FERROUS FRICTION STIR WELD PHYSICAL SIMULATION
A Dissertation
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By Seth Jason Norton, M.S. ******** The Ohio State University 2006
Dissertation Committee: Approved by
Dr. John Lippold, Adviser Dr. David Dickinson Adviser Dr. Charles Albright Welding Engineering Graduate Program
ii
ABSTRACT
Traditional fusion welding processes have several drawbacks associated with the melting and solidification of metal. Weld defects associated with the solidification of molten metal may act as initiation sites for cracks. Segregation of alloying elements during solidification may cause local changes in resistance to corrosion. The high amount of heat required to produce the molten metal in the weld can produce distortion from the intended position on cooling. The heat from the electric arc commonly used to melt metal in fusion welds may also produce metal fumes which are a potential health hazard. Friction stir welding is one application which has the potential to make full thickness welds in a single pass, while eliminating fume, reducing distortion, and eliminating solidification defects. Currently the friction stir welding process is used in the aerospace industry on aluminum alloys. Interest in the process by industries which rely on iron and its alloys for structural material is increasing. While friction stir welding has been shown to be feasible with iron alloys, the understanding of friction stir welding process effects on these materials is in its infancy. This project was aimed to better that understanding by developing a procedure for physical simulation of friction stir welding. Friction stir weld material tracer experiments utilizing stainless steel markers were conducted with plates of ingot iron and HSLA-65. Markers of 0.0625” diameter 308 stainless steel worked well for tracing the end position of material moved by the friction stir welding tool. The markers did not produce measurable increases in the loading of the tool in the direction of travel. Markers composed of 0.25” diameter 304 stainless steel did not perform as well as the smaller markers and produced increased loads on the friction stir welding tool. The smaller markers showed that material is moved in a curved path
ii around the tool and deposited behind the tool. Material near the surface is moved a greater distance as it is acted upon by the tool shoulder. A friction stir weld was made on a plate of HSLA-65 which had 0.0625” Inconel sheathed thermocouples embedded in the tool path at seven positions. Thermocouples on the top of the plate acquired data at the desired position until encountering the shoulder, at which point they were sheared by the shoulder and stirred behind the tool. Thermocouples on the bottom of the plate were deformed a relatively small amount and acquired data throughout the welding process. Heating rates calculated from the slope of the acquired temperature data show that the peak heating rate (~1100ºC on top and ~500ºC on the bottom) occurs on both the top and bottom of the weld at temperatures between 350ºC and 500ºC. An increase in the heating rate occurring at elevated temperature was associated with the transformation from ferrite to austenite. Comparison of phase transformation data acquired in rapid heating in the Gleeble® suggests that austenite transforms back to ferrite at higher temperatures in the presence of strain than in its absence. Peak temperatures on the top of the plate exceeded 1200ºC and peak temperatures acquired on the bottom exceeded 1000ºC. The heating rate method of data analysis was sensitive enough to pick up variations in the heating rate which occurred at the same frequency as the rotation rate of the tool. Hot torsion tests were conducted on both ingot iron and HSLA-65 samples. An annular sample geometry with internal and external gas quench achieved cooling rates in the hot torsion samples similar to those observed in friction stir welding. Designed experiments with varying test temperatures, number of rotations, and rate of rotation were conducted in both study alloys. A scribed line on the sample surface provided a means of measuring the distribution of strain in the sample gage sections and thermocouples on the non-rotating side of the sample allowed an estimate of the thermal profile at the application of torsion. The combination of these two features provides plots of strain versus temperature at the initiation of torsion. Localization of strain in the intercritical temperature region, measured by this means, was determined to be caused by differences in the activation energy for deformation for ferrite and austenite. Adiabatic heating due to shear strain was shown to be related to the Zener-Holloman parameter. Microstructures iii created in both the ingot iron and HSLA-65 were very similar to those observed in friction stir welds made in the same material. A method to study the effects of rapid heating and cooling along with the application of shear strain at a high rate has been developed for the simulation of friction stir weld structures. The combination of thermal data acquired from friction stir welds and hot torsion testing of the same materials has highlighted the importance of the allotropic phase transformation on material flow and local heating rate. Based on these observations nomenclature which is believed to be more representative of the regions in ferrous friction stir welds has been proposed. The fine grained zone, the intercritical zone, and the recovered zone are suggested as replacements for the stir zone, thermomechanically affected zone, and heat affected zone respectively. The hot torsion test with annular samples and gas quench offers the possibility of estimating the rate of strain at a given temperature. The ability to measure adiabatic heating due to the application of shear strain at high rates will provide data for modeling the generation of heat friction stir welds. With continued work this test will provide valuable information for mathematical modeling of the friction stir welding process. The new method is unfortunately limited by the optical pyrometer which measures temperature at the center of the sample. The range over which the pyrometer accurately reads temperature is higher than the melting temperature for aluminum, which prevents the use of Gleeble® torsion testing with the material most frequently associated with friction stir welding.
