake durability index is shown in Figure 6.25. Note that, in all of these plots, data for the mudstone samples are shown in the graphs on the left hand side of each figure, whereas data for the sandstone samples are shown on the right hand side. The coefficient of determination (R2) is also displayed on each plot. Attempts have been made to use the same vertical scale for both the mudstone and the sandstone plots as far as possible. However, the slake durability index of sandstone occurs over a narrower range than for the mudstone, and the horizontal scale for slake durability index could not be the same for the sandstone and the mudstone plots.

331

30 30

Id2 Id2

20 20

10 10 %Kaolinite - SiQ % Kaolinite - SiQ R2 = 0.05 R2 = 0.001 0 0 70 80 90 100 0 20406080100 Id2 % Id2 %

30 30

Id3 Id3

20 20

10 10 %Kaolinite - SiQ % Kaolinite - SiQ R2 = 0.04 R2 = 0.01 0 0 020406080100 70 80 90 100 Id % 3 Id3 %

30 30

Id5 Id5

20 20

10 10 %Kaolinite - SiQ % Kaolinite - SiQ 2 R = 0.04 R2 = 0.009 0 0 0 20406080100 Id5 % 70 80Id % 90 100 5

Figure 6.21: Plots showing percentage of kaolinite against slake durability indices for mudstone (left) and sandstone (right).

332

30 30

Id2 Id2

20 20

10 10

% Mixed layer - SiQ 2 2 R = 0.002 % Mixed layer - SiQ R = 0.09 0 0 0 20406080100 70 80 90 100 Id2 % Id2 %

30 30 Id Id3 3

20 20

10 10

2 R = 0.0004 2 % Mixed layer - SiQ R = 0.06 % Mixed layer - SiQ 0 0 70 80 90 100 0 20406080100 Id3 % Id3 %

30 30 Id5 Id5

20 20

10 10

2 2 R = 0.05 % Mixed layer - SiQ % Mixed layer - SiQ R = 0.003 0 0 70 80 90 100 0 20406080100 Id5 % Id5 %

Figure 6.22: Plot showing percentage of mixed layer clay minerals against slake durability indices for mudstone (left) and sandstone (right).

333

60 50 Id 2 Id2

801 40 702

20 % Quartz - SiQ % Quartz - SiQ

R2 = 0.22 R2 = 0.0005 30 0 70 80 90 100 Id2 % 0 20406080100Id2 %

60 50

Id3 Id3

40 801 702

20 % Quartz - SiQ % Quartz - SiQ R2 = 6E-05 R2 = 0.24 0 30 0 20406080100Id % 3 70 80Id3 % 90 100

60 50

Id5 Id5

40 801 702 40

20 % Quartz - SiQ % Quartz - SiQ % Quartz 2 R = 4E-06 R2 = 0.23 0 30 0 20406080100 Id5 % 70 80 90 100 Id5 %

Figure 6.23: Plots showing percentage of quartz against slake durability indices for mudstone (left) and sandstone (right).

334

60 60 Id Id2 2

40 50

2 2 % (Qtz+Feld) - SiQ R = 0.08

R = 2E-05 % (Qtz+Feld) - SiQ 20 40 70 80 90 100 0 20406080100Id2 % Id2 %

60 60 Id 3 Id3

40 50

2 2

% (Qtz+Feld) - SiQ R = 0.003 R = 0.08 % (Qtz+Feld) - SiQ - % (Qtz+Feld) 20 40 0 20406080100 Id3 % 70 80 90 100 Id3 %

60 60

Id5 Id5

40 50

2 % (Qtz+Feld) - SiQ R = 0.009 2

% (Qtz+Feld) - SiQ - % (Qtz+Feld) R = 0.08 20 40 0 20406080100 Id5 % 70 80 90 100

Id5 %

Figure 6.24: Plots showing percentage of quartz plus feldspar against slake durability indices for mudstone (left) and sandstone (right).

335

7.0 5

Id Id2 2 702

801

5.0 4 % LOI % LOI

R2 = 0.45 R2 = 0.02 3.0 3 0 20406080100 70 80 90 100 Id2 % Id2 %

7.0 5 Id3 Id3 702 801

5.0 4 % LOI % LOI

2 R = 0.57 2 R = 0.04 3.0 3 0 20406080100 Id3 % 70 80 90 100 Id3 %

7.0 5 Id5 Id5 702

801 5.0 4 % LOI % LOI

R2 = 0.51 R2 = 0.05 3.0 3

0 20406080100Id5 % 70 80Id5 % 90 100

Figure 6.25: Plots showing loss on ignition against slake durability indices for mudstone (left) and sandstone (right).

The mudstone samples have narrow range of quartz content (26 to 40 % - Table 3.12 and 3.13), but have a wide range of slake durability index values (Id2 varies from 8.1 to 96.3 % - Table 4.2.2). The plot of these two parameters represents a long, narrow horizontal pattern (Figure 6.23a) 336

2 with a low coefficient of determination; R for Id2, Id3 and

Id5 are 0.0005, 0.0001 and 0.000004 (Table 6.4) respectively.

The opposite applies in the plots for the sandstones. The graph (Figure 6.23) shows a long narrow vertical pattern, i.e. a narrow range of slake durability index values with a wide range of quartz contents. Most of the

Id2 values for sandstone are around 97%, with the exception of samples 702 and 801 (91.8 and 85.1% respectively), while the quartz content varies from 32 to 42%. The R2 values for Id2, Id3 and Id5 are 0.22, 0.24 and 0.23 (Table 6.4) respectively.

Unlike the other mineralogical data, loss on ignition shows a well-defined correlation to the slake durability 2 index values (R = 0.45, 0.57 and 0.51 for Id2, Id3 and Id5 respectively). The plot of the data (Figure 6.25) shows a steady decrease in slake durability as the LOI increases from around 4.5 to around 5.5 or 6%.

The sandstone samples all have LOI values of between 4 and 5%, similar to those of the mudstone samples with high slake durability indices. With the exception of two samples, the sandstones all have high slake durability index values. The two sandstones with lower durability indices (sample numbers 702 and 801) both have LOI values between moderate to highest values of the sandstones’ LOI (4.5 to 5%). Their slake durability values drop to as low as 75% (Id5), and as such overlap with the values for mudstones having similar LOI properties.

LOI represents mainly dehydration of the clay minerals, and thee total clay minerals content is 337

essentially inversely proportional to the quartz plus feldspar content in the present study. The proportion of quartz plus feldspar indicates some degree of relationship with slake durability index (Table 6.1 and Figure 6.5). From these points, conclusion can be made that LOI (in other words total clay content) is related to slake durability index as revealed by Tables 6.1 and 6.4 and Figures 6.6, 6.13, 6.14 and 6.25. However, the plots of the individual minerals show less significant correlations with slake durability index. This is possibly due to the precision (error range) of quantitative XRD evaluation by Siroquant, especially for minor constituent minerals like the clay minerals.

It is thus concluded that LOI provides a useful predictor of slake durability index.

6.6 Fracture and durability

A preliminary scanning electron microscope (SEM) study was carried out in an attempt to determine the clay mineral structure of the rock materials, and to compare the textural features of samples with different durability or other engineering properties. Because clear images could not be obtained of the clay mineral assemblage, the SEM setup was modified to evaluate the microfracture pattern instead.

Samples 310 and 504, having very low and very high slake durability indices, were studied under the scanning microscope, with typical images shown in Figures 6.26 and 6.27. These images show quartz grains embedded in a groundmass of clay minerals. The labels indicate the 338

figure number (0061), voltage setting (20KV), enlargement factor (x 1,500), graphic scale (10µm) and working distance (WD39).

Q Q

F Q

Figure 6.26: Scanning electron micrograph of a low durability rock sample (Sample 310) (Q = Quartz, F = Feldspar).

Figure 6.27: Scanning electron micrograph of a high durability rock sample (Sample 504) (Q = Quartz, F = Feldspar).

Figure 6.26 depicts the microfracture pattern occurring in a low durability rock sample (Sample 310). This rock sample resisted only one cycle in its slake durability test, and has an Id1 value of 3.3%. The sample 339

has porosity, dry density and water absorption values of 34.45%, 1.12 and 30.80% respectively.

The rock with high durability index (sample number 504) is shown in Figure 6.27. Note the dense nature of the matrix, the lower porosity, and the presence of fewer fractures in this image. This rock sample has Id2, Id3 and

Id5 of 97.8, 97.0 and 95.5% respectively, with porosity, dry density and water absorption values of 10.10%, 2.44 and 4.12% respectively.

These two images suggest the possible role of fractures in determining the geotechnical properties of the rock samples. Rocks with abundant or close-spaced fractures tend to have low density, high porosity and low durability index values.

6.7 Multiple Regression Analysis

As discussed in the previous section, no single parameter evaluated in this study has a single, simple correlation to the slake durability behaviour of the rock samples. The highest R2 value for a single correlation was obtained from a plot of slake durability index against the percentage of water absorption. Another good indicator of slake durability is the loss on ignition value. This may be because more than one parameter actually controls the slaking behavior of the rocks studied.

Multiple regression analysis extends simple linear regression when two or more variables are involved in predicting a relationship (Coskun and Wardlaw, 1995, Crosta, 1998, Hoppe, 1999, Gokceoglu et al., 2000). The 340

2 Analysis ToolPak Add-Ins of the Microsoft Excel Package were therefore used to perform this type of analysis on the data set.

Many researchers have worked on the durability properties of rock substances, leading to several durability classification systems. Many of these classifications are straightforward systems, i.e. use two parameters to define the durability group (e.g. Gamble, 1971; Morgenstern and Eigenbrod, 1974). Dick et al. (1992, 1994) have tried to find the parameters controlling the durability based on the rock type. Their work can be used in predicting slake durability indices by using particular equations. For example (Section 4.1.7):

Id2 = 126.0 - 7.5 * % absorption

The relevant equations may or may not be true for other rocks, with different burial histories, mineralogy and geotechnical properties.

One aim of the present study was to identify one or more equations that can be used to predict the slake durability index of materials from the Patonga Claystone. If such a relation can be found, for example one relating water absorption to slake durability index, instead of doing a time consuming slake durability test only the water absorption percentage needs to be determined to allow rock durability to be predicted.

Unfortunately none of the experiments performed on the Patonga Claystone has identified a simple relationship with

2 Microsoft Excel is Trademark of Microsoft Corporation 341

a high coefficient of determination to the slake durability of the rock samples tested. This leads to the conclusion that there may be more than one factor combining to control the durability properties. From the test results, quartz and feldspar percentage, percent of loss on ignition, and water absorption percentage have stronger correlations to durability than the other factors evaluated. Multiple regression analysis was therefore carried out on these parameters. Two or more parameters, e.g water absorption; proportion of quartz plus feldspar; loss on ignition, were used in the process to find out the relationship with the best coefficient of determination. The results of the multiple regression analysis are listed in Table 6.5.

Table 6.5: Multiple regression analysis of tested results.

Models Parameters R2

1 Id2 = 114.09 – 1.58(Moist) – 3.30(Abs) 0.63

2 Id2 = 76.76 + 0.67(QF) – 3.08(Abs) 0.66

3 Id2 = 179.10 – 2.58(Abs) – 15.47(LOI) 0.68

4 Id2 = 152.79 + 0.29(QF) – 2.58(Abs) – 12.91(LOI) 0.68

5 Id2 = 180.65 + 5.92(Moist) – 2.78(Abs) – 18.55(LOI) 0.68

Notes: (Moist)= remaining moisture content, (Abs) = water absorption, (LOI) = Loss on Ignition (QF) = proportion of quartz plus feldspar evaluated from XRD.

In defining an equation to predict the slaking behaviour of materials in the Patonga Claystone, the simplest and most common tests, such as moisture content and water absorption, were used first in the multiple regression analysis process. These two parameters individually have poor correlations to the slake durability index. Determination of the percentage of quartz plus feldspar is considered as time consuming and requires significant skills in XRD analysis, and so a model 342

involving quartz and feldspar is be less concern in the present context. It is also possibly subject to greater errors than some of the other tests. LOI determination is considered as a common test, because even a simple laboratory should be able to accommodate a furnace capable of heating samples up to 1050° C.

The negative roles of water absorption and loss on ignition suggest that these two parameters promote the slaking process while the positive relation to the proportion of quartz plus feldspar suggests that these framework grains add to the durability behaviour. However, the multiple regression process shows that moisture is a negative factor in model 1 but a positive factor in model 5. Thus it is uncertain whether the role of moisture content in slaking behaviour is to assist or to resist the breaking down process.

All of the models provide similar R2 values (Table 6.6) in their relation to slake durability. Because of their simplicity, the equations of models 3 and 5 are suggested as better models to use for predicting slake durability behaviour in the Patonga Claystone. However, as already discussed when considering the significance of moisture content in slaking behaviour, model 3 is preferred. Another reason for ignoring the moisture content is that the moisture may be affected by the storage and handling conditions involved.

A separate set of Patonga Claystone samples was used to test the modeling and prediction process. These samples were collected from natural exposures along the coastline at Forresters Beach (for location of sampling see Chapter 1) in the Central Coast area. A similar test program to 343

that discussed in the previous chapters was performed on these samples, including XRD, slake durability testing, water adsorption and absorption determinations, and LOI evaluation. Water absorption and LOI were inserted into the above equation to predict the slake durability index for the standard 2nd cycle test as suggested by ASTM (1990c) and discussed in Chapters 4.1 and 4.2. The predicted and observed results are listed in Table 6.6.

Table 6.6: Predicted and observed results for slake durability tests on outcrop samples.

Input Predicted Observed Samples Abs LOI Id2 % Id2 % 1 29.55 4.29 36.6 19.4 2 27.58 4.34 41.0 20.4 3 28.22 4.84 31.4 20.0 5r 16.86 3.45 82.4 77.6 5g 32.57 4.44 26.4 8.6 6 9.14 4.26 89.7 81.4

The tested model indicates higher predicted slake durability index values in all cases than the observed index values (Table 6.6 and Figure 6.28). The differences, however, are not large, considering the range of values shown in the main testing program. The index tends to be underestimated by the model for rocks with low durability characteristics. However, for high durability rock samples, the model tends to give more closely comparable results. This might indicate that factors other than water absorption and loss on ignition also control the slaking behaviour of the Patonga Claystone materials or the outcrop samples and long-stored drill cores also play a role in the 344

difference in water absorption or the slake durability determinations.

100

20 Predicted 2nd slake values 0 0 20406080100 Observed 2nd slake durability index

Figure 6.28: Plots of predicted 2nd slake durability index against observed values.

6.8 Concluding Summary

The mineralogy and the chemical composition of the rocks (Chapter 3) have been subjected in this chapter to a series of regression analyses against the slake durability index data (Chapter 4.2). Some correlations have been found between these parameters, suggesting that prediction of slaking behaviour from other, less time-consuming tests can be made with some degree of confidence.

The proportions of the different minerals indicated by XRD studies (Section 3.7) generally give somewhat scattered points with low coefficient of determinations, when plotted against the slake durability index values. The best correlations were obtained from plots of the mixed layer clay mineral percentage, the total clay mineral percentage, 345

and the proportion of quartz plus feldspar against the slake durability indices (Table 6.1). In most cases, as the slake durability tests proceed, the correlations to the different mineral percentages tend to give better R2 values. For example, in Table 6.1 and Figure 6.3, the plot of mixed layer I/S, the R2 values for the 2nd, 3rd and 5th cycles are 0.16, 0.24 and 0.27 respectively. This suggests that the mineralogical properties of the rock samples have a greater impact on the more severe deterioration that occurs with an increasing number of wetting and drying cycles. It might even be that the 2nd wetting and drying cycle provides an insufficient evaluation of the slaking behaviour of the Patonga Claystone materials.

The plot of kaolinite against slake durability index for the present study suggests that rocks having kaolinite content less than 20% have no particular relationship to the slaking behaviour, while rock samples with kaolinite contents higher than 20% tend to have relatively high durability values.

The highly scattered plot representing the illite proportion against slake durability index, with a low coefficient of determination, suggests that the illite content has no particular relation to the slaking behaviour of the rock samples in the present study. Using the same approach, however, rock samples with high proportions of mixed layer I/S tend to have low slake durability index values. The relationship suggests that slaking behaviour can be roughly classified into slaking and more durable materials, based on whether the proportion of mixed layer I/S is greater or less than 20%. Rocks with mixed layer I/S greater than 20% tend to be less durable than rocks in 346

which mixed layer I/S makes up less than 20% of the total minerals present.

The quartz and quartz plus feldspar proportions in the rocks appear to have some degree of correlation with the slake durability properties. In overall plots of the samples studied, the proportion of quartz plus feldspar reveals a better R2 than the plot of quartz content alone.

The total clay mineral content (essentially inversely proportional to the quartz plus feldspar content) also indicates some correlation to the slake durability index values. As with the mixed layer I/S proportions, rock samples with total clay mineral contents greater than 50% tend to be less durable than rock samples having less than 50% total clay minerals.

The chemical composition evaluated from XRF appears to have a lesser correlation to slake durability index than the various mineral percentages. The best correlation among the plots of chemical composition was found from the plot of Al2O3 against slake durability index. This can be explained in terms of the chemical composition represented by the minerals in the rock samples. Al2O3 is a major constituent of the clay minerals, and the correlation indicated between Al2O3 and slaking behaviour is probably related to the clay mineral content discussed above.

The conclusion that slake durability is related to the total clay mineral content of the rock samples is further supported by the plot of LOI against the slake durability indices (Section 6.3.7). Since there are no carbonate minerals, no pyrite, and no organic matter present in the studied rock samples (Chapter 3), the LOI is thought to be 347

related only to the total clay mineral content. It can be concluded with some degree of confidence (around 90%) that there is a correlation between total clay mineral content, as well as LOI, and slake durability characteristics.

The studied rock samples were further classified into mudstone and sandstone, based on their grain size, to establish any differences in these relationships for the different rock types. From this part of the study (Section 6.5), LOI and quartz proportion appear to have better correlations to rock durability for mudstone and sandstone respectively. The slake durability properties of mudstone are related strongly to LOI (equivalent to total clay mineral content), while sandstone durability seems to depend on the abundance of highly resistant minerals such as quartz and feldspar.

The best defined relationships of this types are those of slake durability index against loss on ignition (Section 6.3) and against water absorption (Chapter 4.2). Multiple regression analysis was carried out on these parameters to construct a model for predicting the slake durability index from other less time-consuming tests. The relevant properties of a series of outcrop samples were then used to check the consistency of the model developed from multiple regression analysis. Although the model seems to predict slightly higher slake durability indices than the observed index values, it appears that the model developed is suitable for predicting rock durability in broad terms. Differences between predicted and observed values from the model suggest that other factors may also control the slaking behaviour of the Patonga Claystone materials.

CHAPTER 7 CONCLUSIONS

The Early Triassic Narrabeen Group has been subdivided differently in three separate areas of the Sydney Basin, namely the North (or Central) Coast district, the Western or Blue Mountains district, and the South Coast or Illawarra district. The Patonga Claystone is a Triassic red bed sequence in the middle part of the Narrabeen Group in the North or Central Coast district. It crops out in the Gosford-Wyong region on the New South Wales Central Coast, an area undergoing significant urban development. The maximum thickness of the unit is 167 metres. The average thickness is 137 metres at the type section in the Windeyer’s Hawkesbury River bore.

The sandstones of the Narrabeen Group consist mainly of quartz grains, rock fragments of various types, and interstitial clay that is both detrital and authigenic in origin. Small amounts of mica, siderite and feldspar are also present, the latter being particularly common in the North Coast district (including the main study area). They were deposited mainly as fluvial deposits, with shales and other lutites accumulating in the associated flood plains and possibly lacustrine depositional systems.

The Patonga Claystone consists primarily of red-brown mudstone, with lesser proportions of siltstone and sandstone. Fresh sandstones and siltstones in the sequence are green-grey in colour, while weathered beds of these units are pale brown in colour. The formation was 349

deposited in a fluvial system similar to the other Narrabeen Group units, with sequences deposited from a combination of more energetic flow and still water being indicated by interbedding of the coarser- and finer-grained sediments.

The burial rate of the mudstones was slow, allowing consumption of the organic matter by bacteria and oxidation by exposure to the atmosphere. This imparted a dominant red-brown colour to the mudstones. During diagenesis and uplift, circulating water reduced some of ferric iron to ferrous iron, imparting a green-grey colour to the more permeable siltstones and sandstones. This process also occurred in mudstones made permeable by bedding planes, joints and desiccation cracks. However, the impermeable mudstone was essentially unaffected by this process.

7.1 Mineralogical and Chemical Characteristics

Several types of analyses have been used to characterise the materials in the Patonga Claystone from a geological point of view. X-ray diffraction was used to evaluate the mineral content of the rock materials both qualitatively and quantitatively, and X-ray fluorescence spectrometry was used to determine the chemical composition. Some cation exchange capacity determinations were also carried out. A range of rock samples were also evaluated in terms of their engineering properties, with particular attention to assessing the potential for degradation on exposure through slake durability tests. Relationships between the different parameters have been plotted, and analysed using relevant software. From these 350

observations and experiments, the following conclusions can be drawn.