iv
DEDICATION
Dedicated to my wife Shiloh and my 4 children: Their love and support make me strive to be a better person.
v
ACKNOWLEDGMENTS
I would like to thank my advisor, John Lippold, for his support, guidance, and encouragement. Should I ever find myself employed in academia, advising students, I hope be able to emulate his style and ethic. I feel truly blessed to have had him as my advisor for the six years I have been at The Ohio State University. I would also like to extend thanks to Dr. Boian Alexandrov, who acted as a sounding board for me, helped with data collection and collaborated on some Gleeble testing. The Edison Welding Institute (Tim Li in particular) is acknowledged for the use of their friction stir welding machine and tools. Thanks to Dr. Bahman Zoofan for sharing his expertise and skill in radiography. The X-ray images of the friction stir welds I gave him are incredible. Dr. Suresh Babu I thank for sharing his seemingly inexhaustible knowledge of Thermocalc and for his inquisitive nature. He seemed to raise more questions than he answered. Dr. Julie Christodoulou from the Office of Naval Research provided the funding for this project, without which this work would never have been completed. I would like to thank Dr. David Dickinson, and Dr. Charlie Albright for serving on my advisory committee and reviewing this manuscript. Valuable data and materials were provided by the Naval Surface Warfare Center Carderock Division. Thanks to Jennifer Nguyen, David Forrest, Maria Posada, and Carrie Davis for providing the HSLA-65 plate and data from their experiments. Dr. Blair London, a professor at the California Polytechnic State University, is acknowledged for his suggestion to use metal sheathed thermocouple wires and his leads in finding a supplier.
vi Cameron Begg, of the Campus Electron Optics Facility, deserves recognition for his help and training in acquiring electron backscatter diffraction patterns in scanning electron microscopes. Thanks to Andy Doorman and Dave Ferguson, of DSI, for answering my many questions on the use of the Hot Torsion MCU and for providing the engineering sketches of the various parts I needed to alter. I am grateful to the entire Materials Joining Metallurgy Group for their help, support, and comments; in particular Melissa Rubal, Joe Walko, and Kenny Izor, the undergraduate students who helped with Thermo-Calc and metallographic sample preparation. I would like to thank Allison Polasik, a graduate student in the Materials Science Engineering department, who volunteered to proof-read portions of my manuscript. I thank Fikry Botros and Jim Ibarra at BP for hiring me and for their patience in allowing me to finish this document before beginning my post-doctoral career. My family deserves recognition for their patience and sacrifice while I worked on this dissertation. It is great to come home to their smiling faces, hugs, and kisses. I love you all and look forward to spending more time with you once this is all over. Finally, I believe none of this would be possible without the inspiration and abilities given me by my creator. I thank God for my inquisitive nature, and the friends and family I have been blessed with.
vii
VITA
November 29, 1974………………………… Born – Sanger, California, U.S.A.
1998…………………………………………B.S. Engineering, LeTourneau University
1998 – 1999...... Researcher/Lab Instructor, LeTourneau University Welding Engineering Dept.