1. The colour of the rocks in the Patonga Claystone is controlled by the mineral composition. The common reddish brown colour is related to the proportion of hematite, while the greenish grey colour also developed is related to the chlorite content. Similar colour variation appears in the Bald Hill Claystone of the South Coast district, where it is also related to mineral content. A white colour in rocks of the latter unit is developed in materials low in hematite but rich in kaolinite, while a red colour is found in hematite-rich materials.

2. Quartz is the most abundant constituent of the Patonga Claystone. Some of the quartz appears to occur as very fine particles, since it is almost universally detected in oriented aggregate studies of the clay (<2µm) fraction. Apart from illite, mixed-layer I/S and kaolinite are the major clay mineral constituents, respectively, in the mudstones and sandstones of the Patonga Claystone.

3. Quantitative XRD using the Rietveld-based Siroquant processing system provides data on mineral percentages, including the clay minerals, for the mudstones and sandstones of the Patonga Claystone that are consistent with the chemical composition of the respective rock materials. The method therefore appears to provide a sound basis for mineralogical evaluation, despite the abundance and variable nature of the different types of clay minerals present.

4. The quantitative mineralogy is also consistent with other types of data, such as cation exchange capacity, 351

moisture content etc., that are significant for engineering purposes. Indeed, the data obtained from XRD and Siroquant provide a basis for explaining many of the geotechnical properties of the unit in mineralogical terms.

5. Quantitative mineralogy is also related to the slake durability index, and to other tests of significance to foundation characteristics and slope stability. In particular, slake durability has been shown to depend on the total clay content as determined by XRD of the powdered rock material.

6. The average quartz content of the Patonga Claystone found in this study was about 37%. Mixed layer illite/smectite clay minerals, with an average of 21%, were the second most abundant mineral in the rock unit. The rocks of the formation also contain an average of about 4% hematite. The red brown mudstones in the unit have higher proportions of hematite than the greenish grey sandstones.

7. The relations between the different mineral proportions and rock type indicate a consistency in the average percentage of quartz in both mudstone and sandstone samples. However, the maximum quartz content in the mudstones is higher than in the sandstone samples, indicating possible variations in the sediment source and the action of geological agents (e.g. clay dispersion) during transport and deposition.

8. The chemical weathering of fine-grained feldspar minerals to mixed layer clay (I/S) has possibly given rise to the greater proportions of mixed layer I/S in the mudstones than in the sandstone samples. Because of this, the feldspar content in the mudstones is lower than in the 352

sandstones. The mudstones contain more hematite than the sandstones, but have a lower proportion of chlorite.

9. X-ray fluorescence spectroscopy (XRF) results show that the most abundant chemical component is silica (SiO2), with the second most abundant oxide being that of aluminium

(Al2O3). This is consistent with the high proportion of quartz and clay minerals in the samples studied. Unlike the rocks of the Keuper Marl, a European unit with some similar geotechnical properties, neither calcite nor CaO are present to any significant extent.

7.2 Slaking and Durability

Breakdown of otherwise solid mudstones in the Patonga Claystone can occur within a few days or a few weeks after exposure to the atmosphere. The breakdown probably occurs in response to humidity changes accompanying removal from the buried in-situ state.

The jar slake test and the slake durability test were used in characterizing the breakdown behaviour of a range of rock samples from the Patonga Claystone. In the jar slake test, particularly when applied to the mudstones from the unit, the oven-dried rock samples showed more severe degradation than the air-dried rock samples. Sixty seven percent of the mudstone samples tested were broken down to a pile of flakes or mud after water immersion, giving a low jar slake index value (Ij = 1). In terms of slaking proneness, more than 93% of the mudstones tested would be defined as ‘slaking rocks’ (Ij = 1, 2 and 4) from such simple water immersion studies. None of the mudstone samples were unaffected by the immersion test. By the same 353

definition, the sandstone samples tested from the formation behaved differently, and can be defined as ‘stable rock’ materials.

The jar slake index test can be used as an index test for classifying rock breakdown behaviour on water immersion. Durable rocks remain unchanged (Ij = 6) during the water immersion, while less durable rocks degrade or develop several fractures or chips (Ij value of 1, 2 or 4).

The slake durability test was successfully used as a more comprehensive test to distinguish between high and low durability rocks from the Patonga Claystone unit. The slake durability indices for the materials tested varied from 0 to 100%, indicating potentially unstable (low durability index values) to highly durable (high slake durability index) rocks, and also rocks with a range of characteristics between. For the slake durability test, with some exceptions, sandstones from the sequence displayed higher durability characteristics (average of

96.0% in Id2 slake durability index) than the mudstones. The mudstones showed lower durability properties (average of 73.5% in Id2 slake durability index) based on the same test procedures.

The rock after slake durability testing was found to have mainly Type 2 characteristics, with the material retained on the screen consisting of large and small pieces. The heterogeneity of the fracture pattern, density and mineralogy in the mudstone samples was probably responsible for these characteristics.

Most of the mudrocks in the Patonga Claystone are classified as having a medium to high slake durability. 354

However, most of the material retained in the drum after testing, for most of the samples, is composed of rock fragments with an elongate shape about 5 mm in size (Type 2 and Type 3 rock characteristics after the slake durability tests). The abundance of these broken rock chips leads to relatively high values in the slake durability index. Even though the Patonga Claystone rock materials appear to be relatively high in slake durability, these rock fragments could become smaller in size after loading. This suggests that the Patonga Claystone would be unsuitable for some engineering applications, such as riprap or erosion control, or would have low shear strength in slopes and excavations.

It was found, from water absorption and slake durability tests, that rock samples with high degrees of water absorption tend to have lower slake durability indices. The degree of water absorption, based on study of the slake durability decay index, can therefore probably be used as a preliminary guide in assessment the slake durability properties. It was also found, from a plot of slake durability decay index against the percentage of water absorption, that rock samples with water absorption values of less than 10%, between 10 and 15%, and greater than 15% behave as highly durable, intermediate and less durable materials respectively. The similarity of jar slake index test data to water absorption test results suggest that both of these test methods can be performed at the same time in evaluations of slaking characteristics.

The cation exchange capacity, which is related to the total clay minerals content, is a significant factor that is directly related to rock breakdown. Study of the CEC suggests that the Patonga Claystone tends to be highly 355

dispersive. This dispersive behaviour, together with the abundance of expandable clay minerals, plays a significant role in determining slaking behaviour in the Patonga Claystone materials.

Flocculation of the clay minerals in saline water, however, as suggested by pinhole test results performed in saline water, may be responsible for the contrary non- dispersive behaviour and higher durability of the Patonga Claystone in coastal outcrops and similar settings.

7.3 Effect on other Geotechnical Properties

Although the rock samples used in the present study tend to break up with changes in moisture content, dry sawing with a vacuum cleaner can be successfully used in sample preparation for slaking prone materials. The smooth surface required for some tests was prepared by grinding with corundum powder and kerosene.

Geotextile enclosure could not be successfully used for rock density determination, due to rock disintegration and escape of some colloidal material through the enclosing textile membrane. Because saturation conditions could not be achieved, paint coating on rock materials also gave less reliable density results. However, it was found that the jar slake test could also be used for water absorption determination.

The average values of remaining moisture content on mudstones, sandstones and overall samples are 2.8, 2.0 and 2.6% respectively. These values may indicate that water 356

escapes more easily from the sandstones than mudstones after long-term storage.

Mudstones and sandstones have different water absorption properties. The average values of water absorption in the mudstones and sandstone of the Patonga Claystone are 10.9% and 4.85% respectively. As the water absorption test proceeds, fractures develop more easily in the mudstones and eventually the mudstone becomes disaggregated to flakes or mud. More fractures also mean that more water can be held.

Based on uniaxial compressive strength, the rock samples in the present study can be classified as being of moderate to high strength (average values of 63.1 and 84.3 MPa for mudstones and sandstones respectively). However, based on the point load strength index, the mudstones from the sequence, with an average point load strength index value of 0.25 Mpa, can be classified as low strength rocks while the sandstones (average PLSI value of 0.58 MPa) can be classified as medium strength materials.

Air slaking and the naturally dried conditions of the samples are probably responsible for the reduction of point load strength in the mudstones, especially parallel to the bedding plane. However moisture changes appear to have less effect on sandstone strength than on the point load strength of the mudstones.

Quartz and feldspar also have a better coefficient of determination with rock strength than quartz alone, since quartz and feldspar combine to form the rigid structural (grain to grain) framework of the rock materials and resist the applied load to provide a higher rock strength. This 357

rigid quartz-feldspar framework is also responsible for the higher uniaxial compressive strength and slake durability index of the sandstone samples in the Patonga Claystone.

Grain-to-grain contact, particularly in the sandstone samples, also plays a more significant role in the propagation of sonic waves than the Fe oxide minerals in the mudstone samples. The faster propagation of sonic waves in the sandstones than in the mudstones is therefore confirmed as an indicator of compressive strength, since both depend on the structural framework of the rock material.

7.4 Relation of Mineralogy to Rock Durability

Only relatively low coefficient of determinations were noted in plots of different minerals on an individual basis against the slake durability index values. However, the proportion of mixed layer clay minerals, total clay minerals, and quartz plus feldspar each showed a reasonable degree of correlation in relation to the host rocks’ slake durability properties. In most cases, higher R2 values were obtained as the slake durability tests proceeded (i.e. third and fifth cycle results showed better correlations than first or second cycle results), suggesting that mineralogy has a greater impact on longer-term rock deterioration processes.

Plots of kaolinite and illite against slake durability indices gave low coefficient of determinations, suggesting that these minerals have a relatively insignificant effect on slake durability behaviour. However, materials with a higher proportion (i.e. greater than 20%) of mixed layer 358

I/S in the rock samples tend to have low slake durability indices. This is probably due to the expanding behaviour of the mixed layer I/S in the rock samples. By the same approach, rocks with higher total clay mineral contents (> 50%) tend to be less durable. This is partly because rocks with higher total clay contents inherently have lesser proportions of quartz and feldspar, and hence a less rigid structural framework to resist the disruptive forces associated with the slaking process.

Among the various chemical indicators, the plot of

Al2O3 (a major constituent of the clay minerals) against slake durability index appears to represent the best indicator of durability potential and to have the best coefficient of determination. Again, this relation also reflects the relationship between total clay contents in the rock samples and the slake durability indices.

The loss on ignition at 1050ºC and proportion of quartz, for mudstone and sandstone respectively, appear to have better correlations to rock durability than most other mineralogical or chemical indicators. The slake durability properties of mudstone are related strongly to LOI (which in the absence of organic matter or carbonates reflects the total clay mineral content), while sandstone durability seems to depend on the abundance of highly resistant minerals such as quartz to make up the structural framework. The higher coefficient of determination associated with LOI than with total clay content as determined by XRD probably reflects the greater precision with which the LOI percentage can be determined, and the greater errors inherently associated with the determination of clay mineral percentages, even using Siroquant, based on XRD data. 359

A combination of loss on ignition and water absorption, developed by multiple regression analysis from the core sample results, was used to predict the slake durability index properties for a series of outcrop samples. The (slightly) higher slake durability index derived from this model, compared to the actual determinations, suggest that other factors, apart from loss on ignition and water absorption, may also have some control on the slaking behaviour of the Patonga Claystone materials.

7.5 Slaking Mechanisms

The observed relationships between mineralogy and engineering geological properties suggest that the grain- to-grain contacts in the quartz + feldspar framework governs both the rock strength and the slaking behaviour of the rock samples studied. From relation of water absorption properties to the abundance of mixed-layer clay minerals (with the low proportion of other clays this is close to the total clay content), and the relation of water absorption to slaking behaviour, it is concluded that water absorption plays a significant role in controlling the slake behaviour of the studied rock samples.

The Patonga Claystone rock unit in the Central Coast of New South Wales breaks up mainly in response to changes in moisture content. This breakup can occur only a few days after the rock is exposed to the atmosphere. It also becomes more severe if the rock material is in a completely dried condition before up taking the moisture. The observed relationships between mineralogy and slaking properties suggest that the following mechanisms act to control slaking behaviour in the rocks evaluated for the present study. 360

(1) As observed from the jar slake and water absorption test, oven-dried samples (in other words rocks in a completely dried condition) undergo more severe disintegration than as-received samples (partly moist and partly dried). When the rock materials are in a completely dried state, all of the pores are empty and are filled with only air. This air is trapped and pressurized when the rock materials absorb moisture into their pores through processes such as water immersion. The air pressure exceeds the strength of grain-to-grain contact, consequently reducing the rock’s shear resistance. Mineral grains stay apart and result in a breaking up of the rock substance.

(2) With the reduction in shear resistance when desiccated rock materials become moist as discussed above, the smectite component in the mixed-layer illite-smectite also expands. The expansion of smectite promotes further reduction in shear resistance of the grain-to-grain framework. Reduced shear resistance, together with expansion of the expandable minerals, also leads to breaking up of rock substance.

(3) Rocks with a high proportion of clay minerals and a low proportion of quartz plus feldspar inherently have a lower shear strength, due to the lesser degree of grain-to- grain contact in the rock fabric. The effects of the processes described in (1) and (2) above therefore also have a lower shear resistance to overcome in the more clay- rich rocks, leading to a more rapid breakup from a combination of air pressure and clay swelling processes. CHAPTER 8

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Truitt, M.M. 1983. Soil Mechanics Technology, Prentice-Hall Inc., USA. 381

Tucker, M.E. 2001. Sedimentary Petrology, 3rd Edition. Blackwells, USA.

Tugrul, A. and Zarif, I.H. 1999. Correlation of mineralogical and textural characteristics with engineering properties of selected granitic rocks from Turkey. Engineering Geology, 51, 303-317.

Turner, A.J. and Seago, K.L. 1985. Keuper Marl as a road foundation - predicting its strength. In: Failure in Earthworks, Thomas Telford Ltd., London.

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Vellejo, L. E., Welsh, R. A. Jr., Lovell, C. W., and Robinson, M. K. 1993. The influence of fabric and composition on the durability of Appalachian shales. In: McElroy, C. H. and Lienhart, D. A. (eds.), Rock for Erosion Control, ASTM STP 1177, American Society for Testing and Materials, Philadelphia, USA.

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383

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Addendum

A.1. Engineering Geology Framework

The Narrabeen Group in the northern part of the Sydney Basin contains five formations (Table 2.1), making up a total thickness of 200-800m. These formations include three main lithologies: medium to thickly bedded sandstone (Terrigal Formation and much of the Tuggerah Formation); shale or laminated to thinly interbedded sandstone, siltstone and mudstone (Patonga Claystone, the remainder of the Tuggerah Formation and the Dooralong Shale); and massive sandstone/conglomerate beds (the Munmorah Conglomerate).

The two formations in the middle of the sequence, the Terrigal Formation and the Patonga Claystone, underlie most of the urbanised areas in the Central Coast region. As indicated by McNally (1995), the Terrigal Formation forms relatively steep slopes below cliffs of the overlying Hawkesbury Sandstone. The Patonga Claystone occupies broad swampy valley floors and does not outcrop naturally at all except in sea cliffs. The Tuggerah Formation and Munmorah Conglomerate form undulating low hills elsewhere in the area.

At its type section near Peats Ferry (Table 2.2), the Patonga Claystone is 136 m thick. It remains fairly constant in thickness at least as far north as Wyong, but thins to the northwest as the Tuggerah Formation thickens; by the vicinity of Martindale the Patonga Claystone has lost its separate identity. To the west, around Mangrove Creek Dam (McNally, 1995), the Patonga Claystone may also interfinger with the lower units of the overlying Terrigal Formation.

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The upper boundary of the Patonga Claystone is usually marked by a sharp transition from red-brown mudstone to light- coloured sandstone (Uren, 1975). The unit typically contains about 20% fine sandstone, in beds 0.5 to 5m thick, but in places the proportion of sandstone may increase to about half. The remainder is made up of red-brown, grey-green and grey mudstone, with the red-brown colour dominant towards the top and the other colours being more common with depth.

The fine-grained rocks are mostly siltstones or mudstones in terms of grainsize, with claystone (where all the particles are finer than 4 micron) being relatively rare. The silt- sized particles often form aggregated and cemented clusters of clay flakes, and McNally and Whitehead (1994) have suggested that the variability in cementation may be one reason for the rapid breakdown of the Patonga Claystone on exposure, in a similar way to the Keuper Marl in the United Kingdom.

The colour of the mudstone units varies from predominantly red-brown (chocolate) to green-grey. Fresh sandstone and siltstone units are green-grey in colour, while weathered beds of these units are pale brown. Previous geological studies indicate that the mudstone has a framework of silt-sized quartz and feldspar particles, set in an abundant matrix of illite, irregularly interstratified illite/smectite (I/S), kaolinite and chlorite (Loughnan et al., 1964; Ward, 1971a; Ward, et al., 2003; 2005). Despite the bright red colour which is so characteristic of the Patonga Claystone, the haematite content is only 2-7%.

Mineralogical analyses for the present study show that the sandstones of the Patonga Claystone have on average more quartz and significantly more feldspar than the mudstones. Kaolinite and chlorite are slightly more abundant in the

A - 3 sandstones, but illite and mixed layer I/S, as well as haematite, are more abundant in the mudstones. The mudstones have higher proportions of mixed layer I/S, and also a wider spread of quartz contents than the sandstones (Table 3.14).

A.1.1 Geotechnical Properties of Patonga Claystone

Several geotechnical studies have been carried out on the Patonga Claystone, including work by the Electricity Commission of New South Wales for Deep Creek Power Station (ECNSW 1983a and b), Golder Moss for the Kincumber Outfall Tunnels in 1974, and Fell et al. (1987) for the F3 (Sydney- Newcastle) Freeway at Hue Hue Road, outside Wyong. McNally (1995) has also summarised the engineering geology of the Narrabeen Group in the Gosford-Newcastle Region, including the geomechanical properties of the different rock units.

McNally (1995) reports wide range of test results for the material properties of the Narrabeen Group strata, noting that standard deviations of 20 to 80 % from the mean for groups of apparently similar specimens sometimes indicate a significant degree of geomechanical inhomogeneity. The geotechnical properties of the Patonga Claystone measured by several researchers, including the present study, are listed in Table A.1. The properties of the overlying Terrigal Formation and Hawkesbury Sandstone are given in Table A.2.

The point load strength data from previous studies and the present study are comparable. However some differences do occur in the respective uniaxial compressive strength evaluations. The rock strength (UCS) values obtained in the present study are much higher than in previous studies, especially those of Golder Moss (1974). The difference may be

A - 4 due to changes in moisture content. As suggested by many researchers, variations in moisture content may affect different types of geological substances, with higher rock strength derived from rocks with lower moisture content or in a completely dry condition (e.g. Farmer, 1982; Attewell and Farmer, 1982; Bell, 1992a; Brady and Brown, 1985; Franklin, 1985; Lama and Vutukuri, 1978; McNally, 1995). Work on the geotechnical properties of various rock substances in the Sydney Basin, as summarized by McNally (1995), provides some good examples of this. The ratio of wet and dry UCS in Sydney Basin sandstones and shales varies from 0.30 to 0.70 (Table A.2). This suggests that the strength of dry rock material may be as high as 1.42 to 3.33 times the wet uniaxial compressive strength. In general, however, the moisture content of tested rock samples should be such as to minimize any moisture gain or loss of the sample, as suggested by several standards for testing of rock material (e.g. ASTM, 1990b; ISRM, 1972; ISRM, 1989). The average remained moisture content of the rock specimens used in the present study was 2.6% and ranged from 1.5% to 4.1% (Table 4.2.1), compared to moisture contents of 5.3% derived from natural exposures, ranging from 3.6% to 7.3 (Table 4.2.2).

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Table A.1: Summary of geotechnical properties measured for the Patonga Claystone.

Rock type and ECNSW (1983) Golder Moss Fell, et al. Testing Method Present Study Weathering grade Diametral Axial (1974) (1987) Red-brown mudstone 0.2 – 0.5 0.2 – 0.5 0.03 – 0.65 Sandstone 0.3 – 1.4 0.4 – 1.7 0.25 – 1.09 Point Load Test Green-grey mudstone/siltstone 0.5 0.1 – 0.5 Interbedded siltstone/sandstone 0.6 0.8 Siltstone mudstone claystone UCS - MPa 4.6 – 9.2 15.4 - 24.0 39.9 – 72.6 Elastic Modulus 1.2 - 2.6 Uniaxial Poisson’s ratio 0.18 - 0.42 Compressive Sandstone Strength UCS - MPa 8.6 – 27 32.4 - 62.0 69.1 - >102 Elastic Modulus 3.3 - 8.8 Poisson’s ratio 0.16 - 0.40 Cr = 6.2 MPa Siltstone φr = 32.5 deg. Cr = 6.5 MPa Triaxial Test Interbedded φr = 27 deg. Cr = 4.7 MPa Sandstone φr = 36 deg. C’ = 10 kPa Extremely weathered claystone φ’ = 15 deg. Highly weathered claystone Shear Strength C’ = 10 kPa - along bedding planes φ’ = 15 deg. C’ = 30 kPa - in other directions φ’ = 23 deg. A -5 Sandstone 3.3 – 14.0 MPa Bazilian Test Mudstone 2.5 – 7.4 MPa

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Table A.2: Geomechanical Properties of the Terrigal Formation and Hawkesbury Sandstone (McNally, 1995)

Kangy Angy MWSDB Hawkesbury Mangrove Creek Kincumber Tunnels Boomerang Creek Cutting Tunnels Sandstone Sandstone Shale Sandstone Shale Sandstone Shale Uniaxial Compressive Strength (MPa) Mean 49.9 88.5 41.2 31.1 34.7 32.6 100.0 45.6 30 - 32 Standard Deviation 9.9 21.7 6.4 18.1 6.5 18.1 35.0 16.3 - No of Tests 10 6 12 6 18 18 6 13 - Indirect Tensile Strength (MPa) Mean - - - - 4.5 - 5.8 6.6 2.7 – 4.2 Standard Deviation - - - - 0.8 - 2.4 2.1 - No of Tests - - - - 18 - 6 20 - Elastic Modulus (GPa) Mean 7.8 8.5 5.9 3.0 4.4 3.1 22.8 - 10 - 13 Standard Deviation - - 1.1 2.2 0.7 1.3 4.7 - - No of Tests 2 1 12 6 12 9 6 - - Dry Density (t/m3) Mean 2.24 2.48 - - 2.38 2.49 2.10 - 2.16 – 2.26 Standard Deviation 0.08 0.15 - - 0.11 0.14 1.20 - - No of Tests 10 6 - - 11 16 12 - - Ratios Wet/dry UCS 0.45 0.38 - - 0.55 0.68 - - 0.30 - 0.70

E/UCS 210 303 144 98 126 131 240 - 100 - 300 A -6 ITS/UCS - - - - 0.11 - 0.06 - 0.06 - 0.08

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Only a few tensile strengths, measured by the Brazilian method, have been published for rocks (mainly sandstones) from the upper Narrabeen Group (Table A2). None, apart from the present study, have been published for the Patonga Claystone. The values do not differ much with lithology and are typically in the range 3 to 5 MPa, about 10 to 14% of the compressive strength (McNally, 1995). This ratio is rather high for sedimentary rocks of the Sydney Basin, with 6 to 7% being more common, according to McNally (1995). This is probably because true tensile failure is difficult to achieve in low strength rocks, which tend to shear rather than split cleanly under loading.

Point load strength index may be a good indicator of relative tensile strength in drill core, but it is inadequate for estimating uniaxial compressive strength in these low strength rocks (McNally, 1995). The point load strength of freshly drilled samples of the Patonga Claystone, as measured by ECNSW in 1983 (Table 5.1 and Table A.1), has a degree of anisotropy of approximately one, indicating that this rock has equal strength regardless of the direction of testing. However, in the present study, diametral point load tests could not be performed, due to loss in cohesion along the lamination plane, which developed severe hair cracks in response to the applied load.

Uniaxial compressive strength tests suggest that the mudstones and sandstones have slightly different strength characteristics. The mudstones can be classified as ‘weak to strong’ (Table 5.10). The sandstones have higher UCS values and can be classified as ‘moderately strong to strong’. Although grainsize and quartz content may have much to do with this strength range – mudstone UCS values are typically 40 to 75 MPa – values at the top end are thought to be mainly due to

A - 8 the presence of Fe cement together with the well-compacted nature of the clay minerals in the mudstones, while the sandstones have bigger and more open pore spaces leading to a lower density. This is reflected in dry densities of around 2.59 t/m3 for the strongest mudstone specimens, compared to only 2.38 t/m3 in the stronger sandstones (Table 5.8).

Modulus ratio was evaluated from the deformation modulus and the UCS; average values for siltstone and sandstone in the Patonga Claystone were 96 and 133 respectively (Golder Moss, 1974). Therefore the Patonga Claystone can be classified as having a low modulus ratio (Farmer, 1983). In the present study, modulus ratio was also evaluated, varying from 98 to 160 for the sandstones, around 114 for the mudstones, and falling between these values for the intercalated sandstones/siltstones. Rock specimens with low modulus ratio represent either porous weathered sandstones or uncemented mudstones. By contrast, the occurrence of sandstones with high modulus ratios may indicate secondary silica cementation, despite the high porosity (McNally, 1995).

Sandstones and mudstones in the Patonga Claystone exhibit higher bulk density values than those of the Hawkesbury Sandstone (Pells, 1985a). The higher bulk density of the mudstones and sandstones could be due to a combination of poorer sorting (better grading), a higher proportion of clay matrix filling inter-particle voids, and/or a denser cementing material.

Residual internal friction angle (φr) evaluated by the triaxial test (Table A.1) ranges from 27 to 36 degrees, with the highest values associated with sandstone and the lowest values associated with interbedded siltstone/sandstone. The sandstones have higher residual internal friction angles than

A - 9 the siltstones/mudstones. The higher the internal friction angle the higher the slope angle that can be cut, and therefore the sandstones in the sequence can be cut at higher slope angles while still maintaining slope stability.

Permeability testing has been carried out by Golder Moss (1974) on sections with various degrees of weathering, ranging from fresh to slightly weathered to highly weathered rock. Permeability test results from that investigation ranged from 10-6 to 10-8 m/sec (1.5 to 160 metres per year), indicating impermeable to permeable rock strata. The wide range of test results suggests that the degree of weathering does not seem to play a major role in the variation of permeability.

A suggested weathering classification for the mudstone (described as “shale” by McNally, 1995) units of the Patonga Claystone, based largely on information in Fell et al. (1987) and ECNSW (1983a, b) is as follows:

- Talus and residual soil (RS). Stiff to very stiff fissured silty clay of low to high plasticity, with or without sandstone fragments and a proportion of fine sand. Mottled red-brown, white and yellow-brown colours. Can be augered, and has standard penetration test (SPT) N-values generally of 30-50. Typical depth 2-3 m.

- Extremely weathered (EW) shale saprolite. Similar in colour and strength to the above but retaining vestiges of the parent rock macrofabric, particularly bedding and jointing. SPT values around 50, point load strength zero.

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- Highly weathered (HW) shale saprolite. Very weak rock, indicated by SPT refusal (N>50 blows) and low but measurable point load strength values (>0.1 MPa). Mainly red-brown, but with extensive pale discolouration and mottling adjacent to joints.

- Moderately weathered and slightly weathered (MW and SW) shale saprolite. Red-brown and grey-green with little or no discolouration, grade distinction based largely on apparent point load strength values (MW, 0.1-0.3 MPa; SW, 0.3-0.6 MPa) and average fracture spacing in drill core.

The Patonga Claystone is an inhomogeneous rock substance, as can be seen from the variation in geotechnical test results and the variation in weathering characteristics. Some mudstone layers are distinctly more resistant than others, and some weather tan or off-white rather than red-brown, presumably due to variations in clay mineralogy or clay particle aggregation.

A.1.2 Geotechnical Problems Related to Patonga Claystone

The principal geotechnical problem associated with the Patonga Claystone is that it weathers rapidly on exposure. The Patonga Claystone occupies broad swampy valley floors or hummocky footslopes, and does not outcrop naturally at all except in sea cliffs and man-made exposures (e.g. road and railway cuttings, quarry walls, basement excavations). Although it is the most troublesome of the Narrabeen Group formations from an engineering view point (McNally, 1995), remarkably little has been written on the geology of the Patonga Claystone. The lack of the geological interest is

A - 11 largely due to the poor natural exposure, a consequence of its tendency to weather rapidly.

The Patonga Claystone was first recognized as a difficult formation in the excavation of the Woolworths underground car park at Wyong in about 1970, where small wedge failures caused construction delays and extra costs for rock bolt, shotcrete and mesh support. Moreover, a planned sewer tunnel site was not proceeded with because it was feared that there would be excessive overbreak prior to lining, i.e. increased lining costs due to the need for backfill concrete (G. McNally, personal communication).

Excavated faces in the Patonga Claystone break down rapidly, creating aprons of rock fragments and sometimes causing joint blocks to fall off or become at risk of undercutting. The fragmented rock disintegrates further and rills (shallow, closely spaced gullies typically 1m apart and 0.2m deep) conduct red muddy water flows off the faces, blocking drains. The cut faces become very untidy over months and years, and it is difficult to grow vegetation on the red mudstone surface.

Fossil landslides in weathered Patonga Claystone material have caused major damage in a freeway cutting – the Hue Hue Road landslide in 1986 – and present potential problems in housing subdivisions. Previous to this the F3 Freeway route had been changed to avoid similar landslides on the western side of Wyong Hill. Other, much smaller, landslides have occurred on the Yarramalong Road, on minor roads in the Watagan State Forest, and in coastal cliffs near Forresters Beach. Since the 1980s a great deal of housing development has taken place in areas on the Patonga Claystone south and north of Wyong and at Forresters Beach. The presence of thick

A - 12 talus derived from the Patonga Claystone has increased the cost of the houses because of the need for retaining walls.

The Patonga Claystone underlies most of the low ground near Wyong, an indication of its lack of resistance to weathering. The more durable sandstones of the overlying Terrigal Formation make up the hills. The Patonga Claystone is almost impermeable, forming the floor of the Warnervale Swamp, near Wyong. It is also of poor quality as fill.

All things considered, the Patonga Claystone is the most troublesome unit from a geotechnical perspective on the New South Wales central coast, and hence it is avoided wherever possible for foundations, road cuttings and tunnels. It has, however, been used for brickmaking at Wyong, and similar red mudrocks from the underlying Tuggerah Formation have been used for tile-making at Wyee, north of Wyong.

A.2. Micro-textural Study

A.2.1 Thin Section Study Thin section study suggests that the sandstones and mudstones of the Patonga Claystone differ from each other in terms of both grain size and mineral content. The mudstones studied (Figure A.1a) contain mostly fine grains, while the sandstones (Figure A.1b) contain coarser fine sand and silt size particles. Both types of sediment contain quartz, feldspar and clay minerals. However, chlorite is more abundant in the sandstones while iron oxide is dominant in the mudstones as a cementing material. Most of the grains less than 0.5 millimeters in diameter are angular to sub-angular and poorly sorted. The larger grains, which are less common, tend to be elliptical in cross-section, and are made up of

A - 13 fine argillaceous material representing either rock fragments or sand-sized rounded clay pellets. Some rock specimens are made up of coarser silt sized quartz grains that do not show parallel arrangement. The quartz grains are mostly angular to sub-angular, but totally altered grains of other types (rock fragments and/or clay pellets) are usually rounded.

a). b).

Figure A.1: Quartz and feldspar particles (transparent) embedded in the fine, iron-rich matrix of a mudstone sample (a, sample 143) and coarser quartz and feldspar particles showing a grain to grain framework in a sandstone (b, sample 602). Scale bar = 0.5 mm.

The mudstone in the Patonga Claystone is dark red-brown in colour, and is made up of angular silt sized quartz grains and larger rounded altered grains of microcrystalline low- birefringent material (rock fragments and/or clay pellets). The matrix is also microcrystalline, with abundant opaque (iron oxide) particles, and shows no visible lamination.

Thin section study of some rock samples (e.g. Sample 609) indicates the presence of ferruginous nodules up to 3 millimeter in diameter, in which opaque and semi-opaque layers are arranged concentrically (Figure A.2a). These nodules (or

A - 14 ooliths) were probably formed in the sediment source area and transported into the basin. Similar nodules (or ooliths) are described in other Sydney Basin red-beds by Loughnan et al. (1964). They would have behaved as ‘pseudo-silt’ or ‘pseudo- sand’ particles during deposition. As described by Davis (1967) and McNally (1995), they have also probably increased the inter-granular cohesion of the rocks in which they occur. These pseudo-silt or pseudo-sand particles are visible in rock exposures. Some layers in which they are abundant are more resistant to weathering, and stand out as rock ledges (McNally, 1995). More commonly, however, the mudstones appear from microscope studies to be somewhat poorly cemented.

a). b).

Figure A.2: Oolitic nodule ‘pseudo-silt’ particle (a, sample 609) and lamination (b, sample 203) in mudstones of the Patonga Claystone. Scale bar = 0.5 mm.

Despite similarities in hand specimen, thin sections of other samples (e.g. Sample 203) have a more pronounced lamination in the matrix components (Figure A.2b). A notable feature is a micro-dislocation of the laminae, which is also visible in some instances, as shown by discontinuation of organic-rich layers. This could be due to temporary desiccation and ensuing contraction of the fine sediment in the ancient soil profile, with cracks possibly infilled by

A - 15 coarser-grained overlying material. Alternatively, these features could be due to plant root activity, or to burrowing by other organisms.

Some sandstones (e.g. Sample 215) are light grey in colour under the microscope, but also have irregular brown patches of opaque (iron oxide) minerals (Figure A.3a). The opaque minerals are more concentrated within the coarser- grained patches of the sandstone. The red brown patches are evenly distributed in some rock samples but are less well distributed in the others, and silt sized angular quartz grains occur only rarely in some slides. The clayey groundmass in these materials shows a parallel orientation in respect to bedding, and appears to be mainly microcrystalline, although angular silt-sized particles of quartz are also common in thin section. These patches probably represent post-depositional changes in the sediment due to permeating groundwaters in the original (Triassic) depositional environment.

Rounded fragments of very fine clay-rich material are embedded in some mudstone samples (e.g. Sample 613; Figure A.3b). These probably represent contemporaneous soft-sediment particles or intraclasts, reworked from a slightly older generation of mudstone material.

From thin section studies, the sandstones appear to have a well-developed grain-to-grain framework of quartz and (mainly hard) rock fragments, while the coarser (silt-sized) hard mineral particles (where present) in the mudstones are suspended in a finer-grained to microcrystalline clay-rich matrix, and less grain-to-grain contact between the more rigid framework components.

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a). b).

Figure A.3: irregular brown patches of opaque minerals in sandstone (a, sample 215) and shale fragment (intraclast) in mudstone (b, sample 613). Scale bar = 1 mm.

A.2.2 Scanning Electron Microscopy Study

Scanning electron microscopy (SEM) was employed in an attempt to more closely investigate the microstructure of the rocks in this study. A JEOL 834 unit was used, with a voltage of 20 kV and a working distance of 39 mm. The latter was limited by the requirements of the energy dispersive X-ray analysis (EDX) system. The primary electron beam was used to bombard the sample, generating other interactions, such as secondary electrons, characteristic X-rays, auger electrons and backscattered electrons. These allowed both observation of the mineral textures and analysis the elemental composition of the different components.

The labelling system beneath each SEM image provides information on the conditions used. An example is reproduced in Figure A.4.

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Figure A.4: Labelling system used for SEM images.

The first number is instrument’s file number; the second set of numbers defines the working voltage. In this example x2,000 indicates the magnification ratio, and the horizontal bar with indicated number provides a graphic scale for the image in question. The final number shows the working distance of the apparatus.

Electrical conductivity has to be introduced on to the sample to provide a clearer image. Gold and carbon are normally used for conductivity proposes. In this study carbon was used as the coating material.

Polished sections of a range of samples from low to high slake durability index were prepared for the SEM study.

A - 18

a). b).

c).

Figure A.5: Micrographs showing the effect of different magnifications on images of the clay matrix in a fine grained sandstone (sample number 504).

As can be seen from Figure A.5, the images of the clay minerals in the samples obtained from the SEM study tended to decrease in quality as the magnification was increased from x3,300 (Figure A.5a) to x7,500 (Figure A.5b) and x14,000 times (Figure A.5c). The micrograph shown in Figure A.5a has a clear and definable texture. In an attempt to define the clay mineral assemblage more fully, a portion was photographed at a higher magnification, as shown in Figure A.5b and again in Figure A.5c. The images captured at the higher magnifications, however, were less clear in defining the clay mineral structure. This may be due to the electrical

A - 19 conductivity properties of the samples themselves, or it may be due to micro-fractures in the rock, developed perhaps by burial processes after sedimentation, which give rise to a discontinuous carbon coating (Viera Piegerova, pers. comm., 2000).

a). b).

c). d).

Figure A.6: Micrographs showing features of rocks with low slake durability indices, a = sample 215, b = sample 310, c = sample 203 and d = sample 313. See text for further discussion.

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a). b).

c). d).

Figure A.7: Micrographs showing features of rocks with high slake durability indices, a = sample 205, b and c = sample 504, and d = sample 133. See text for further discussion.

Micrographs taken from less durable rock materials appear to have a loose structure of solid mineral grains embedded in a fine-grained clay matrix (Figure A.6), while those obtained from the more highly durable rocks show extensive grain-to- grain interlock (Figure A.7). Most of the clay particles in the matrix appear to be very fine, typically less than one micron in diameter. Most of the quartz grains appear to be 'floating' in the fine fraction of the sediment, i.e. to be matrix-supported rather than supported by grain-to-grain contacts.

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The micrographs of the samples with low slake durability indices also suggest that the low-durability rock materials contain numerous fractures or fissures, and even some open pores. In the most rapidly deteriorating rock sample identified in the study (sample 310, Figure A.6b), cracks with an opening of greater than 70 µm are present. In other low- durability specimens, micro-cracks with openings of greater than 2 µm are frequently observed (Figure A.6a).

When a comparison is made between rocks with low and high slake durability characteristics, the rocks with low slake durability properties trend to contain continuous fractures, fissures, microcracks and pores, while the rocks with high slake durability properties tend to have a dense matrix, fewer fractures, or fractures with less continuity.

Figure A.6a was obtained from a rock sample (sample 215) having a two-cycle slake durability index of 41%. Figure A.6b was obtained from a mudstone sample (sample 310) that resisted only one cycle in its slake durability test, giving an Id1 value of 3.3%. The latter sample had a high porosity (34.45%), low grain density (1.12), and very high degree of water absorption (30.80%). Figure A.6c was taken from a rock sample (sample 203) that resisted only one cycle of wetting and drying and had an Id1 value of 8.1%. No test results on porosity or water absorption, however, were available for this particular sample. Figure A.6d taken from a sample (sample

313) with a standard [Id2] slake durability index of 32.7%. This mudstone sample has high porosity (27.4%), and quite a high degree of water absorption (19.0%). These details are summarised as in Table A.3.

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Table A.3: Some geotechnical properties of low slake durability rocks as in Figure A.6.

Figure Sample Id2 porosity Grain Water density absorption A.6(a) 41

A.6(b) 3.3(Id1) 34.45 1.12 30.80

A.6(c) 8.1(Id1) N/A N/A N/A A.6(d) 32.7 27.4 19.0

Figure A.7a was obtained from a sample (sample 205) having a 2nd cycle slake durability index of 97.4%, along with a degree of water absorption of 5.7% and a porosity value of 10.7%. Figure A.7b and c were also taken from a high durability rock sample (sample 504) having a standard slake durability (Id2) of 97.8%. The porosity and water absorption of this particular sample were 10.1% and 4.1% respectively. Figure A.7d was obtained from a rock sample (sample 133) with an Id2 value of 91.6%, a low porosity (9.4%) and a low degree of water absorption (5.2%). These details are summarised as in Table A.4.

Table A.4: Some geotechnical properties of low slake durability rocks as in Figure A.7.

Figure Sample Id2 porosity Grain Water density absorption A.7(a) 97.4 10.7 5.7 A.7(b and c) 97.8 10.1 4.1 A.7(d) 91.6 9.4 5.2

The geotechnical data obtained from the samples in Figures A.6 and A.7 clearly indicate that a high porosity and a high degree of water absorption are associated with rocks

A - 23 having low slake durability indices. By contrast, a low porosity and a low degree of water absorption occur in those rocks having high slake durability indices. The SEM photographs support this observation, suggesting a more dense nature of the matrix, a lower proportion of open pores, and the presence of fewer fractures in the high-durability materials.

The geometric arrangement of the framework and matrix elements of the fabric of sedimentary rocks varies in nature, extent and continuity. Three ideal microfabric types, skeletal, matrix and turbostratic microfabric, have been defined to provide a framework for describing such soft rock materials (Huppert, 1988). Which type of microfabric dominates an individual rock depends on both the grain size distribution and the post-depositional loading history (Figure A.8).

Figure A.8: Classification of microfabric types (Huppert, 1988).

A - 24

Skeletal microfabric resembles granular fabrics, with the pore space dominated by irregular intergranular pores. Matrix microfabric has a continuous clay matrix where clay micro- aggregates are in edge-to-face (EF) contact. Turbostratic microfabric has a continuous clay matrix.

Generally, the skeletal and matrix microfabric types are considered to represent the initial fabrics of the sediments Compaction during burial transforms matrix and mixed matrix/skeletal microfabrics into turbostratic fabrics. This leads to a change in the intra-matrix edge-to-face (EF) contacts, e.g. the contact angles become more acute, and also to pore collapse progressively from the larger to the smaller pores (Huppert, 1988). The turbostratic microfabic may, in turn, be transformed back to matrix microfabric by stress relief causing microcrack development.

Due to grain arrangement, and the cohesion between grain/matrix and distributed pore space, rock materials with different microfabrics exhibit differences in their geotechnical properties. Rocks containing turbostratic and skeletal microfabric are respectively high and low in uniaxial compressive strength.

The micrographs suggest that the low slake durability rock materials in Figure A.6 tend to exhibit a skeletal microfabric structure, while the high slake durability materials in Figure A.7 have a matrix and turbostratic microfabric as defined by Huppert (1988) and reproduced in Figure A.8. Slake durability appears to be relatively high in those samples with a continuous matrix (matrix and turbostratic microfabric), but decreases drastically in rocks with a skeletal microfabric (Huppert, 1988).