2002…………………………………………M.S. Welding Engineering, The Ohio State University
1999 – present………………………………Graduate Research Associate, The Ohio State University
PUBLICATIONS
1. S.J. Norton, J.C. Lippold, “Development of a Gleeble-based Test for Postweld Heat Treatment Cracking Susceptibility,” Trends in Welding Research, Proc. of the 6th Annual Conference, ASM International, pp 609-614, (2003)
2. B. Alexandrov, N.E. Nissley, S.J. Norton, J.C. Lippold, Q. Lu, “Development of Repair Weldability Test for High Performance Base and Filler Metals,” EWI Cooperative Research Program Summary Report (SR0425), December 2004
3. S.J. Norton, J.C. Lippold, “Simulation of Friction Stir Weld Microstructures in Steel: Preliminary Studies,” Trends in Welding Research, Proc. of the 7th Annual Conference, ASM International, 6 pp., (2005)
FIELDS OF STUDY
Major Field: Welding Engineering Minor Field: Materials Science Engineering viii
TABLE OF CONTENTS
Page
Abstract...... ii
Dedication...... v
Acknowledgments...... vi
Vita………...... viii
List of Tables ...... xv
List of Figures...... xvi
Chapters:
1. Introduction...... 1
2. Background ...... 4 2.1 Metallurgy Principles...... 4 2.1.1 Crystal Structures...... 4 2.1.2 Cubic Crystal Coordinates ...... 6 2.1.2.1 Direction Indices...... 6 2.1.2.2 Plane Indices...... 7 2.1.3 Vacancies and Dislocations ...... 8 2.1.4 Phase Transformations...... 9 2.1.5 Solid State Nucleation...... 10 2.1.6 Annealing...... 11 2.1.6.1 Recovery ...... 11 2.1.6.2 Recrystallization ...... 11 2.1.6.3 Grain Growth ...... 13 2.1.7 Grain Size Effects ...... 14 2.1.7.1 Measuring Grain Size ...... 14 ix 2.1.8 Alloying ...... 15 2.1.8.1 Precipitation...... 15 2.1.8.2 Solid Solution ...... 16 2.2 Steel Metallurgy...... 16 2.2.1 Ferrite...... 17 2.2.2 Austenite ...... 17 2.2.3 Delta Iron ...... 17 2.2.4 Cementite ...... 18 2.2.5 Iron-Carbon Phase Diagram ...... 18 2.2.6 Phase Morphologies...... 20 2.2.6.1 Pearlite ...... 20 2.2.6.2 Bainite...... 21 2.2.6.3 Martensite ...... 21 2.2.6.4 Ferrite Morphologies ...... 21 2.2.7 Alloying Additions...... 24 2.2.7.1 Carbon...... 25 2.2.7.2 Manganese ...... 25 2.2.7.3 Sulfur ...... 25 2.2.7.4 Phosphorus...... 26 2.2.7.5 Silicon ...... 26 2.2.7.6 Copper...... 26 2.2.7.7 Chromium ...... 27 2.2.7.8 Nickel...... 27 2.2.7.9 Molybdenum...... 27 2.2.7.10 Niobium ...... 28 2.2.7.11 Vanadium...... 28 2.2.7.12 Aluminum ...... 28 2.2.8 Calculation of Alloying Effects ...... 29 2.3 Hot Working of Steel ...... 29 2.3.1 Dynamic Annealing ...... 30 2.3.1.1 Luton and Sellars Model...... 31 2.3.1.2 Sakai and Jonas Model ...... 32 2.3.1.3 McQueen’s Model ...... 34 2.3.2 Measuring Critical Strain...... 36 2.3.2 Softening After Dynamic Recrystallization...... 37 2.3.4 Effect of Carbon on Flow Stress...... 41 2.3.4 Phase Stability in High Strain...... 42 2.3.5 Controlled Processing ...... 44
x 2.4 Study Steels...... 44 2.4.1 Armco Ingot Iron ...... 44 2.4.2 HSLA-65...... 45 2.5 The Friction Stir Welding Process...... 46 2.5.1 Terminology...... 47 2.5.2 FSW Characterization...... 48 2.5.2.1 Weld Regions...... 48 2.5.2.2 Flow Visualization...... 49 2.5.3 Modeling of FSW ...... 53 2.5.4 Physical Simulation of FSW...... 54 2.6 The Gleeble...... 55 2.6.1 Gleeble Hot Torsion...... 55 2.7 Single Sensor Differential Thermal Analysis ...... 57 2.8 Electron Backscatter Diffraction Analysis...... 57 2.9 Response Surface Methodology ...... 59 2.9.1 Coded variables...... 59 2.9.2 Types of Experiments ...... 60 2.9.2.1 Central Composite ...... 60 2.9.2.2 Low Cost Response Surface Method...... 61 2.9.3 Determining Significance ...... 62
3. Objectives, Equipment, & Materials...... 64 3.1 Project Objectives ...... 64 3.2 Equipment ...... 64 3.2.1 Friction Stir Welder ...... 65 3.2.2 Gleeble 3800 ...... 66 3.2.3 Electron Microscope ...... 66 3.2.4 Optical Microscopes ...... 66 3.3 Materials ...... 66 3.3.1 Armco Iron...... 67 3.3.2 HSLA-65...... 69
4. Iron Friction Stir Welds ...... 71 4.1 Armco Ingot Iron FSW Procedure...... 71 4.1.1 Process Parameters...... 72 4.1.2 Thermocouple Instrumented Plates...... 72