A - 25

A.3 Swelling Pressure Tests

Swelling can be defined as “a combination of physico- chemical reaction involving water and stress relief. The physico-chemical reaction with water is usually the major contributor to swelling, but swelling can only take place simultaneously with or following stress relief” (Oliver, 1990). This implies that understanding the time-dependent behaviour of the rock material is necessary for the assessment of the engineering geological behaviour of rock masses by observing the weathering characteristics as well as the magnitude of the swelling and shrinkage strains that could develop after exposure (Oliver, 1990).

A free swelling test can be performed by using the apparatus shown in Figure A.9. The aim of this test is to measure the axial and radial free swelling strain developed when an unconfined, undisturbed rock specimen is immersed in water. The swelling displacement is recorded as a function of time elapsed until a constant or a maximum value has been reached. After swelling is terminated, and before the specimen is removed from the cell, the increase in circumference is measured with a stainless-steel band. The axial and radial swelling strain can be calculated from the ratio of axial displacement and radial displacement to original specimen thickness and diameter respectively.

A - 26

Figure A.9: Apparatus for measuring the swelling strain (ISRM, 1989)

Bell (1992) has explained failure occurring in consolidated and poorly cemented rocks in terms of swelling pressure and capillary suction pressure. This failure happens during the saturation process, when the swelling pressure, or internal saturation swelling pressure (σs), developed by capillary suction pressures, exceeds the tensile strength.

Oliver (1990) studied the deterioration of Lower Triassic Karoo Sequence mudstones from mineral contents and evaluation of geomechanical properties, as well as swelling tests. From these studies, the causes of slaking were concluded to be a result of partially irreversible anisotropic shrinkage and expansion of the rock material when subjected to a variable degree of air drying and moisture absorption.

Most of samples for the present study were taken from cored drill-holes, sunk for coal exploration in 1997 or earlier. The drilled cores were left in their aluminium core boxes in the core shed. Air slaking and moisture changes may have affected some parts of the cored intervals. Since the core had been kept unprotected for some time after completion

A - 27 of the drill hole, cutting to particular sizes and shapes was very difficult because of the brittle nature of the mudstone itself and possibly because of moisture content changes.

The free swelling test could not be executed on these moisture-changed rock samples for the present study, for the reasons discussed above. The diameter of the cored sample (60 mm) also did not conform to the suggested method as described in the “Suggested Methods for Laboratory Testing of Argillaceous Swelling Rocks” (ISRM, 1989). Furthermore it was difficult to have three undisturbed specimens for one set of tests. As discussed in ISRM (1989), the rock specimens used in swelling test should:

- have the same density and water content as those in situ at the time of sampling,

- be derived from boring performed with air pressure or, with an anti-swelling admixture (such as Antisol) in the cooling (flushing) water, whichever is best to keep the sample as close to its natural state as possible,

- preferably be close to 100 mm in diameter, with sufficient sample to prepare at least three undisturbed specimens, and have enough additional material for identification tests,

A - 28

A.4. Role of Clay Mineralogy in the Development of Slaking Behaviour

X-ray diffraction analysis, including detailed study of the clay minerals through artificially swelling and collapsing their crystal structures with ethylene glycol and heating (e.g. Hardy and Tucker, 1988; Moore and Reynolds, 1997), has long been used to identify rocks with significant proportions of swelling clay and to indicate any potential of this type. In addition to (pure) smectite, a range of interstratified illite/smectite (I/S) minerals may also be present in Sydney Basin strata (e.g., Ward, 1989, 2001; Ruan and Ward, 2002; Ward, et al., 2003; 2005), with similar but perhaps less intense swelling characteristics with glycol saturation.

Ward (2001) describes a study the clay minerals in a series of coal measure mudstones from the northern Sydney Basin in relation to the resistance of the rocks to slaking in laboratory tests. The slaking test used was similar to the Emerson crumb test (Emerson, 1967) and the jar slaking test (Vellejo, et al., 1993), and involved immersion of small pieces of the rock under test in water. The rocks’ reaction with water uptake were observed and categorized from 1 (total breakdown) to 8 (no reaction), with intermediate stages involving slaking, cracking and swelling behaviour under the water immersion. These rocks contain non-reactive quartz and feldspar as part of their structural framework and clay minerals (kaolinite, illite, and expandable lattice illite/smectite or smectite) bind the quartz-feldspar framework together and make up the remainder of the material present. The results suggest that rocks with low proportions of quartz- plus-feldspar and high total clay contents have a lower resistance to slaking than rocks with lower proportions of clay minerals and higher quartz-plus-feldspar percentages. The same

A - 29 relationship seems to apply whether the expandable-lattice clay mineral is mainly smectite or interstratified illite/smectite (Ward, 2001; Ward et al., 2003; 2005).

Also as described by Ward (2001), the as-sampled moisture content of mudrocks from the floors of two different Sydney Basin coal seams also shows a significant decrease with increasing quartz plus feldspar content and an increase with the total proportion of clay minerals. For a given clay mineral content, the mudrocks of the smectite-bearing beds also hold more moisture than the mudrocks from the I/S rich units (Figure A.10). This presumably reflects the great capacity of “pure” smectite minerals to retain water in their crystal lattice, relative to minerals in which the smectite is interstratified with a less absorptive component.

100

R2 = 0.81(I/S Dominant) R2 = 0.63 (S Dominant) 90

I/S Dominant 50 S Dominant Total Clay - Siroquant (%) 40 0 5 10 15 20 25 Moisture Content (%)

Figure A.10: Correlation between moisture content and the total percentage of clay minerals, determined by XRD and Siroquant, for mudrocks from the coal measures of the northern Sydney Basin (Ward, 2001).

The relation between the unconfined compressive strength (UCS) and mineralogy for a series of Patonga Claystone samples

A - 30 is presented in Figure 5.18. The strength of the mudrocks clearly increases with increasing quartz plus feldspar content and decreases with the proportion of clay minerals, especially the proportion of illite plus illite/smectite. A similar relationship is shown between quartz content determined by XRD and UCS for mudrocks from British coal measures (Smart, et al., 1982; Taylor and Spears, 1970), although with higher strength values for equivalent quartz percentages. Significant feldspar was not reported in the British mudrock materials.

Several researchers have considered rock strength, either point load strength index or uniaxial compressive strength, as a factor controlling rock durability characteristics (e.g. Franklin, 1983; Grainger, 1984; Oliver, 1990; Taylor, 1988; Taylor and Spears, 1970). A plot of uniaxial compressive strength (UCS) against 2nd cycle slake durability index for the Patonga Claystone is shown in Figure 5.23. It is clear that rock with a low UCS value tends to deteriorate more rapidly than rock with a high UCS value. This finding is in agreement with the work of Grainger (1984), Koncagul and Santi (1999), Oliver (1990) and Taylor (1988).

The difference between the relationship of strength to mineralogy in the mudrocks in the Sydney Basin, compared to the relationship displayed by quartzose sandstones from the Hawkesbury Sandstone (Swanson et al., 2002), probably reflects the overall rock fabric. Whereas the strength of the sandstones in that study was derived from a silica-cemented quartz framework reinforced by cohesion from the interstitial clay minerals, the strength of the mudrocks is apparently derived mainly from the cohesion between the clay particles that make up most of the framework. This clay-to-clay framework is apparently reinforced in the mudrocks by the

A - 31 presence of more rigid quartz and feldspar grains, which provide a separate support network through their own grain-to- grain contacts as they increase in overall abundance.

A.5. Loss on Ignition, Water Absorption and Slake Durability Index

A.5.1 Loss on Ignition and Slake Durability Index

Figure 6.6 shows the relation of the second, third and fifth cycle slake durability indices to the total percentage of clay minerals in the present study. Rock samples with 40 to 50% total clay minerals, and, in the absence of significant carbonates and other components, 50 to 60% quartz-plus- feldspar, are relatively resistant to the slaking process, even after five slake durability cycles. Those with a greater proportion of clay minerals, however, and a lesser proportion of quartz-plus-feldspar, show significant breakdown and lower slake durability indices, especially after three or five cycles in the testing apparatus. This is shown by the increasingly greater number of data points among the high-clay samples on the left-hand sides of the respective plots, compared to the equivalent plot for the 2-cycle tests.

A similar trend in relation to slake durability (Figure 6.14) is shown by the loss in mass (loss on ignition) when the oven-dried rock samples are heated to 1050 °C. Since there are no carbonate minerals and no significant organic matter in these particular mudstones, the loss on ignition (LOI) reflects the loss of lattice water from the clay mineral components. The relationship between LOI and slake durability is very similar to that between the total clay mineral percentage and slake durability, but better defined due to the

A - 32 higher precision associated with the LOI determination.

Key minerals, analysed by XRD and evaluated by Siroquant (Ruan and Ward, 2002; Swanson, et al., 2002a; 2002b; Ward, et al., 2001; 2003; 2005), and loss on ignition were plotted against slake durability. The correlation coefficients for these plots were listed in Table 6.1 and Table 6.2 and are reproduced here (Table A.5).

Table A.5: Correlation coefficients for key mineral percentages and loss on ignition, when plotted against slake durability results.

R2 Variable Id2 Id3 Id5 Kaolinite 0.02 0.03 0.06 Illite 0.02 0.02 0.04 Mixed layer clays 0.16 0.24 0.27 Quartz 0.10 0.14 0.16 Quartz + feldspar 0.23 0.32 0.37 Total clay minerals 0.17 0.23 0.25 Loss on Ignition 0.47 0.60 0.62

From the above table, high correlation coefficients were obtained from the evaluation of slake durability index against the LOI (especially for Id5). Lesser correlation coefficients are indicated for slake durability against quartz-plus- feldspar, total clay minerals and mixed layer clay minerals. This is probably due to the greater errors associated with the mineralogical determinations by XRD techniques. Taken with the LOI, however, and in the absence of carbonates or organic matter, the data are interpreted as indicating a relationship between the total proportion of clay minerals in the Patonga Claystone materials, especially the relatively abundant mixed- layer clays, and the slake durability characteristics.

When the sandstones and mudstones are plotted separately,

A - 33 however, the mudstones indicate significantly better correlations of slaking characteristics to LOI than do the sandstones (Figure 6.25). This is partly due to the greater abundance of clay minerals in the mudstones than the sandstones. The sandstones all have LOI values below 5% (Figure 6.25). Mudstones from the sequence with LOI <5% are mostly relatively durable materials, with Id5 always >50% and commonly >80%. With two exceptions the sandstones studied also have high slake durability values (Id5 >90%), although no further correlation appears to exist within this range between LOI and slake durability characteristics. The texture of the sediment, such as the relative abundance of slake-resistant minerals such as quartz in the structural framework, may also play a part in the slaking process.

A.5.2 Water absorption and slake durability index

The degree of water absorption has been evaluated by several researchers in relation to the slaking characteristics of rock materials (e.g. Dick and Shakoor, 1992; Dick, et al., 1994; Morgenstern and Eigenbrod, 1974; Russell, 1982). For durable rocks the amount of water absorption is related to the rock porosity, whereas in slaking rocks it represents a combination of the water filling the pore spaces and the water absorbed into the micro-fractures present in the rock sample, as well possibly as water absorbed into the clay minerals.

The mudstones of the Patonga Claystone have a framework of silt-sized quartz and feldspar particles, set in a matrix of illite, irregularly interstratified illite/smectite (I/S), kaolinite, and chlorite. Although a significant amount of scatter is involved, the percentage of water absorption decreases as the proportion of quartz and feldspar-framework

A - 34 particles increases, and increases with increasing clay mineral (especially illite/smectite) content. The (air-dried) moisture content of the mudstones has a similar relationship to mineralogy, decreasing as quartz plus feldspar increases and increasing with the proportion of interstratified illite/smectite material.

The relationship between water absorption and mineralogy for the mudstones is different to the relationship between porosity and mineralogy for more quartzose sandstones from the Sydney Basin, as described by Swanson et al. (2002). This is due to the different types of rock fabric involved. In the quartzose sandstones the porosity (and hence water absorption) is derived from the intergranular spaces between a relatively open mesh of silica-cemented framework grains. The clays fill these spaces to an extent depending on overall clay mineral abundance, and hence the proportion of unoccupied pore space decreases. No such mesh of coarse, silica-cemented grains, however, occurs in the mudstones of the Patonga Claystone, and the entire rock volume is filled either with quartz and feldspar or with clay minerals. The capacity of the clay minerals to absorb water into their crystal lattices, combined with the probable presence of fissures and micro-pore spaces between the clay particles, provides a greater degree of porosity, and hence a greater degree of water absorption, in the more clay-rich mudstone materials.

The plot of water absorption against slake durability index, as shown in Figure 4.2.13, suggests that rock samples with greater water absorption values tend to be less durable. The results seem to confirm work on other materials carried out by several researchers (e.g. Dick and Shakoor, 1992; Dick, et al., 1994; Emerson, 1967; Morgenstern and Eigenbrod, 1974; Russell, 1982; Vellejo, et al., 1993; Swanson et al., 2002).

A - 35

In conjunction with these studies, this suggests the possibility of using water absorption, possibly together with LOI, as a simple predictor of slake durability characteristics.

A.6. Slaking Behaviour Prediction

From the above discussion, the quartz and feldspar percentage, the percent loss on ignition and the water absorption percentage have stronger correlations to durability than the other factors evaluated. From this it can be concluded that more than one parameter may actually control the slaking behaviour of the rocks studied. Multiple regression analysis was carried out on these parameters, to investigate the use of two or more parameters simultaneously in the prediction process.

The parameters of quartz plus feldspar, moisture content, water absorption and LOI were accordingly inserted into the equations listed in Table A.6 to predict the slake durability index for the standard 2nd cycle test for a series of outcrop samples from the Forresters Beach area. The predicted slake durability values compared to the actual values from the tested samples are listed in Table A.7.

A - 36

Table A.6: Equations used in multiple regression analysis.

Models Parameters R2

1 Id2 = 114.09 – 1.58(Moist) – 3.30(Abs) 0.63

2 Id2 = 76.76 + 0.67(QF) – 3.08(Abs) 0.66

3 Id2 = 179.10 – 2.58(Abs) – 15.47(LOI) 0.68

4 Id2 = 152.79 + 0.29(QF) – 2.58(Abs) – 12.91(LOI) 0.68

5 Id2 = 180.65 + 5.92(Moist) – 2.78(Abs) – 18.55(LOI) 0.68

Notes: (Moist)= remaining moisture content, (Abs) = water absorption, (LOI) = Loss on Ignition (QF) = proportion of quartz plus feldspar evaluated from XRD.

Table A.7: Predicted and observed results for slake durability tests on outcrop samples.

Obs. Input Parameters Predicted Id2 Samples

Moist Abs LOI QF Id2 Model 1 Model 2 Model 3 Model 4 Model 5

1 5.3 29.6 4.3 59.5 19.4 8.2 25.6 36.5 38.4 50.3 2 6.2 27.6 4.3 52.6 20.4 13.3 27.1 40.8 40.8 60.2 3 3.6 28.2 4.8 54.4 20.0 15.3 26.3 31.4 33.3 33.7 5r 5.6 16.9 3.4 63.1 77.6 49.6 67.1 82.2 83.1 102.9 5g 7.3 32.6 4.4 52.1 8.6 -4.9 11.4 26.4 26.5 51.0 6 3.7 9.1 4.3 48.2 81.4 78.08 80.9 89.6 88.2 98.1

Although having similar overall correlation coefficients (Table A.6), the slake durability indices predicted from models 3, 4 and 5 tend to be overestimates for the rock samples with low slake durability indices, but are close to the observed values for the more highly slake resistant rocks. Model number 5 provides an unrealistic predicted index of >100% for sample number 5r. Model number 1 gives underestimates in all cases, with an unrealistic negative index predicted for one sample (sample number 5g). Due to these unrealistic results, model number 1 and number 5 are not considered further at this stage.

A - 37

Model number 2 (Figure A.11a), model number 3 (Figure A.11b) and model number 4 (Figure A.11c) give predicted values close to the observed 2nd cycle slake durability index. Note that the diagonal line indicates the equivalence between observed and predicted values. Departure from this line suggests a difference between the predicted and observed values. One of the predicted indices from model number 2 is lower than the actual value (sample number 5r), but in all other cases the prediction is slightly above the observed value. In general, especially for high-durability rock samples, these three models tend to give closely comparable results.

The differences between observed and predicted slake durability values might indicate some difference between materials in naturally exposed outcrops and samples taken from exploration drill holes. Changes associated with the stored drill cores may have affected the water absorption or the slake durability determinations of the mudstones and sandstones. Differences in the rate of pressure relief between natural exposures and cored samples might also play a role in the development of fractures, and hence produce some differences in slaking characteristics (McNally, 1995). The general agreement between the observed indices for the natural outcrops and the predicted indices from the drill core data, however, suggests that such differences are probably relatively minor.

A - 38

100

20 a). Model 2 0

Predicted 2nd slake values slake 2nd Predicted 0 20406080100 Observed 2nd slake durability index

100

20 b). Model 3 Predicted 2nd slake values Predicted 2nd slake

0 0 20406080100 Observed 2nd slake durability index

100

20 c). Model 4 Predicted 2nd slake values 0 0 20406080100 Observed 2nd slake durability index

Figure A.11: Plots of predicted 2nd slake durability index against observed values evaluated from model 2, 3 and 4.

A - 39

Considering the simplicity of the test program, model 3 is suggested as the best model for predicting slake durability behaviour in the Patonga Claystone, since it is based on only simple laboratory parameters (water absorption and LOI). Even models 2 (quartz-plus-feldspar and water absorption) and 4 (quartz-plus-feldspar, water absorption and LOI) provide good agreement between observed and predicted indices. Determination of mineral percentages (i.e. quartz and feldspar) by XRD and Siroquant requires well-calibrated XRD equipment, a skilled operator, and special, relatively expensive software. The XRD data nevertheless explain the LOI values, and increase confidence in the use of the LOI parameter. The relation between LOI and durability may be quite different, for example, if significant proportions of carbonate minerals or organic matter were also present.

A.7. Applicability and Limited Trialling

From the observed and predicted slake durability, the input parameters (quartz plus feldspar and water absorption) used in model 2 (Table A.7 and Figure A.11a) suggest a better result in predicting the slake durability. However, the difficultly in performing XRD to determine the proportion of quartz plus feldspar may make this approach less convenient in geotechnical laboratory. Instead of taking the quartz plus feldspar into consideration, model number 3 gives similar results with more simple equipment, and still predicts the slake durability index with some level of certainty.

From the plot, predictions for less durable rocks depart more from the observed values and provide a slight overestimation of durability, but for high durable rocks the predictions are close to observed indices. Therefore, when

A - 40 prediction is performed on the Patonga Claystone, estimation of durability in this way should be carried out with some care, especially for rocks with lower slake durability index values.

Standard slake durability testing might be considered as a time consuming process, even with only two cycles of wetting and drying, especially when lots of samples have to be tested. However, water absorption and loss on ignition determination take less time, and many samples can also be evaluated at the same time. Therefore, for quick and easy estimation of the slaking characteristics of the Patonga Claystone, the simple geotechnical/geochemical properties of water absorption and LOI can be used with some level of reliability. This quick method can also be applied when preparing engineering geologic maps with particular reference to delineating the extent of slaking-prone rock materials. Such maps may be useful for applications such as urban planning or road construction. The quick method, when applied to mapping, even with the model number 2 based on XRD analysis, takes less time for preparation than the conventional standard slake durability test.

However, although this numerical method is quick and consumes less time, some limitations are also apparent. The lower slake durability portion (Figure A.11b) suggests that the predicted slake durability index is in some cases twice the observed slake durability value, while the higher slake durability portion (Figure A.11b) suggests a few differences between the predicted and observed slake durability indices. The predicted value in some cases is 5 to 10% higher than the observed slake durability index.

Although the model, when tested against a series of

A - 41 outcrop samples, seems to predict slightly higher slake durability indices than the observed index values, it appears that the model developed, based on simple tests, is suitable for predicting rock durability in broad terms. The predicted model can be used in mapping the extent, for example, of slaking-prone rock types. However, if a more precise predicted value is required, a numerical model including XRD data should probably be applied.

A.8. Fundamental Causes of Slaking Behaviour

A.8.1 Observations

- The degree of slaking, as expressed by parameters such as the slake durability index, has been shown to be related to the relative abundance of clay minerals in the material;

- The dominant clay mineral is an irregularly interstratified illite/smectite, the lattice spacing of which swells to a variable extent with water and ethylene glycol (as shown by the contrast between air-dried, glycolated and heated XRD traces), but less than the swelling associated with pure smectite minerals. The lattices of the other clay minerals in the material, kaolinite, illite and chlorite, do not swell or shrink significantly under these conditions. The swelling pressure may exceed the inter-particle cohesion. The repeated cycle of swelling and then shrinking, i.e. wetting and drying, of the swelling lattice clay minerals results in breaking up of the rock materials;

- A network of fine interparticle pores and microcracks, especially in the mudstones, allows high suction pressures to develop on wetting, causing ‘slaking’ or air breakage at a

A - 42 microscopic scale (fine fragments literally explode due to pore air overpressure ahead of the advancing moisture film). Scanning electron microscope (SEM) studies show a network of fine fissures in the mudstones, and to a lesser extent in the clay matrix of the siltstones and sandstones, with a pattern that could be an expression of shrinkage associated with sample drying in the preparation process (Figures A.6 and Figure A.7);

- The mudstone is susceptible to slaking not only because of its expanding lattice clay mineral content, though this may contribute, but because of its microfabric. The inter-granular pore space is relatively open and hence capable of drawing in air and the moisture film under great pressure;

- The sandstones within the Patonga and Tuggerah Formations are less slake-prone than the mudstones, mainly because their inter-granular cementing (grain to grain) is more complete (McNally, 1995). Nevertheless, these quartz- lithic sandstones degrade more rapidly than more porous arenites such as the Hawkesbury Sandstone. The dry density of the Hawkesbury Sandstone is distinctly lower than that of the less porous Narrabeen Group sandstones, with densities of 2.1 and 2.5 t/m3 respectively (McNally, 1995);

- The Patonga Claystone rock materials exhibit different slaking characteristics in outcrops exposed to sea water compared to those in air. Air-exposed outcrops deteriorate quickly to form rock chips, while seawater-exposed outcrops form hard ground. The difference in the slaking behaviour may be due to the fact that the high salt concentration in the sea water promotes flocculation of the swelling-lattice clay minerals. This would in turn increase the inter-particle cohesion between the clay minerals, which, combined with an

A - 43 environment that is less likely to dry out, increases the slaking resistance. Rocks exposed near or below sea level will maintain a more stable moisture content, due to the more water saturated conditions, compared to those on land which likely to dry out or experience alternate wet and dry conditions. Another factor could be the continual washing away of any loosened debris by wave and/or wind action, so that fresh rock is always exposed. However, flocculation of clay minerals promoting increased cohesion between grains and matrix is thought to be a better explanation of the differences between coastal and other outcrops than washing away of the debris by wave action. The coastal outcrops have been exposed to sea water for a very long time, but have not been eroded away to a significantly greater extent than the other strata in the area;

- The observed relationships between mineralogy and geotechnical properties suggest that the grain-to-grain contacts in the quartz plus feldspar framework governs both the rock strength and the slaking behaviour of the samples studied. The variation in mineral contents of the rock materials (i.e. abundance of quartz + feldspar on the one hand and of total clay minerals on the other; cf. Ward et al., 2003; 2005) or a high concentration of expandable-lattice clay minerals in some layers (McNally, 1995), depending in turn on the sedimentation history, appears to govern the differences in rock slaking characteristics and other geotechnical properties among these and other rock materials (cf. Brady and Brown, 1985; Farmer, 1983; Goodman, 1980). Differences in water absorption properties are also related to differences in geotechnical properties (e.g. Jumikis, 1979; Farmer, 1983; Franklin, 1989; McNally, 1995; McNally and McQueen, 2000). Although the proportion of haematite cement, as revealed by Siroquant evaluation and XRF, is quite small, the haematite is

A - 44 not evenly distributed, making some patches better cemented than others and hence producing differences in slaking characteristics as well as other geotechnical properties;

- The rock close to excavated surfaces crumbles to a depth of several centimetres – that is, to the depth at which stress relief becomes ineffective. Angular chips, typically 10-15mm in diameter, build up on the new rock surface within days; if they are blasted off with an air-water jet a new layer of chips forms just as quickly;

- On the other hand, if the chips are left in place, the slaking mechanism slows down and eventually ceases. The reason for this is not clear, but it could be related to the small degree of confinement imparted by the mat of rock chips, to the moisture equilibrium established between the damp chips and the in situ rock, or to the cessation of inward cracking as surface stresses close to the excavation walls are relieved;

- Over a period of weeks to months the mudstone chips break down further, possibly due to water uptake and clay swelling; dispersive properties of the clay mineral aggregates may also play a part, especially where salt concentrations are low. However this mechanism is much slower than the slaking referred to above. A thin red mud results, but not all chips break down (it is possible that some resist breakdown due to more effective haematite cementing between grains);

- Iron oxide cement might form a bridge between grain aggregates and keep the pore space open, up to the point where overpressure explodes the rock. In other words, the Fe cement may be sufficient to impart a weak rock structure to the mudstones (McNally, 1995).

A - 45

- From the above, the disintegration or slaking of the Patonga Claystone may be summarized as being controlled by the abundance of expandable clay minerals, the overall mineral composition (including non-expanding clays), stress relief caused by excavation, moisture ingress and evaporation, pore space characteristics caused by stress relief, or combinations of several such factors.

A.8.2 Interpretation of the Slaking Process

Bearing these observations in mind, the mechanisms operating to cause the rock degradation process in the Patonga Claystone are suggested to be as follows:

- When the rock material is dry, air is drawn into the outer pores and a high suction pressure develops, increasing the shearing resistance of the individual fragments. The bulk of the voids are filled with air under extreme desiccation conditions (Figure 4.1.1). When the rock material absorbs water, a surface moisture film is drawn into the exposed mudstone by the very high capillary suction pressure developed following stress relief. A cycle of wetting and drying may cause cyclic application of tensional and compressional stresses between the pore walls and between the clay particles (Taylor and Spears, 1970).

- The Patonga Claystone rocks are readily deformable, but are confined by high lateral stresses in their natural state (McNally, 1995). Hence they are prone to extensive microcracking and dilation when these stresses are removed. Even only a 1% increase in rock volume can generate a huge area of cracks when the cracks are only 0.01 millimetres wide (McNally, 1995).

A - 46

- As the microcracking proceeds, air at the tip of the advancing fractures is held under high pressure, possibly 50- 100 Mpa or more (McNally, 1995). The overpressure generated may be sufficient to literally explode the intact rock at a microscopic scale, in cases such as surface exposures, where the cover is only a few millimetres thick. Hence slaking is sometimes referred to as air pressure breakage (Taylor and Smith (1986).

- The tensional stress of the water-clay interaction may be great enough to overcome the poorly cemented bonding strength of the rock material. The strength of the rock material will also decrease when the water film propagates as moisture is absorbed into the rock material (Singh and Cummings, 1983; Taylor and Smith, 1986; Taylor, 1988; Vallejo, et al., 1993). When moist, the fracture strength of the mudstones will be lowered as surface energy is lowered along with the rock strength or shear resistance, i.e. there is a reduction in the coefficient of friction but an increase in the pore pressure (Van Eeckhout, 1976). Without confining pressure, such as when exposure at the ground surface induces stress relief, the rock material will disintegrate or break down (Underwood, 1967; Spears and Taylor, 1972; McNally, 1995).

- A sequence of wetting and drying may also occur. Air is drawn into the outer pores of the rock as it dries out producing high suction pressures. When the rock is wetted again the air is pressurized as a water film is drawn in by capillary action. The repeated cycle of changing tensional stress will thus cause the skeletal structure to be de- stressed and re-stressed. If the stress is higher than the shear strength of the skeletal structure, the mudstones will then slake (Brady and Brown, 1985; Taylor and Smith (1986);

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Taylor and Spears (1970); Vallejo et al. (1993); Van Eeckhout, 1976).

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Additional References

Oliver, H.J., 1990. Some Aspects of the Engineering-Geological Properties of Swelling and Slaking Mudrocks, Proceedings Sixth International Association of Engineering Geology, 707-712.

Pells, PJN., 1985a. Engineering Properties of the Hawkesbury Sandstone. In: Pells, PJN. (ed.) Engineering Geology of the Sydney Region, Balkema, Rotterdam.

Pells, PJN., 1985b. Engineering Properties of the Narrabeen Group. In: Pells, PJN. (ed.) Engineering Geology of the Sydney Region, Balkema, Rotterdam.

Smart, B.G.D., Rowlands, N., Isaac, A.K., 1982, Progress towards establishing relationships between the mineralogy and physical properties of Coal Measures rocks. International Journal of Rock Mechanics and Mining Sciences 19(2), 81-89.

Swanson, J., Ward, C.R., and Franklin, B.J., 2002a. Mineralogy of Sydney building sandstones in relation to geotechnical properties – 1: Relation of quantitative X-ray diffraction data to other chemical and petrographic indicators. Australian Geomechanics 37(5), 140-141.

Swanson, J., Ward, C.R., and Franklin, B.J., 2002b. Mineralogy of Sydney building sandstones in relation to geotechnical properties – 2: Relation of quantitative X-ray diffraction data and cation exchange capacity to geotechnical indicators of rock durability. Australian Geomechanics 37(5), 97-110.

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Ward, C.R., 1989, Minerals in bituminous coals of the Sydney Basin (Australia) and the Illinois Basin (U.S.A.). International Journal of Coal Geology 13, 455-479.

Ward, C.R., 2001. Mineralogical analysis in hazard assessment. In: Geological Hazards – the impact to mining (Ed R. Doyle and J. Moloney), Coalfield Geology Council of New South Wales, Newcastle, 81-88.

Ward, C.R., Matulis, C.E., Taylor, J.C. and Dale, L.S., 2001. Quantification of mineral matter in the Argonne Premium Coals using interactive Rierveld-based X-ray diffraction. International Journal of Coal Geology, 46, 67-82.

Ward, C.R., Nunt-jaruwong, S., Swanson, J. and Crouch, A., 2003. Use of mineralogical analysis in geotechnical assessment of rock strata for coal mining. Proceedings of 20th Pittsburgh Coal Conference, Pittsburgh, Pennsylvania, 20 pp (CD publication).

Ward, C.R., Nunt-jaruwong, S. and Swanson, J., 2005. Use of mineralogical analysis in geotechnical assessment of rock strata for coal mining. International Journal of Coal Geology, 64, 156-171.

List of Editorial Corrections

Corrections requested by Examiner #2

Page Paragraph Line Correction required Correction made

iii 1 3 Insert “and” before “editing” Inserted “and” before “editing” iii 2 2 Change “his” to “their” Changed “his” to “their” viii Fig 1.5 Change “outdrop” to “outcrop” Changed “outdrop” to “outcrop” x 4.2.1 Change “nochange” to “no change” Changed “nochange” to “no change” 2 Fig 1.1 Map of Australia should show Townsville Added “Townsville”, symbol for thrust and legend (Reference) should show symbol system, and North indicator to the map for thrust system. North should be shown on the figure. 2 1 3 Change “formations” to “units” Changed “formations” to “units” 4 Ensure consistent spelling of “grey” or For consistency, “grey” has been used for “grey” but not both the whole text 5 Table 1.2 Change “area” to “areas” Changed “area” to “areas” caption 6 Figure 1.3 The meanings of the abbreviations for Fm, The meaning of these abbreviations has Ss, Cs, RSL, STAT and Clayst should be been added

given B -1 10 2 3 Change “car” to “caravan” Changed “car” to “caravan”

Page Paragraph Line Correction required Correction made

11 2 6 Delete “a” Deleted “a” 15 Table 1.3 Change “1.6” to “1.5” Changed “1.6” to “1.5” caption 30 Figure 2.6 Scale should be indicated Scale added 31 Figure 2.8 Scale should be indicated Scale added 40,67 Figures Should state the type of radiation used Added note on type of radiation used: “Cu , 2.14, 3.8, (Cu K alpha radiation) K alpha radiation” 75,78 3.12, 3.13 44 2 3 Should not use “etc” Changed “etc” to “and” 48 3 2 Examples of other techniques should be Added “such as infrared” after “other stated e.g. infrared techniques” 70 1 8 Change “most of clay” to “most clay” Changed “most of clay” to “most clay” 73 3 1 Change “Ir” to “It” Changed “Ir” to “It” 82, Figure Change “CuKalpha” to “Cu K alpha” Changed “CuKalpha” to “Cu K alpha” 84, 3.16, 85, 3.17, 86, 3.18, 3.19 90 3.20 87 2nd Change “belending” to “blending” Changed “belending” to “blending” last B -2 line

Page Paragraph Line Correction required Correction made

117 3 4 Should explain or delete “too fine” Deleted “too fine or” 136 2 3 Change “test” to “treatment” Changed “test” to “treatment” 183 Figure Scale? Plus size of chips should be stated Scale and size of chips added 4.2.1 196 Figure Scale? Scale added 4.2.5 219 1 3 Change “Figure 4.2.14” to “Figure 4.2.15” Changed “Figure 4.2.14” to “Figure 4.2.15” 219 2 2 What is the unit of measure under the Added “(slake durability index * minutes)” curve? 221 Figure The grouping is not clear or apparent in Added “Highly Durable”, “Intermediate”, 4.2.16 Figures 4.2.16 and4.2.13 “Less Durable” to figure 234 2 3 Change “op cit.” to “1974” Changed “op cit.” to “1974” 253 Figure Scale ? Scale added 5.10 257 Table 5.13 Change “meter” to “metre” Changed “meter” to “metre” 275 1 7 Poor wording. Not appropriate to mention Changed “Microsoft Excel” to “Excel”, with trade names. Should use footnotes or an details provided in a footnote appendix with a list of computer software used

275 2 4 Change “heamatite” to “haematite” Changed “heamatite” to “haematite” B -3 292 Chapter 5, Correlation coefficient is usually Changed “correlation coefficient” to

Page Paragraph Line Correction required Correction made

6, and 7 expressed as R or r and the coefficient of “coefficient of determination” for the determination is usually R2 of r2 whole text 307 2 6 Changed “more” to “less” 309 Figure 6.8 No explanation for the one sample which Explanation and sample number added has a high slake durability index and low

Al2O3 336 2 2 Figure 6.23b is not labelled. Is it the Deleted “b” from “Figure 6.23b” right hand side of Figure 6.23? 336 3 6 label 702 and 801 on Figure Samples 702 and 801 are labelled in Figures 6.23, 6.25 (pages 333, 335) 336 4 7 “Top of the sandstone range” is a very Changed “near the top of the sandstone generalised statement and is only partly range” to “between the mid-range and indicated by figure 6.25 highest values of the sandstones’ LOI” 337 2 LOI, as a useful predictor for sandstone, Deleted “, whether for sandstone or is not shown in Figure 6.25 mudstone materials” 337 3 See Suggestions for Improvement Suggestions incorporated in Addendum 338 Figures Mineralogy is not indicated – photographs Minerals labelled in figures 6.26 & require minerals to be labelled 6.27 B -4 339 3 last Insufficient observations are presented Discussion provided in Section A.2 in for this statement to be made Addendum

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340 1 1 This could be a footnote or listed in an The computer software is defined in a appendix as the computer software used footnote 347 1 2 The “degree of confidence” should be The “degree of confidence” is quantified quantified 347 2 last Change “quartz” to “quartz and feldspar” Changed “quartz” to “quartz and feldspar” 351 Point 8 SEM should have illustrated this statement Additional SEM discussion provided in Addendum 355 2 This is a very important observation that Discussion provided in Addendum needs to be discussed. See Suggestions for Improvement 357 “Grain-to-grain contact” is a statement Extended discussion of SEM and thin that should have been confirmed by section studies provided in Addendum observation (SEM or thin section) 359 2 1 Would the concentration and type of Discussion of these aspects is included in cations in the water play a role? the Addendum Table of Revised page listing compiled Contents

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APPENDIX A

PETROLOGICAL STUDY

Rock studied under microscopic

Sample No. 133 Claystone – fine-grained with a high portion of carbonaceous (organic) matter, which makes the pelitic groundmass almost opaque. Very fine angular grains of quartz are scattered throughout.

Sample No. 143 Mudstone – very fine-grained with organic matter finely dispersed in a mostly structureless groundmass. Angular grains of quartz (<0.5 mm) occur all over. Less frequent are larger elliptical grains made up of fine argillaceous matter (possibly kaolinitized feldspars).

Sample No. 203 Claystone – dark brown, consisting of microcrystalline micaceous clay particles arranged in parallel bands. The thinly laminated structure is caused by streaks and minute lenses of very dark brown opaque organic matter arranged parallel to the bedding. Some areas are made up of coarser grained angular silt sized quartz grains that do not show parallel arrangement.

Sample No. 205 Mudstone – or siltstone, consisting mostly of fine-grained angular quartz of a rather uniform size. Subparallel arrangement of particles is highlighted by occasional presence of altered (chloritized) mica flakes and specks of organic matter. The clayey groundmass is microcrystalline. Some minute accessory minerals are present.

Sample No. 215 Similar to section 205, however the lamination is more conspicuous due to an alternation of fine and coarser lamellae. Quartz grains are angular to subangular, while totally altered (microcrystalline) grains of other minerals are usually rounded. There are some accessory minerals in the coarser laminae-micas, both muscovite and biotite, chlorite, zircon, opaque minerals, as well as specks of organic matter. Tiny flakes of sericite occur in fine lamellae.

Sample No. 310 Claystone, dark brown, laminated and made up of microcrystalline clay material. The structure is mostly entirely obliterated by abundant organic matter. Some angular particles of quartz are recognizable in laminae devoid of organic matter.

Sample No. 504 Mudstone with alternating light and dark brown layers – poor and rich in organic matter. The lighter layers contain coarser grains than the darker ones. Clastic minerals are represented by angular quartz and rounded grains of microcrystalline material (originally feldspar?). Some minute flakes of sirecite were occasionally noted. The pelitic groundmass is microcrystalline. This thin section is similar to Nos. 215 and 310.

Sample No. 506 Claystone, dark brown with a pelitic structure. Irrigular clouds of organic matter mask completely the microcrystalline groundmass. Some angular silt size particles of quartz are present.

Sample No. 513 Claystone-mudstone, dark brown with a subparallel arrangement of microcrystalline pelitic matter. Organic matter forms lenticles and short laminea or uneven specks. It clouds and masks the clay. Some angular silt size quartz grains are present.

Sample No. 512 Similar to the previous section, however the lamination is more pronounced. A notable feature is a microdislocation of the laminea revealed by discontinuation of organic-rich laminea. This could be due to temporary desiccation and ensuing contraction of matter in the ancient soil profile. The cracks might have been filled with coarser overlaying material.

Sample No. 602 Claystone – mudstone, light grey with irregular brown patches of organic matter. The clayey groundmass shows a parallel orientation in respect to bedding. It is microcrystalline, appears to be micaceous. Angular silt particles of quartz are common. The organic matter is more concentrated within coarser patches and is totally opaque.

Sample No. 609 Mudstone, dark brown, made up of angular silt sized quartz grains and larger rounded altered grains of microcrystalline material. The microcrystalline groundmass does not show any lamination. The section contains several nodules (up to 3mm in diameter) in which carbonaceous opaque and semi-opaque material is arranged concentrically (?remnants of roots). Their rims are made of light brown material with concentric zonal arrangement visible under crossed polars (colloidal structure, possibly limonite?). Sample No. 613 Similar to the above. The lamination is rather more noticeable. No nodules with concentric texture present. Rounded fragments of very fine clay material are embedded in the mudstone (?older generation of claystone).

Sample No. 615 Claystone, stained grayish brown. Brown stains contain organic matter. Texture is pelitic microcrystalline. There is no difference between brown and light patches. Some silt sized angular quartz is present. Specks of opaque organic matter are scattered in the groundmass, however they are more common in the brown patches.

Sample No. 701 Claystone, dark brown, opaque organic matter is distributed more evenly. Consists of pelitic material, which is very fine and contains very fine particles of quartz. Larger, silt sized angular quartz grains occur only rarely.

APPENDIX B

X-RAY DIFFRACTOGRAM &

SIROQUANT RESULTS

Notes: 1. Samples number with extensions of *.ar, *.ad, *.gl, and *.h4, are referred to sample as received random powder, air dried, glycol, heated at 400 °C respectively;

2. Not all of X-ray diffractograms are shown in this appendix;

3. In orientation clay aggregates (slides), air dried, glycorated and heated sample are displayed from bottom to top respectively.

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0 0102030 2-Theta Angle (degree) Mineral 130 Error 131 Error 132 Error 133 Error 134 Error 135 Error 136 Error Quartz 47.4 0.56 41.90.69 32.2 0.73 34.9 0.96 33.5 0.78 32.8 0.57 41.8 0.90 Kaolinite 8.7 0.30 13.90.62 10.8 0.37 10.4 0.64 11.1 0.67 15.7 0.50 6.1 0.36 Illite 15.2 0.47 17.00.70 20.1 1.11 18.3 1.20 16.3 1.39 16.0 0.90 14.4 0.94 Chlorite 0 0.53 2.6 0.59 2.4 0.44 1.0 0.55 4.3 0.56 2.1 0.41 2.5 0.64 Mixed layer 13.5 0.55 15.0 0.86 20.3 1.35 21.0 1.70 19.6 0.96 19.7 0.87 26.7 1.13 Albite 8.9 0.43 8.9 0.33 8.0 0.48 8.2 0.50 9.8 0.60 8.2 0.45 4.3 0.77 Heamatite 5.7 0.19 0.4 0.18 5.5 0.19 5.8 0.24 4.8 0.23 5.4 0.18 3.9 0.23 Siderite 0 0.20 0 0.20 0.1 0.17 0 0.20 0 0.23 0 0.18 0 0.23 Anatase 0.6 0.15 0.2 0.15 0.6 0.13 0.5 0.15 0.6 0.17 0 0.13 0.2 0.18 Global Chi2 4.45 6.82 4.78 5.03 7.35 4.20 6.51

Mineral 137 Error 138 Error 139 Error 140 Error 141 Error 142 Error 143 Error Quartz 44.2 0.94 39.40.91 39.8 0.56 39.0 0.63 47.9 0.96 40.4 0.80 44.2 1.72 Kaolinite 9.6 0.61 11.2 0.48 6.4 0.29 4.7 0.22 8.0 1.45 9.2 0.42 6.7 0.60 Illite 10.0 0.79 9.8 1.1812.4 0.46 11.0 0.76 16.0 0.80 20.8 0.99 21.6 1.43 Chlorite 3.7 0.52 5.8 0.49 1.9 0.50 2.0 0.51 3.0 0.33 3.0 0.60 0.6 0.11 Mixed layer 25.7 1.21 23.5 1.37 32.5 0.77 30.6 0.87 9.9 0.42 19.4 1.09 17.9 2.78 Albite 4.2 0.68 7.8 0.27 1.6 0.14 6.9 0.27 10.1 0.50 1.4 0.14 3.6 0.87 Heamatite 1.9 0.19 1.8 0.19 5.2 0.21 5.8 0.20 4.7 0.23 4.9 0.25 5.2 0.31 Siderite 0 0.20 0 0.20 0 0.23 0 0.21 0 0.23 0 0.26 0 0.26 Anatase 0.5 0.15 0.5 0.15 0.2 0.17 0 0.17 0.3 0.17 0.6 0.19 0 0.19 Global Chi2 7.61 7.05 5.70 5.99 5.27 6.25 6.42

Mineral 144 Error 145 Error 146 Error 203 Error 205 Error 211 Error 212 Error Quartz 39.9 0.70 43.10.92 37.6 1.56 36.2 0.98 34.1 0.55 36.9 0.74 31.1 0.54 Kaolinite 10.3 0.63 11.70.45 12.3 0.71 11.5 1.27 14.2 0.87 8.1 0.5916.3 0.42 Illite 13.5 0.79 16.00.57 14.5 1.82 17.5 0.89 16.8 0.58 15.9 0.90 10.0 0.83 Chlorite 1.5 0.54 0.2 0.58 0.1 0.01 2.8 0.83 1.0 0.38 3.9 0.54 0 0.36 Mixed layer 22.2 0.90 20.5 1.49 21.0 2.82 19.7 1.52 17.4 0.73 22.4 1.06 28.9 0.96 Albite 8.1 0.39 4.9 0.30 8.0 0.46 8.3 0.50 16.6 0.45 9.1 0.61 8.7 0.36 Heamatite 4.0 0.21 3.2 0.21 5.9 0.30 3.8 0.22 0 0.15 3.6 0.20 4.9 0.16 Siderite 0 0.21 0 0.23 0 0.20 0 0.22 0 0.16 0 0.20 0 0.13 Anatase 0.5 0.16 0.4 0.17 0.4 0.15 0.1 0.16 0 0.13 0 0.15 0 0.10 Global Chi2 5.87 5.13 5.12 5.08 4.68 6.96 4.94

Mineral 213 Error 214 Error 215 Error 216 Error 217 Error 310 Error 311 Error Quartz 44.9 0.97 36.20.53 27.6 0.61 37.4 0.94 34.0 0.58 32.0 0.67 34.8 0.70 Kaolinite 11.0 0.78 9.5 0.41 11.7 0.49 6.8 0.38 9.7 0.54 9.6 1.05 11.1 0.96 Illite 15.6 0.81 19.30.65 22.2 0.86 14.6 1.07 18.4 0.68 14.7 0.70 10.7 0.76 Chlorite 0 0.54 0.4 0.65 0.5 0.41 0 0.56 2.1 0.43 2.1 0.51 0 0.38 Mixed layer 17.1 1.24 22.0 0.67 25.4 1.38 25.6 1.52 19.5 1.02 29.2 1.04 31.7 1.02 Albite 8.7 0.67 6.5 0.38 7.9 0.36 12.0 0.58 11.2 0.32 6.2 0.56 8.6 0.49 Heamatite 2.7 0.21 5.6 0.19 4.6 0.19 2.9 0.20 4.8 0.18 6.3 0.21 2.8 0.15 Siderite 0 0.22 0 0.20 0 0.17 0 0.21 0 0.19 0 0.19 0 0.15 Anatase 0 0.16 0.4 0.15 0 0.13 0.6 0.16 0.2 0.14 0 0.14 0.3 0.12 Global Chi2 7.20 6.57 6.63 6.06 5.72 7.47 4.66

Mineral 312 Error 313 Error 409 Error 414 Error 501 Error 502 Error 504 Error Quartz 33.4 0.47 34.80.66 35.6 0.48 34.2 0.45 32.2 0.78 31.0 0.72 38.9 0.74 Kaolinite 13.2 0.48 14.00.48 18.9 0.48 12.4 0.45 12.5 1.08 13.1 0.77 11.6 0.50 Illite 17.2 0.60 10.40.88 12.7 0.66 18.8 0.54 22.0 0.92 19.4 1.00 17.9 0.83 Chlorite 0 0.47 0.1 0.43 2.3 0.44 4.3 0.43 2.2 0.49 0.4 0.07 1.7 0.43 Mixed layer 22.5 0.73 27.7 1.07 20.1 0.61 17.2 0.62 20.6 1.38 22.9 1.39 16.6 1.18 Albite 8.7 0.31 8.9 0.45 10.1 0.37 13.0 0.42 6.3 0.44 8.1 0.39 11.1 0.40 Heamatite 4.9 0.16 3.8 0.16 0 0.15 0.1 0.15 4.0 0.19 4.9 0.18 1.8 0.16 Siderite 0 0.17 0 0.16 0 0.16 0 0.16 0 0.18 0 0.15 0 0.17 Anatase 0.1 0.13 0.3 0.12 0.3 0.12 0 0.12 0.2 0.14 0.3 0.11 0.4 0.12 Global Chi2 5.74 4.43 4.13 5.69 5.27 5.40 5.24

Mineral 506 Error 508 Error 511 Error 512 Error 513 Error 602 Error 605 Error Quartz 34.6 0.81 32.70.83 34.8 0.96 34.9 0.75 30.4 0.65 37.7 0.66 29.9 0.62 Kaolinite 13.1 0.82 12.00.92 13.4 0.99 9.2 0.4413.3 0.48 14.2 0.86 16.0 0.51 Illite 11.5 1.00 10.81.08 11.7 1.14 10.4 0.96 14.4 1.00 20.5 0.64 12.3 1.33 Chlorite 0.3 0.36 3.1 0.40 0 0.42 3.1 0.37 0.1 0.40 2.3 0.41 2.1 0.44 Mixed layer 30.8 1.31 32.4 1.38 26.9 1.59 27.8 1.29 32.2 1.16 17.4 0.96 24.0 0.92 Albite 4.4 0.35 4.2 0.41 9.4 0.45 11.8 0.42 5.6 0.41 7.3 0.34 9.1 0.41 Heamatite 4.9 0.17 4.3 0.19 3.7 0.19 2.5 0.15 3.5 0.17 0 0.14 6.3 0.19 Siderite 0 0.15 0 0.17 0 0.17 0 0.15 0 0.16 0 0.15 0 0.17 Anatase 0.5 0.12 0.6 0.13 0.1 0.13 0.4 0.11 0.3 0.12 0.6 0.11 0.3 0.13 Global Chi2 4.86 5.21 4.51 5.18 4.94 4.46 5.04

Mineral 606 Error 607 Error 608 Error 609 Error 612 Error 613 Error 615 Error Quartz 36.8 0.47 34.40.68 35.2 0.69 34.9 0.78 39.3 0.55 32.1 0.80 32.8 0.74 Kaolinite 11.9 0.30 14.50.48 13.5 1.11 12.5 0.50 24.4 0.56 11.0 0.55 11.2 0.47 Illite 18.0 0.43 13.10.89 11.7 0.63 12.1 1.03 7.4 0.6815.2 1.14 12.5 1.10 Chlorite 0.5 0.06 0.8 0.41 3.3 0.48 0.3 0.42 4.0 0.54 2.7 0.47 0.2 0.35 Mixed layer 16.7 0.85 25.7 1.14 22.7 0.93 30.8 1.25 7.4 0.50 26.8 1.45 33.7 1.22 Albite 13.4 0.39 5.9 0.40 13.4 0.44 3.7 0.48 17.3 0.50 6.5 0.48 5.5 0.41 Heamatite 2.2 0.16 5.1 0.17 0 0.16 5.2 0.19 0 0.19 5.2 0.21 3.7 0.18 Siderite 0 0.17 0 0.16 0 0.17 0 0.17 0 0.20 0 0.19 0 0.17 Anatase 0.4 0.13 0.6 0.12 0.3 0.13 0.5 0.13 0 0.15 0.3 0.14 0.3 0.13 Global Chi2 5.61 4.48 4.71 4.51 5.37 4.60 4.26

Mineral 701 Error 702 Error 703 Error 704 Error 705 Error 706 Error 708 Error Quartz 31.9 0.60 39.80.74 34.8 0.49 48.1 0.64 36.8 0.59 41.4 0.66 36.7 0.60 Kaolinite 13.2 0.42 14.70.87 15.5 0.42 16.0 0.54 18.2 0.50 16.1 0.76 12.7 0.49 Illite 15.8 0.94 8.5 0.6918.6 0.79 10.8 0.71 15.2 0.81 11.7 0.74 14.0 0.80 Chlorite 0.2 0.15 2.1 0.50 2.0 0.38 1.0 0.53 0 0.47 3.8 0.46 2.9 0.50 Mixed layer 25.0 1.09 17.9 0.96 13.7 0.58 9.6 0.37 13.4 0.80 7.5 0.65 16.2 0.80 Albite 8.0 0.34 13.10.54 10.1 0.40 8.0 0.3911.4 0.44 15.0 0.48 11.1 0.50 Heamatite 5.6 0.17 3.9 0.18 5.1 0.15 6.1 0.20 4.7 0.18 4.5 0.17 5.9 0.19 Siderite 0 0.14 0 0.18 0 0.15 0 0.21 0 0.18 0 0.17 0 0.19 Anatase 0.4 0.11 0 0.14 0.2 0.11 0.5 0.16 0.2 0.13 0 0.13 0.5 0.14 Global Chi2 4.94 5.07 4.58 4.33 5.41 4.80 5.00

Mineral 801 Error 809 Error 815 Error 820 Error O3R Error Quartz 42.9 0.62 40.10.47 36.4 0.51 43.9 0.86 34.0 0.75 Kaolinite 23.6 0.57 24.90.46 22.6 0.45 13.8 0.53 16.4 1.01 Illite 6.7 0.73 8.9 0.55 9.6 0.63 8.1 0.81 8.1 1.09 Chlorite 5.6 0.55 3.2 0.44 2.9 0.37 2.0 0.51 2.8 0.50 Mixed layer 6.1 0.48 7.4 0.45 10.7 0.77 18.1 1.20 20.6 1.02 Albite 15.1 0.52 15.60.41 17.8 0.45 13.8 0.59 18.1 0.57 Heamatite 0 0.19 0 0.15 0 0.14 0 0.19 0 0.17 Siderite 0 0.21 0 0.16 0 0.15 0 0.20 0 0.18 Anatase 0 0.15 0 0.12 0 0.11 0.3 0.15 0.1 0.14 Global Chi2 6.00 5.39 5.61 5.43 5.97

APPENDIX C

GEOTECHNICAL RESULTS

Sample no 130 Container wt. 297.56 gm Container no 130 Before Cont + rock wt. 936.31 gm rock wt. 638.75 gm After Cont + rock wt. 921.48 gm rock wt. 623.92 gm Moisture content 2.38 % 1st cycle Before Cont + rock wt. 922.84 gm After Cont + rock wt. 911.86 gm rock wt. 614.30 gm

Id1 98.46 % type 2

2nd cycle Before Cont + rock wt. 904.20 gm After Cont + rock wt. 893.42 gm rock wt. 595.86 gm

Id2 95.50 % type 2

3rd cycle Before Cont + rock wt. 886.33 gm After Cont + rock wt. 874.35 gm rock wt. 576.79 gm

Id3 92.45 % type 2

4th cycle Before Cont + rock wt. 862.63 gm After Cont + rock wt. 851.24 gm rock wt. 553.68 gm

Id4 88.74 % type 2

5th cycle Before Cont + rock wt. 845.73 gm After Cont + rock wt. 834.79 gm rock wt. 537.23 gm

Id5 86.10 % type 2

Sample no 131 Container wt. 326.09 gm Container no 131 Before Cont + rock wt. 890.08 gm rock wt. 563.99 gm After Cont + rock wt. 879.03 gm rock wt. 552.94 gm Moisture content 2.00 % 1st cycle Before Cont + rock wt. 877.43 gm After Cont + rock wt. 872.03 gm rock wt. 545.94 gm

Id1 98.73 % type 1

2nd cycle Before Cont + rock wt. 873.40 gm After Cont + rock wt. 866.07 gm rock wt. 539.98 gm

Id2 97.66 % type 1

3rd cycle Before Cont + rock wt. 866.50 gm After Cont + rock wt. 860.78 gm rock wt. 534.69 gm

Id3 96.70 % type 1

4th cycle Before Cont + rock wt. 862.99 gm After Cont + rock wt. 856.53 gm rock wt. 530.44 gm

Id4 95.93 % type 1

5th cycle Before Cont + rock wt. 857.90 gm After Cont + rock wt. 852.08 gm rock wt. 525.99 gm

Id5 95.13 % type 1 Sample no 132 Container wt. 374.05 gm Container no 132 Before Cont + rock wt. 1018.82 gm rock wt. 644.77 gm After Cont + rock wt. 1003.16 gm rock wt. 629.11 gm Moisture content 2.49 % 1st cycle Before Cont + rock wt. 1004.50 gm After Cont + rock wt. 994.60 gm rock wt. 620.55 gm

Id1 98.64 % type 2

2nd cycle Before Cont + rock wt. 971.28 gm After Cont + rock wt. 958.37 gm rock wt. 584.32 gm

Id2 92.88 % type 2

3rd cycle Before Cont + rock wt. 932.13 gm After Cont + rock wt. 919.10 gm rock wt. 545.05 gm

Id3 86.64 % type 2

4th cycle Before Cont + rock wt. 890.08 gm After Cont + rock wt. 873.89 gm rock wt. 499.84 gm

Id4 79.45 % type 2

5th cycle Before Cont + rock wt. 845.51 gm After Cont + rock wt. 830.00 gm rock wt. 455.95 gm

Id5 72.48 % type 2

Sample no 133 Container wt. 557.61 gm Container no 133 Before Cont + rock wt. 1205.57 gm rock wt. 647.96 gm After Cont + rock wt. 1189.33 gm rock wt. 631.72 gm Moisture content 2.57 % 1st cycle Before Cont + rock wt. 1187.61 gm After Cont + rock wt. 1178.20 gm rock wt. 620.59 gm

Id1 98.24 % type 2

2nd cycle Before Cont + rock wt. 1150.60 gm After Cont + rock wt. 1136.48 gm rock wt. 578.87 gm

Id2 91.63 % type 2

3rd cycle Before Cont + rock wt. 1083.65 gm After Cont + rock wt. 1067.36 gm rock wt. 509.75 gm

Id3 80.69 % type 2

4th cycle Before Cont + rock wt. 998.24 gm After Cont + rock wt. 981.55 gm rock wt. 423.94 gm

Id4 67.11 % type 3

5th cycle Before Cont + rock wt. 924.00 gm After Cont + rock wt. 911.04 gm rock wt. 353.43 gm

Id5 55.95 % type 3 Sample no 134 Container wt. 357.54 gm Container no 134 Before Cont + rock wt. 973.78 gm rock wt. 616.24 gm After Cont + rock wt. 959.28 gm rock wt. 601.74 gm Moisture content 2.41 % 1st cycle Before Cont + rock wt. 957.98 gm After Cont + rock wt. 950.92 gm rock wt. 593.38 gm

Id1 98.61 % type 1

2nd cycle Before Cont + rock wt. 945.31 gm After Cont + rock wt. 937.14 gm rock wt. 579.60 gm

Id2 96.32 % type 1

3rd cycle Before Cont + rock wt. 930.50 gm After Cont + rock wt. 922.11 gm rock wt. 564.57 gm

Id3 93.82 % type 2

4th cycle Before Cont + rock wt. 915.33 gm After Cont + rock wt. 907.47 gm rock wt. 549.93 gm

Id4 91.39 % type 2

5th cycle Before Cont + rock wt. 904.28 gm After Cont + rock wt. 894.48 gm rock wt. 536.94 gm

Id5 89.23 % type 2

Sample no 135 Container wt. 356.14 gm Container no 135 Before Cont + rock wt. 980.65 gm rock wt. 624.51 gm After Cont + rock wt. 962.16 gm rock wt. 606.02 gm Moisture content 3.05 % 1st cycle Before Cont + rock wt. 956.36 gm After Cont + rock wt. 944.20 gm rock wt. 588.06 gm

Id1 97.04 % type 1

2nd cycle Before Cont + rock wt. 864.71 gm After Cont + rock wt. 850.42 gm rock wt. 494.28 gm

Id2 81.56 % type 2

3rd cycle Before Cont + rock wt. 741.74 gm After Cont + rock wt. 730.32 gm rock wt. 374.18 gm

Id3 61.74 % type 2

4th cycle Before Cont + rock wt. 652.32 gm After Cont + rock wt. 643.56 gm rock wt. 287.42 gm

Id4 47.43 % type 2

5th cycle Before Cont + rock wt. 598.13 gm After Cont + rock wt. 591.67 gm rock wt. 235.53 gm

Id5 38.86 % type 2 Sample no 136 Container wt. 371.97 gm Container no 136 Before Cont + rock wt. 1134.44 gm rock wt. 762.47 gm After Cont + rock wt. 1113.05 gm rock wt. 741.08 gm Moisture content 2.89 % 1st cycle Before Cont + rock wt. 1111.20 gm After Cont + rock wt. 1097.02 gm rock wt. 725.05 gm

Id1 97.84 % type 1

2nd cycle Before Cont + rock wt. 1037.00 gm After Cont + rock wt. 1018.62 gm rock wt. 646.65 gm

Id2 87.26 % type 2

3rd cycle Before Cont + rock wt. 910.41 gm After Cont + rock wt. 893.11 gm rock wt. 521.14 gm

Id3 70.32 % type 2

4th cycle Before Cont + rock wt. 812.39 gm After Cont + rock wt. 798.81 gm rock wt. 426.84 gm

Id4 57.60 % type 2

5th cycle Before Cont + rock wt. 748.96 gm After Cont + rock wt. 736.14 gm rock wt. 364.17 gm

Id5 49.14 % type 2

Sample no 137 Container wt. 361.83 gm Container no 137 Before Cont + rock wt. 949.45 gm rock wt. 587.62 gm After Cont + rock wt. 933.58 gm rock wt. 571.75 gm Moisture content 2.78 % 1st cycle Before Cont + rock wt. 930.65 gm After Cont + rock wt. 922.23 gm rock wt. 560.40 gm

Id1 98.01 % type 1

2nd cycle Before Cont + rock wt. 918.20 gm After Cont + rock wt. 912.28 gm rock wt. 550.45 gm

Id2 96.27 % type 1

3rd cycle Before Cont + rock wt. 910.91 gm After Cont + rock wt. 904.08 gm rock wt. 542.25 gm

Id3 94.84 % type 1

4th cycle Before Cont + rock wt. 903.25 gm After Cont + rock wt. 895.65 gm rock wt. 533.82 gm

Id4 93.36 % type 1

5th cycle Before Cont + rock wt. 894.10 gm After Cont + rock wt. 887.32 gm rock wt. 525.49 gm

Id5 91.91 % type 1 Sample no 138 Container wt. 335.17 gm Container no 138 Before Cont + rock wt. 1026.90 gm rock wt. 691.73 gm After Cont + rock wt. 1009.37 gm rock wt. 674.20 gm Moisture content 2.60 % 1st cycle Before Cont + rock wt. 1007.30 gm After Cont + rock wt. 998.62 gm rock wt. 663.45 gm

Id1 98.40 % type 1

2nd cycle Before Cont + rock wt. 997.35 gm After Cont + rock wt. 989.36 gm rock wt. 654.19 gm

Id2 97.03 % type 1

3rd cycle Before Cont + rock wt. 988.65 gm After Cont + rock wt. 980.88 gm rock wt. 645.71 gm

Id3 95.77 % type 1

4th cycle Before Cont + rock wt. 980.28 gm After Cont + rock wt. 972.99 gm rock wt. 637.82 gm

Id4 94.60 % type 2

5th cycle Before Cont + rock wt. 974.06 gm After Cont + rock wt. 966.61 gm rock wt. 631.44 gm

Id5 93.66 % type 2

Sample no 139 Container wt. 298.31 gm Container no 139 Before Cont + rock wt. 970.36 gm rock wt. 672.05 gm After Cont + rock wt. 950.08 gm rock wt. 651.77 gm Moisture content 3.11 % 1st cycle Before Cont + rock wt. 932.06 gm After Cont + rock wt. 912.52 gm rock wt. 614.21 gm

Id1 94.24 % type 2

2nd cycle Before Cont + rock wt. 728.05 gm After Cont + rock wt. 706.07 gm rock wt. 407.76 gm

Id2 62.56 % type 2

3rd cycle Before Cont + rock wt. 507.23 gm After Cont + rock wt. 495.03 gm rock wt. 196.72 gm

Id3 30.18 % type 3

4th cycle Before Cont + rock wt. 401.36 gm After Cont + rock wt. 394.14 gm rock wt. 95.83 gm

Id4 14.70 % type 3

5th cycle Before Cont + rock wt. 364.94 gm After Cont + rock wt. 359.17 gm rock wt. 60.86 gm

Id5 9.34 % type 3 Sample no 140 Container wt. 374.62 gm Container no 140 Before Cont + rock wt. 1036.86 gm rock wt. 662.24 gm After Cont + rock wt. 1017.64 gm rock wt. 643.02 gm Moisture content 2.99 % 1st cycle Before Cont + rock wt. 1011.94 gm After Cont + rock wt. 1001.02 gm rock wt. 626.40 gm

Id1 97.42 % type 1

2nd cycle Before Cont + rock wt. 956.87 gm After Cont + rock wt. 943.97 gm rock wt. 569.35 gm

Id2 88.54 % type 2

3rd cycle Before Cont + rock wt. 876.08 gm After Cont + rock wt. 863.45 gm rock wt. 488.83 gm

Id3 76.02 % type 2

4th cycle Before Cont + rock wt. 799.98 gm After Cont + rock wt. 787.85 gm rock wt. 413.23 gm

Id4 64.26 % type 2

5th cycle Before Cont + rock wt. 729.46 gm After Cont + rock wt. 719.74 gm rock wt. 345.12 gm

Id5 53.67 % type 2

Sample no 141 Container wt. 326.80 gm Container no 141 Before Cont + rock wt. 964.17 gm rock wt. 637.37 gm After Cont + rock wt. 944.39 gm rock wt. 617.59 gm Moisture content 3.20 % 1st cycle Before Cont + rock wt. 942.68 gm After Cont + rock wt. 933.23 gm rock wt. 606.43 gm

Id1 98.19 % type 1

2nd cycle Before Cont + rock wt. 911.91 gm After Cont + rock wt. 900.13 gm rock wt. 573.33 gm

Id2 92.83 % type 2

3rd cycle Before Cont + rock wt. 858.20 gm After Cont + rock wt. 843.81 gm rock wt. 517.01 gm

Id3 83.71 % type 2

4th cycle Before Cont + rock wt. 777.98 gm After Cont + rock wt. 765.99 gm rock wt. 439.19 gm

Id4 71.11 % type 2

5th cycle Before Cont + rock wt. 715.88 gm After Cont + rock wt. 704.27 gm rock wt. 377.47 gm

Id5 61.12 % type 2 Sample no 142 Container wt. 557.60 gm Container no 142 Before Cont + rock wt. 1276.33 gm rock wt. 718.73 gm After Cont + rock wt. 1254.63 gm rock wt. 697.03 gm Moisture content 3.11 % 1st cycle Before Cont + rock wt. 1246.28 gm After Cont + rock wt. 1231.91 gm rock wt. 674.31 gm

Id1 96.74 % type 2

2nd cycle Before Cont + rock wt. 1141.44 gm After Cont + rock wt. 1127.72 gm rock wt. 570.12 gm

Id2 81.79 % type 2

3rd cycle Before Cont + rock wt. 1044.12 gm After Cont + rock wt. 1030.70 gm rock wt. 473.10 gm

Id3 67.87 % type 2

4th cycle Before Cont + rock wt. 947.78 gm After Cont + rock wt. 938.15 gm rock wt. 380.55 gm

Id4 54.60 % type 2

5th cycle Before Cont + rock wt. 897.26 gm After Cont + rock wt. 889.16 gm rock wt. 331.56 gm

Id5 47.57 % type 2

Sample no 143 Container wt. 371.24 gm Container no 143 Before Cont + rock wt. 1161.40 gm rock wt. 790.16 gm After Cont + rock wt. 1138.69 gm rock wt. 767.45 gm Moisture content 2.96 % 1st cycle Before Cont + rock wt. 1069.49 gm After Cont + rock wt. 1043.79 gm rock wt. 672.55 gm

Id1 87.63 % type 1

2nd cycle Before Cont + rock wt. 769.29 gm After Cont + rock wt. 751.06 gm rock wt. 379.82 gm

Id2 49.49 % type 2

3rd cycle Before Cont + rock wt. 549.03 gm After Cont + rock wt. 533.74 gm rock wt. 162.50 gm

Id3 21.17 % type 2

4th cycle Before Cont + rock wt. 425.70 gm After Cont + rock wt. 421.04 gm rock wt. 49.80 gm

Id4 6.49 % type 2

5th cycle Before Cont + rock wt. 394.28 gm After Cont + rock wt. 391.28 gm rock wt. 20.04 gm

Id5 2.61 % type 2 Sample no 144 Container wt. 357.14 gm Container no 144 Before Cont + rock wt. 1049.25 gm rock wt. 692.11 gm After Cont + rock wt. 1028.18 gm rock wt. 671.04 gm Moisture content 3.14 % 1st cycle Before Cont + rock wt. 1027.63 gm After Cont + rock wt. 1017.75 gm rock wt. 660.61 gm

Id1 98.44 % type 1

2nd cycle Before Cont + rock wt. 1006.88 gm After Cont + rock wt. 995.66 gm rock wt. 638.52 gm

Id2 95.15 % type 2

3rd cycle Before Cont + rock wt. 983.23 gm After Cont + rock wt. 971.34 gm rock wt. 614.20 gm

Id3 91.53 % type 2

4th cycle Before Cont + rock wt. 949.96 gm After Cont + rock wt. 938.73 gm rock wt. 581.59 gm

Id4 86.67 % type 2

5th cycle Before Cont + rock wt. 919.06 gm After Cont + rock wt. 908.12 gm rock wt. 550.98 gm

Id5 82.11 % type 2

Sample no 145 Container wt. 355.47 gm Container no 145 Before Cont + rock wt. 1109.96 gm rock wt. 754.49 gm After Cont + rock wt. 1086.90 gm rock wt. 731.43 gm Moisture content 3.15 % 1st cycle Before Cont + rock wt. 1083.33 gm After Cont + rock wt. 1070.94 gm rock wt. 715.47 gm

Id1 97.82 % type 1

2nd cycle Before Cont + rock wt. 1028.41 gm After Cont + rock wt. 1018.30 gm rock wt. 662.83 gm

Id2 90.62 % type 2

3rd cycle Before Cont + rock wt. 984.82 gm After Cont + rock wt. 974.99 gm rock wt. 619.52 gm

Id3 84.70 % type 2

4th cycle Before Cont + rock wt. 944.30 gm After Cont + rock wt. 934.35 gm rock wt. 578.88 gm

Id4 79.14 % type 2

5th cycle Before Cont + rock wt. 901.30 gm After Cont + rock wt. 891.64 gm rock wt. 536.17 gm

Id5 73.30 % type 2 Sample no 146 Container wt. 548.51 gm Container no 146 Before Cont + rock wt. 1390.50 gm rock wt. 841.99 gm After Cont + rock wt. 1365.77 gm rock wt. 817.26 gm Moisture content 3.02 % 1st cycle Before Cont + rock wt. 1365.96 gm After Cont + rock wt. 1353.30 gm rock wt. 804.79 gm

Id1 98.47 % type 1

2nd cycle Before Cont + rock wt. 1337.78 gm After Cont + rock wt. 1324.39 gm rock wt. 775.88 gm

Id2 94.94 % type 2

3rd cycle Before Cont + rock wt. 1307.00 gm After Cont + rock wt. 1294.30 gm rock wt. 745.79 gm

Id3 91.25 % type 2

4th cycle Before Cont + rock wt. 1277.67 gm After Cont + rock wt. 1265.05 gm rock wt. 716.54 gm

Id4 87.68 % type 2

5th cycle Before Cont + rock wt. 1255.52 gm After Cont + rock wt. 1243.53 gm rock wt. 695.02 gm

Id5 85.04 % type 2

Sample no 203 Container wt. 371.27 gm Container no 203 Before Cont + rock wt. 832.34 gm rock wt. 461.07 gm After Cont + rock wt. 819.29 gm rock wt. 448.02 gm Moisture content 2.91 % 1st cycle Before Cont + rock wt. - gm After Cont + rock wt. 673.89 gm rock wt. 302.62 gm

Id1 67.55 % type 2

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 407.58 gm rock wt. 36.31 gm

Id2 8.10 % type 2

3rd cycle Before Cont + rock wt. - gm After Cont + rock wt. - gm rock wt. - gm

Id3 - % type -

4th cycle Before Cont + rock wt. - gm After Cont + rock wt. - gm rock wt. - gm

Id4 - % type -

5th cycle Before Cont + rock wt. - gm After Cont + rock wt. - gm rock wt. - gm

Id5 - % type - Sample no 205 Container wt. 371.23 gm Container no 205 Before Cont + rock wt. 993.35 gm rock wt. 622.12 gm After Cont + rock wt. 981.95 gm rock wt. 610.72 gm Moisture content 1.87 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 973.60 gm rock wt. 602.37 gm

Id1 98.63 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 966.00 gm rock wt. 594.77 gm

Id2 97.39 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 959.35 gm rock wt. 588.12 gm

Id3 96.30 % type 1

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 953.30 gm rock wt. 582.07 gm

Id4 95.31 % type 1

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 946.55 gm rock wt. 575.32 gm

Id5 94.20 % type 1

Sample no 211 Container wt. 374.05 gm Container no 211 Before Cont + rock wt. 1035.80 gm rock wt. 661.75 gm After Cont + rock wt. 1016.80 gm rock wt. 642.75 gm Moisture content 2.96 % 1st cycle Before Cont + rock wt. 991.34 gm After Cont + rock wt. 972.58 gm rock wt. 598.53 gm

Id1 93.12 % type 2

2nd cycle Before Cont + rock wt. 814.83 gm After Cont + rock wt. 798.32 gm rock wt. 424.27 gm

Id2 66.01 % type 2

3rd cycle Before Cont + rock wt. 659.57 gm After Cont + rock wt. 649.68 gm rock wt. 275.63 gm

Id3 42.88 % type 2

4th cycle Before Cont + rock wt. 588.58 gm After Cont + rock wt. 579.50 gm rock wt. 205.45 gm

Id4 31.96 % type 2

5th cycle Before Cont + rock wt. 531.19 gm After Cont + rock wt. 525.65 gm rock wt. 151.6 gm

Id5 23.59 % type 2 Sample no 212 Container wt. 326.10 gm Container no 212 Before Cont + rock wt. 861.48 gm rock wt. 535.38 gm After Cont + rock wt. 845.80 gm rock wt. 519.70 gm Moisture content 3.02 % 1st cycle Before Cont + rock wt. 784.75 gm After Cont + rock wt. 760.65 gm rock wt. 434.55 gm

Id1 83.62 % type 2

2nd cycle Before Cont + rock wt. 529.48 gm After Cont + rock wt. 514.62 gm rock wt. 188.52 gm

Id2 36.27 % type 3

3rd cycle Before Cont + rock wt. 383.16 gm After Cont + rock wt. 377.22 gm rock wt. 51.12 gm

Id3 9.84 % type 3

4th cycle Before Cont + rock wt. 351.31 gm After Cont + rock wt. 348.63 gm rock wt. 22.53 gm

Id4 4.34 % type 4.34

5th cycle Before Cont + rock wt. 341.56 gm After Cont + rock wt. 339.12 gm rock wt. 13.02 gm

Id5 2.50 % type 3

Sample no 213 Container wt. 357.74 gm Container no 213 Before Cont + rock wt. 868.83 gm rock wt. 511.09 gm After Cont + rock wt. 854.50 gm rock wt. 496.76 gm Moisture content 2.88 % 1st cycle Before Cont + rock wt. 845.13 gm After Cont + rock wt. 836.79 gm rock wt. 479.05 gm

Id1 96.43 % type 1

2nd cycle Before Cont + rock wt. 807.08 gm After Cont + rock wt. 799.47 gm rock wt. 441.73 gm

Id2 88.92 % type 2

3rd cycle Before Cont + rock wt. 778.29 gm After Cont + rock wt. 771.45 gm rock wt. 413.71 gm

Id3 83.28 % type 2

4th cycle Before Cont + rock wt. 748.76 gm After Cont + rock wt. 741.45 gm rock wt. 383.71 gm

Id4 77.24 % type 2

5th cycle Before Cont + rock wt. 725.53 gm After Cont + rock wt. 718.54 gm rock wt. 360.80 gm

Id5 72.63 % type 2 Sample no 214 Container wt. 371.94 gm Container no 214 Before Cont + rock wt. 920.31 gm rock wt. 548.37 gm After Cont + rock wt. 901.88 gm rock wt. 529.94 gm Moisture content 3.48 % 1st cycle Before Cont + rock wt. 845.86 gm After Cont + rock wt. 822.47 gm rock wt. 450.53 gm

Id1 85.02 % type 2

2nd cycle Before Cont + rock wt. 535.95 gm After Cont + rock wt. 519.59 gm rock wt. 147.65 gm

Id2 27.86 % type 3

3rd cycle Before Cont + rock wt. 393.63 gm After Cont + rock wt. 389.87 gm rock wt. 17.93 gm

Id3 3.38 % type 3

4th cycle Before Cont + rock wt. 374.02 gm After Cont + rock wt. 372.63 gm rock wt. 0.69 gm

Id4 0.13 % type 3

5th cycle Before Cont + rock wt. 372.49 gm After Cont + rock wt. 372.28 gm rock wt. 0.34 gm

Id5 0.06 % type 3

Sample no 215 Container wt. 356.25 gm Container no 215 Before Cont + rock wt. 912.59 gm rock wt. 556.34 gm After Cont + rock wt. 894.74 gm rock wt. 538.49 gm Moisture content 3.31 % 1st cycle Before Cont + rock wt. 850.54 gm After Cont + rock wt. 828.37 gm rock wt. 472.12 gm

Id1 87.67 % type 2

2nd cycle Before Cont + rock wt. 595.37 gm After Cont + rock wt. 577.94 gm rock wt. 221.69 gm

Id2 41.17 % type 3

3rd cycle Before Cont + rock wt. 417.50 gm After Cont + rock wt. 413.39 gm rock wt. 57.14 gm

Id3 10.61 % type 3

4th cycle Before Cont + rock wt. 401.82 gm After Cont + rock wt. 400.09 gm rock wt. 43.84 gm

Id4 8.14 % type 3

5th cycle Before Cont + rock wt. 400.75 gm After Cont + rock wt. 399.12 gm rock wt. 42.87 gm

Id5 7.96 % type 3 Sample no 216 Container wt. 361.52 gm Container no 216 Before Cont + rock wt. 952.99 gm rock wt. 591.47 gm After Cont + rock wt. 935.17 gm rock wt. 573.65 gm Moisture content 3.11 % 1st cycle Before Cont + rock wt. 923.27 gm After Cont + rock wt. 909.87 gm rock wt. 548.35 gm

Id1 95.59 % type 2

2nd cycle Before Cont + rock wt. 848.92 gm After Cont + rock wt. 836.00 gm rock wt. 474.48 gm

Id2 82.71 % type 2

3rd cycle Before Cont + rock wt. 766.11 gm After Cont + rock wt. 756.08 gm rock wt. 394.56 gm

Id3 68.78 % type 2

4th cycle Before Cont + rock wt. 696.82 gm After Cont + rock wt. 688.13 gm rock wt. 326.61 gm

Id4 56.94 % type 2

5th cycle Before Cont + rock wt. 656.96 gm After Cont + rock wt. 649.10 gm rock wt. 287.58 gm

Id5 50.13 % type 2

Sample no 217 Container wt. 334.03 gm Container no 217 Before Cont + rock wt. 921.42 gm rock wt. 587.39 gm After Cont + rock wt. 903.85 gm rock wt. 569.82 gm Moisture content 3.08 % 1st cycle Before Cont + rock wt. 898.24 gm After Cont + rock wt. 880.69 gm rock wt. 546.66 gm

Id1 95.94 % type 2

2nd cycle Before Cont + rock wt. 777.81 gm After Cont + rock wt. 765.65 gm rock wt. 431.62 gm

Id2 75.75 % type 2

3rd cycle Before Cont + rock wt. 714.60 gm After Cont + rock wt. 705.73 gm rock wt. 371.70 gm

Id3 65.23 % type 2

4th cycle Before Cont + rock wt. 677.62 gm After Cont + rock wt. 670.05 gm rock wt. 336.02 gm

Id4 58.97 % type 2

5th cycle Before Cont + rock wt. 655.22 gm After Cont + rock wt. 649.26 gm rock wt. 315.23 gm

Id5 55.32 % type 2 Sample no 310 Container wt. 334.02 gm Container no 310 Before Cont + rock wt. 919.34 gm rock wt. 585.32 gm After Cont + rock wt. 896.04 gm rock wt. 562.02 gm Moisture content 4.14 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 352.47 gm rock wt. 18.45 gm

Id1 3.28 % type 3

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id2 % type

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id3 % type

4th cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id4 % type

5th cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id5 % type

Sample no 311 Container wt. 361.53 gm Container no 311 Before Cont + rock wt. 989.29 gm rock wt. 627.76 gm After Cont + rock wt. 969.87 gm rock wt. 608.34 gm Moisture content 3.19 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 444.78 gm rock wt. 83.25 gm

Id1 13.68 % type 3

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id2 % type

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id3 % type

4th cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id4 % type

5th cycle Before Cont + rock wt. gm After Cont + rock wt. gm rock wt. gm

Id5 % type Sample no 312 Container wt. 297.56 gm Container no 312 Before Cont + rock wt. 875.59 gm rock wt. 578.03 gm After Cont + rock wt. 857.32 gm rock wt. 559.76 gm Moisture content 3.26 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 748.05 gm rock wt. 450.49 gm

Id1 80.48 % type 2

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 466.34 gm rock wt. 168.78 gm

Id2 30.15 % type 3

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 332.50 gm rock wt. 34.94 gm

Id3 6.24 % type 3

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 301.42 gm rock wt. 3.86 gm

Id4 0.69 % type 3

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 299.82 gm rock wt. 2.26 gm

Id5 0.40 % type 3

Sample no 313 Container wt. 557.61 gm Container no 313 Before Cont + rock wt. 1223.73 gm rock wt. 666.12 gm After Cont + rock wt. 1203.73 gm rock wt. 646.12 gm Moisture content 3.10 % 1st cycle Before Cont + rock wt. 1128.86 gm After Cont + rock wt. 1098.51 gm rock wt. 540.90 gm

Id1 83.72 % type 2

2nd cycle Before Cont + rock wt. 787.29 gm After Cont + rock wt. 769.01 gm rock wt. 211.4 gm

Id2 32.72 % type 2

3rd cycle Before Cont + rock wt. 605.78 gm After Cont + rock wt. 598.53 gm rock wt. 40.92 gm

Id3 6.33 % type 3

4th cycle Before Cont + rock wt. 566.41 gm After Cont + rock wt. 564.17 gm rock wt. 6.56 gm

Id4 1.02 % type 3

5th cycle Before Cont + rock wt. 560.01 gm After Cont + rock wt. 559.18 gm rock wt. 1.57 gm

Id5 0.24 % type 3 Sample no 409 Container wt. 297.60 gm Container no 409 Before Cont + rock wt. 713.64 gm rock wt. 416.04 gm After Cont + rock wt. 704.58 gm rock wt. 406.98 gm Moisture content 2.23 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 690.66 gm rock wt. 393.06 gm

Id1 96.58 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 653.20 gm rock wt. 355.6 gm

Id2 87.38 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 615.52 gm rock wt. 317.92 gm

Id3 78.12 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 592.86 gm rock wt. 295.26 gm

Id4 72.55 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 578.54 gm rock wt. 280.94 gm

Id5 69.03 % type 2

Sample no 414 Container wt. 355.55 gm Container no 414 Before Cont + rock wt. 933.05 gm rock wt. 577.50 gm After Cont + rock wt. 922.05 gm rock wt. 566.50 gm Moisture content 1.94 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 912.25 gm rock wt. 556.7 gm

Id1 98.27 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 889.90 gm rock wt. 534.35 gm

Id2 94.32 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 874.35 gm rock wt. 518.8 gm

Id3 91.58 % type 1

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 865.35 gm rock wt. 509.80 gm

Id4 89.99 % type 1

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 857.75 gm rock wt. 502.2 gm

Id5 88.65 % type 1 Sample no 501 Container wt. 355.53 gm Container no 501 Before Cont + rock wt. 988.20 gm rock wt. 632.67 gm After Cont + rock wt. 974.95 gm rock wt. 619.42 gm Moisture content 2.14 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 958.65 gm rock wt. 603.12 gm

Id1 97.37 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 845.20 gm rock wt. 489.67 gm

Id2 79.05 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 736.00 gm rock wt. 380.47 gm

Id3 61.42 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 639.86 gm rock wt. 284.33 gm

Id4 45.90 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 584.26 gm rock wt. 228.73 gm

Id5 36.93 % type 2

Sample no 502 Container wt. 326.16 gm Container no 502 Before Cont + rock wt. 980.25 gm rock wt. 654.09 gm After Cont + rock wt. 968.45 gm rock wt. 642.29 gm Moisture content 1.84 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 957.00 gm rock wt. 630.84 gm

Id1 98.22 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 901.90 gm rock wt. 575.74 gm

Id2 89.64 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 822.80 gm rock wt. 496.64 gm

Id3 77.32 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 731.90 gm rock wt. 405.74 gm

Id4 63.17 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 654.32 gm rock wt. 328.16 gm

Id5 51.09 % type 2 Sample no 504 Container wt. 355.64 gm Container no 504 Before Cont + rock wt. 998.45 gm rock wt. 642.81 gm After Cont + rock wt. 989.05 gm rock wt. 633.41 gm Moisture content 1.48 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 981.55 gm rock wt. 625.91 gm

Id1 98.82 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 975.20 gm rock wt. 619.56 gm

Id2 97.81 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 969.80 gm rock wt. 614.16 gm

Id3 96.96 % type 1

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 964.90 gm rock wt. 609.26 gm

Id4 96.19 % type 1

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 960.35 gm rock wt. 604.71 gm

Id5 95.47 % type 1

Sample no 506 Container wt. 374.11 gm Container no 506 Before Cont + rock wt. 1131.35 gm rock wt. 757.24 gm After Cont + rock wt. 1111.40 gm rock wt. 737.29 gm Moisture content 2.70 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 1071.35 gm rock wt. 697.24 gm

Id1 94.57 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 803.00 gm rock wt. 428.89 gm

Id2 58.17 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 490.76 gm rock wt. 116.65 gm

Id3 15.82 % type 3

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 406.88 gm rock wt. 32.77 gm

Id4 4.44 % type 3

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 380.52 gm rock wt. 6.41 gm

Id5 0.87 % type 3 Sample no 508 Container wt. 334.07 gm Container no 508 Before Cont + rock wt. 988.00 gm rock wt. 653.93 gm After Cont + rock wt. 971.50 gm rock wt. 637.43 gm Moisture content 2.59 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 939.90 gm rock wt. 605.83 gm

Id1 95.04 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 789.50 gm rock wt. 455.43 gm

Id2 71.45 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 643.54 gm rock wt. 309.47 gm

Id3 48.55 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 556.46 gm rock wt. 222.39 gm

Id4 34.89 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 505.80 gm rock wt. 171.73 gm

Id5 26.94 % type 2

Sample no 511 Container wt. 374.07 gm Container no 511 Before Cont + rock wt. 1132.40 gm rock wt. 758.33 gm After Cont + rock wt. 1111.10 gm rock wt. 737.03 gm Moisture content 2.89 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 1077.50 gm rock wt. 703.43 gm

Id1 95.44 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 949.90 gm rock wt. 575.83 gm

Id2 78.13 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 820.75 gm rock wt. 446.68 gm

Id3 60.60 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 718.42 gm rock wt. 344.35 gm

Id4 46.72 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 611.64 gm rock wt. 237.57 gm

Id5 32.23 % type 2 Sample no 512 Container wt. 371.30 gm Container no 512 Before Cont + rock wt. 1113.65 gm rock wt. 742.35 gm After Cont + rock wt. 1092.00 gm rock wt. 720.70 gm Moisture content 3.00 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 1079.50 gm rock wt. 708.20 gm

Id1 98.26 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 1007.00 gm rock wt. 635.70 gm

Id2 88.20 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 908.95 gm rock wt. 537.65 gm

Id3 74.60 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 830.50 gm rock wt. 459.20 gm

Id4 63.72 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 770.64 gm rock wt. 399.34 gm

Id5 55.41 % type 2

Sample no 513 Container wt. 374.07 gm Container no 513 Before Cont + rock wt. 995.05 gm rock wt. 620.98 gm After Cont + rock wt. 978.95 gm rock wt. 604.88 gm Moisture content 2.66 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 948.00 gm rock wt. 573.93 gm

Id1 94.88 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 830.70 gm rock wt. 456.63 gm

Id2 75.49 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 713.52 gm rock wt. 339.45 gm

Id3 56.12 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 613.13 gm rock wt. 239.06 gm

Id4 39.52 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 575.72 gm rock wt. 201.65 gm

Id5 33.34 % type 2 Sample no 602 Container wt. 355.49 gm Container no 602 Before Cont + rock wt. 963.01 gm rock wt. 607.52 gm After Cont + rock wt. 949.59 gm rock wt. 594.10 gm Moisture content 2.26 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 917.00 gm rock wt. 561.51 gm

Id1 94.51 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 781.44 gm rock wt. 425.95 gm

Id2 71.70 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 622.44 gm rock wt. 266.95 gm

Id3 44.93 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 514.48 gm rock wt. 158.99 gm

Id4 26.76 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 450.58 gm rock wt. 95.09 gm

Id5 16.00 % type 2

Sample no 605 Container wt. 357.17 gm Container no 605 Before Cont + rock wt. 1099.30 gm rock wt. 742.13 gm After Cont + rock wt. 1084.10 gm rock wt. 726.93 gm Moisture content 2.09 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 1069.70 gm rock wt. 712.53 gm

Id1 98.02 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 955.40 gm rock wt. 598.23 gm

Id2 82.30 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 829.00 gm rock wt. 471.83 gm

Id3 64.91 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 712.60 gm rock wt. 355.43 gm

Id4 48.89 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 636.06 gm rock wt. 278.89 gm

Id5 38.36 % type 2 Sample no 606 Container wt. 297.58 gm Container no 606 Before Cont + rock wt. 1141.75 gm rock wt. 844.17 gm After Cont + rock wt. 1126.35 gm rock wt. 828.77 gm Moisture content 1.86 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 1116.45 gm rock wt. 818.87 gm

Id1 98.80 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 1073.25 gm rock wt. 775.67 gm

Id2 93.59 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 1011.30 gm rock wt. 713.72 gm

Id3 86.12 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 933.80 gm rock wt. 636.22 gm

Id4 76.77 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 859.30 gm rock wt. 561.72 gm

Id5 67.78 % type 2

Sample no 607 Container wt. 374.00 gm Container no 607 Before Cont + rock wt. 1049.12 gm rock wt. 675.12 gm After Cont + rock wt. 1033.04 gm rock wt. 659.04 gm Moisture content 2.44 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 985.80 gm rock wt. 611.80 gm

Id1 92.83 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 790.78 gm rock wt. 416.78 gm

Id2 63.24 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 680.66 gm rock wt. 306.66 gm

Id3 46.53 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 594.16 gm rock wt. 220.16 gm

Id4 33.41 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 537.82 gm rock wt. 163.82 gm

Id5 24.86 % type 2 Sample no 608 Container wt. 371.79 gm Container no 608 Before Cont + rock wt. 989.09 gm rock wt. 617.30 gm After Cont + rock wt. 976.47 gm rock wt. 604.68 gm Moisture content 2.09 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 968.25 gm rock wt. 596.46 gm

Id1 98.64 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 962.35 gm rock wt. 590.56 gm

Id2 97.66 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 956.95 gm rock wt. 585.16 gm

Id3 96.77 % type 1

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 951.30 gm rock wt. 579.51 gm

Id4 95.84 % type 1

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 945.55 gm rock wt. 573.76 gm

Id5 94.89 % type 1

Sample no 609 Container wt. 357.16 gm Container no 609 Before Cont + rock wt. 1090.32 gm rock wt. 733.16 gm After Cont + rock wt. 1067.58 gm rock wt. 710.42 gm Moisture content 3.20 % 1st cycle Before Cont + rock wt. 949.78 gm After Cont + rock wt. 911.33 gm rock wt. 554.17 gm

Id1 78.00 % type 2

2nd cycle Before Cont + rock wt. 504.86 gm After Cont + rock wt. 491.01 gm rock wt. 133.85 gm

Id2 18.84 % type 3

3rd cycle Before Cont + rock wt. 403.92 gm After Cont + rock wt. 398.84 gm rock wt. 41.68 gm

Id3 5.87 % type 3

4th cycle Before Cont + rock wt. 375.24 gm After Cont + rock wt. 372.84 gm rock wt. 15.68 gm

Id4 2.21 % type 3

5th cycle Before Cont + rock wt. 366.38 gm After Cont + rock wt. 364.40 gm rock wt. 7.24 gm

Id5 1.02 % type 3 Sample no 612 Container wt. 297.57 gm Container no 612 Before Cont + rock wt. 865.99 gm rock wt. 568.42 gm After Cont + rock wt. 854.13 gm rock wt. 556.56 gm Moisture content 2.13 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 844.95 gm rock wt. 547.38 gm

Id1 98.35 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 839.65 gm rock wt. 542.08 gm

Id2 97.39 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 836.85 gm rock wt. 539.28 gm

Id3 96.89 % type 1

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 830.85 gm rock wt. 533.28 gm

Id4 95.82 % type 1

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 826.70 gm rock wt. 529.13 gm

Id5 95.07 % type 1

Sample no 613 Container wt. 361.69 gm Container no 613 Before Cont + rock wt. 997.55 gm rock wt. 635.86 gm After Cont + rock wt. 981.40 gm rock wt. 619.71 gm Moisture content 2.61 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 964.65 gm rock wt. 602.96 gm

Id1 97.30 % type 2

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 788.50 gm rock wt. 426.81 gm

Id2 68.87 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 614.40 gm rock wt. 252.71 gm

Id3 40.78 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 510.42 gm rock wt. 148.73 gm

Id4 23.99 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 468.84 gm rock wt. 107.15 gm

Id5 17.29 % type 2 Sample no 615 Container wt. 361.62 gm Container no 615 Before Cont + rock wt. 901.80 gm rock wt. 540.18 gm After Cont + rock wt. 888.20 gm rock wt. 526.58 gm Moisture content 2.58 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 875.35 gm rock wt. 513.73 gm

Id1 97.56 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 847.75 gm rock wt. 486.13 gm

Id2 92.32 % type 1

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 819.25 gm rock wt. 457.63 gm

Id3 86.91 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 794.04 gm rock wt. 432.42 gm

Id4 82.12 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 772.86 gm rock wt. 411.24 gm

Id5 78.10 % type 2

Sample no 701 Container wt. 371.25 gm Container no 701 Before Cont + rock wt. 1034.45 gm rock wt. 663.20 gm After Cont + rock wt. 1016.75 gm rock wt. 645.50 gm Moisture content 2.74 % 1st cycle Before Cont + rock wt. 1006.85 gm After Cont + rock wt. 985.85 gm rock wt. 614.60 gm

Id1 95.21 % type 2

2nd cycle Before Cont + rock wt. 756.68 gm After Cont + rock wt. 735.50 gm rock wt. 364.25 gm

Id2 56.43 % type 2

3rd cycle Before Cont + rock wt. 550.08 gm After Cont + rock wt. 537.26 gm rock wt. 166.01 gm

Id3 25.72 % type 3

4th cycle Before Cont + rock wt. 461.14 gm After Cont + rock wt. 453.00 gm rock wt. 81.75 gm

Id4 12.66 % type 3

5th cycle Before Cont + rock wt. 424.68 gm After Cont + rock wt. 420.44 gm rock wt. 49.19 gm

Id5 7.62 % type 3 Sample no 702 Container wt. 357.21 gm Container no 702 Before Cont + rock wt. 880.55 gm rock wt. 523.34 gm After Cont + rock wt. 869.40 gm rock wt. 512.19 gm Moisture content 2.18 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 859.85 gm rock wt. 502.64 gm

Id1 98.14 % type 1

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 827.35 gm rock wt. 470.14 gm

Id2 91.79 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 787.40 gm rock wt. 430.19 gm

Id3 83.99 % type 2

4th cycle Before Cont + rock wt. gm After Cont + rock wt. 765.54 gm rock wt. 408.33 gm

Id4 79.72 % type 2

5th cycle Before Cont + rock wt. gm After Cont + rock wt. 755.22 gm rock wt. 398.01 gm

Id5 77.71 % type 2

Sample no 703 Container wt. 371.25 gm Container no 703 Before Cont + rock wt. 967.55 gm rock wt. 596.30 gm After Cont + rock wt. 951.50 gm rock wt. 580.25 gm Moisture content 2.77 % 1st cycle Before Cont + rock wt. 948.37 gm After Cont + rock wt. 939.58 gm rock wt. 568.33 gm

Id1 97.94 % type 1

2nd cycle Before Cont + rock wt. 911.84 gm After Cont + rock wt. 900.45 gm rock wt. 529.20 gm

Id2 91.20 % type 1

3rd cycle Before Cont + rock wt. 852.70 gm After Cont + rock wt. 842.18 gm rock wt. 470.93 gm

Id3 81.16 % type 2

4th cycle Before Cont + rock wt. 809.10 gm After Cont + rock wt. 800.80 gm rock wt. 429.55 gm

Id4 74.03 % type 2

5th cycle Before Cont + rock wt. 777.84 gm After Cont + rock wt. 770.00 gm rock wt. 398.75 gm

Id5 68.72 % type 2 Sample no 704 Container wt. 374.09 gm Container no 704 Before Cont + rock wt. 991.95 gm rock wt. 617.86 gm After Cont + rock wt. 977.20 gm rock wt. 603.11 gm Moisture content 2.44 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 957.40 gm rock wt. 583.31 gm

Id1 96.72 % type 2

2nd cycle Before Cont + rock wt. 860.75 gm After Cont + rock wt. 846.20 gm rock wt. 472.11 gm

Id2 78.28 % type 2

3rd cycle Before Cont + rock wt. 774.74 gm After Cont + rock wt. 763.52 gm rock wt. 389.43 gm

Id3 64.57 % type 2

4th cycle Before Cont + rock wt. 724.86 gm After Cont + rock wt. 715.42 gm rock wt. 341.33 gm

Id4 56.59 % type 2

5th cycle Before Cont + rock wt. 694.36 gm After Cont + rock wt. 684.10 gm rock wt. 310.01 gm

Id5 51.40 % type 2

Sample no 705 Container wt. 355.48 gm Container no 705 Before Cont + rock wt. 1092.37 gm rock wt. 736.89 gm After Cont + rock wt. 1072.35 gm rock wt. 716.87 gm Moisture content 2.79 % 1st cycle Before Cont + rock wt. 1070.44 gm After Cont + rock wt. 1058.94 gm rock wt. 703.46 gm

Id1 98.13 % type 1

2nd cycle Before Cont + rock wt. 1028.24 gm After Cont + rock wt. 1012.73 gm rock wt. 657.25 gm

Id2 91.68 % type 2

3rd cycle Before Cont + rock wt. 957.98 gm After Cont + rock wt. 942.83 gm rock wt. 587.35 gm

Id3 81.93 % type 2

4th cycle Before Cont + rock wt. 903.00 gm After Cont + rock wt. 888.68 gm rock wt. 533.20 gm

Id4 74.38 % type 2

5th cycle Before Cont + rock wt. 849.97 gm After Cont + rock wt. 839.04 gm rock wt. 483.56 gm

Id5 67.45 % type 2 Sample no 706 Container wt. 361.67 gm Container no 706 Before Cont + rock wt. 911.30 gm rock wt. 549.63 gm After Cont + rock wt. 898.50 gm rock wt. 536.83 gm Moisture content 2.38 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 889.55 gm rock wt. 527.88 gm

Id1 98.33 % type 1

2nd cycle Before Cont + rock wt. 889.80 gm After Cont + rock wt. 882.55 gm rock wt. 520.88 gm

Id2 97.03 % type 1

3rd cycle Before Cont + rock wt. 884.40 gm After Cont + rock wt. 875.95 gm rock wt. 514.28 gm

Id3 95.80 % type 1

4th cycle Before Cont + rock wt. 876.60 gm After Cont + rock wt. 869.65 gm rock wt. 507.98 gm

Id4 94.62 % type 1

5th cycle Before Cont + rock wt. 870.45 gm After Cont + rock wt. 864.15 gm rock wt. 502.48 gm

Id5 93.60 % type 1

Sample no 708 Container wt. 355.55 gm Container no 708 Before Cont + rock wt. 951.20 gm rock wt. 595.65 gm After Cont + rock wt. 935.55 gm rock wt. 580.00 gm Moisture content 2.70 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 918.15 gm rock wt. 562.60 gm

Id1 97.00 % type 2

2nd cycle Before Cont + rock wt. 821.15 gm After Cont + rock wt. 801.75 gm rock wt. 446.2 gm

Id2 76.93 % type 2

3rd cycle Before Cont + rock wt. 652.54 gm After Cont + rock wt. 635.52 gm rock wt. 279.97 gm

Id3 48.27 % type 2

4th cycle Before Cont + rock wt. 536.32 gm After Cont + rock wt. 522.80 gm rock wt. 167.25 gm

Id4 28.84 % type 3

5th cycle Before Cont + rock wt. 460.82 gm After Cont + rock wt. 451.86 gm rock wt. 96.31 gm

Id5 16.60 % type 3 Sample no 801 Container wt. 297.60 gm Container no 801 Before Cont + rock wt. 761.04 gm rock wt. 463.44 gm After Cont + rock wt. 752.26 gm rock wt. 454.66 gm Moisture content 1.93 % 1st cycle Before Cont + rock wt. 735.70 gm After Cont + rock wt. 724.46 gm rock wt. 426.86 gm

Id1 93.88 % type 1

2nd cycle Before Cont + rock wt. 693.40 gm After Cont + rock wt. 684.66 gm rock wt. 387.06 gm

Id2 85.13 % type 2

3rd cycle Before Cont + rock wt. 673.48 gm After Cont + rock wt. 665.06 gm rock wt. 367.46 gm

Id3 80.82 % type 2

4th cycle Before Cont + rock wt. 658.00 gm After Cont + rock wt. 650.22 gm rock wt. 352.62 gm

Id4 77.56 % type 2

5th cycle Before Cont + rock wt. 643.18 gm After Cont + rock wt. 635.14 gm rock wt. 337.54 gm

Id5 74.24 % type 2

Sample no 809 Container wt. 357.17 gm Container no 809 Before Cont + rock wt. 921.05 gm rock wt. 563.88 gm After Cont + rock wt. 909.85 gm rock wt. 552.68 gm Moisture content 2.03 % 1st cycle Before Cont + rock wt. 911.60 gm After Cont + rock wt. 902.75 gm rock wt. 545.58 gm

Id1 98.72 % type 1

2nd cycle Before Cont + rock wt. 903.65 gm After Cont + rock wt. 896.85 gm rock wt. 539.68 gm

Id2 97.65 % type 1

3rd cycle Before Cont + rock wt. 898.15 gm After Cont + rock wt. 891.00 gm rock wt. 533.83 gm

Id3 96.59 % type 1

4th cycle Before Cont + rock wt. 892.65 gm After Cont + rock wt. 886.55 gm rock wt. 529.38 gm

Id4 95.78 % type 1

5th cycle Before Cont + rock wt. 888.90 gm After Cont + rock wt. 882.50 gm rock wt. 525.33 gm

Id5 95.05 % type 1 Sample no 815 Container wt. 334.09 gm Container no 815 Before Cont + rock wt. 808.35 gm rock wt. 474.26 gm After Cont + rock wt. 799.86 gm rock wt. 465.77 gm Moisture content 1.82 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 794.14 gm rock wt. 460.05 gm

Id1 98.77 % type 1

2nd cycle Before Cont + rock wt. 795.92 gm After Cont + rock wt. 790.08 gm rock wt. 455.99 gm

Id2 97.90 % type 1

3rd cycle Before Cont + rock wt. 792.28 gm After Cont + rock wt. 787.06 gm rock wt. 452.97 gm

Id3 97.25 % type 1

4th cycle Before Cont + rock wt. 787.68 gm After Cont + rock wt. 783.90 gm rock wt. 449.81 gm

Id4 96.57 % type 1

5th cycle Before Cont + rock wt. 785.42 gm After Cont + rock wt. 780.88 gm rock wt. 446.79 gm

Id5 95.92 % type 1

Sample no 820 Container wt. 326.16 gm Container no 820 Before Cont + rock wt. 815.50 gm rock wt. 489.34 gm After Cont + rock wt. 806.45 gm rock wt. 480.29 gm Moisture content 1.88 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 798.76 gm rock wt. 472.60 gm

Id1 98.40 % type 1

2nd cycle Before Cont + rock wt. 797.76 gm After Cont + rock wt. 792.50 gm rock wt. 466.34 gm

Id2 97.10 % type 1

3rd cycle Before Cont + rock wt. 792.92 gm After Cont + rock wt. 788.10 gm rock wt. 461.94 gm

Id3 96.18 % type 1

4th cycle Before Cont + rock wt. 788.84 gm After Cont + rock wt. 784.02 gm rock wt. 457.86 gm

Id4 95.33 % type 1

5th cycle Before Cont + rock wt. 785.50 gm After Cont + rock wt. 780.38 gm rock wt. 454.22 gm

Id5 94.57 % type 1 Sample no O3R Container wt. 371.63 gm Container no O3R Before Cont + rock wt. 827.35 gm rock wt. 455.72 gm After Cont + rock wt. 815.00 gm rock wt. 443.37 gm Moisture content 2.78 % 1st cycle Before Cont + rock wt. gm After Cont + rock wt. 758.40 gm rock wt. 386.77 gm

Id1 87.23 % type 2

2nd cycle Before Cont + rock wt. gm After Cont + rock wt. 634.04 gm rock wt. 262.41 gm

Id2 59.18 % type 2

3rd cycle Before Cont + rock wt. gm After Cont + rock wt. 538.02 gm rock wt. 166.39 gm

Id3 37.53 % type 2

4th cycle Before Cont + rock wt. 496.02 gm After Cont + rock wt. 486.38 gm rock wt. 114.75 gm

Id4 25.88 % type 2

5th cycle Before Cont + rock wt. 461.14 gm After Cont + rock wt. 453.18 gm rock wt. 81.55 gm

Id5 18.39 % type 2