xi 4.1.3 Marker Embedded Plates ...... 75 4.2 Armco Ingot Iron Friction Stir Weld Results ...... 78 4.2.1 Microstructures ...... 78 4.3.2 Thermal Data ...... 81 4.3.3 Marker Data ...... 83 4.3.4 Electron Backscatter Diffraction Data...... 87
5. HSLA-65 Friction Stir Welds ...... 92 5.1 HSLA-65 FSW Procedure ...... 92 5.1.1 Process Parameters...... 92 5.1.2 Thermocouple Instrumented Plates...... 93 5.1.3 Marker Embedded Plates ...... 96 5.2 HSLA-65 Friction Stir Weld Results...... 99 5.2.1 Microstructures ...... 99 5.2.2 Thermal Data ...... 101 5.2.3 Marker Data ...... 109 5.2.4 Electron Backscatter Diffraction Data...... 114
6. Armco Iron Torsion Experiments ...... 116 6.1 Preliminary Study ...... 116 6.1.1 Experiment Design...... 116 6.1.2 Procedure ...... 116 6.1.3 Results...... 117 6.2 Modification of Hot Torsion Test Procedure...... 119 6.3 Modified Torsion Tests...... 121 6.3.1 Modified Sample – Central Composite...... 122 6.3.1.1 Procedure ...... 122 6.3.1.2 Results...... 122 6.3.2 Modified Sample – LCRSM ...... 125 6.3.2.1 Iron LCRSM Procedure...... 126 6.3.2.2 Iron LCRSM Results ...... 127 6.4 Strain – Temperature Relationships in Iron...... 133 6.4.1 Iron Strain vs. Temperature Procedure ...... 133 6.4.2 Iron Strain vs. Temperature Results...... 135 6.4.2.1 Strain vs. Temperature...... 135 6.4.2.2 Images...... 136 6.4.2.3 Electron Backscatter Diffraction Data...... 143 xii 7. HSLA-65 Torsion Experiments ...... 149 7.1 Modified Hot Torsion Tests...... 149 7.1.1 Hot Torsion Microstructures...... 149 7.1.2 General Procedure...... 152 7.2 H-LCRSM 1 Experiment ...... 153 7.2.1 H-LCRSM 1 Design ...... 153 7.2.2 H-LCRSM 1 Results...... 153 7.3 H-LCRSM 2 Experiment ...... 154 7.3.1 H-LCRSM 2 Design ...... 154 7.3.2 H-LCRSM 2 Results...... 155 7.4 H-LCRSM 3 Experiment ...... 158 7.4.1 H-LCRSM 3 Design ...... 158 7.4.2 H-LCRSM Results...... 158
8. Phase Transformations...... 163 8.1 Calculated Equilibrium Volume Fraction...... 163 8.2 Differential Thermal Analysis ...... 166 8.2.1 Procedure ...... 167 8.2.2 Gleeble Phase Transformation Results ...... 167 8.3 Testing Inconel Sheathed Thermocouple Response ...... 172 8.3.1 Test Procedure ...... 172 8.4 Summary of Phase Transformation Data Processing...... 175
9. Discussion...... 176 9.1 Localized Strain ...... 176 9.1.1 Changes in Iron Flow Stress ...... 177 9.1.2 Localized Strain in Iron Hot Torsion Samples ...... 180 9.2 Heat Generation in Friction Stir Welding...... 184 9.2.1 Heat Generated by the Shoulder ...... 184 9.2.2 Heat Generated in the Shear Zone ...... 185 9.3 Estimation of Strain in HSLA-65 Friction Stir Weld ...... 197 9.4 Grain Size Significance...... 197 9.5 Conceptual Model for Ferrous Friction Stir Welds ...... 198 9.6 Implications of Modified Hot Torsion Testing...... 200
xiii 10. Conclusions...... 202
11. Suggestions for Future Work...... 206
List of References ...... 209
Appendix A – Schematics of Parts and Samples...... 218
Appendix B – List of Equipment and Supplies ...... 225
Appendix C – Experimental Designs...... 227
Appendix D – Psuedo Binary Phase Diagrams...... 231
xiv
LIST OF TABLES
Table Page
2.1 Increase in Recrystallization Temperature of Pure Copper by the Addition of 0.01 Atomic Percent of the Indicated Element...... 13
2.2 A945 Grade 65 chemical specification...... 46
2.3 LCRSM with four factors in scaled (-1,1) units...... 61
3.1 As received properties for irons used in study...... 67
3.2 Chemical composition (wt%) of iron used in study...... 67
3.3 As received properties for HSLA-65 plates used in study...... 69
3.4 Chemical composition (wt%) of HSLA-65 used in study ...... 69
4.1 Weld Schedule development for Armco ingot iron FSW...... 72
5.1 Weld Schedule development for HSLA-65 FSW...... 93
6.1 Strain versus temperature sample designations and test conditions ...... 133
6.2 ASTM grain size measurements for samples with same temperature history and different strain conditions (run 6 – torsion, run 6n – no torsion)...... 142
8.1 Summary of phase change temperature tests for iron rod and 0.25” HSLA- 65 plate (all temperatures ºC)...... 175
9.1 Suggested values for activation energy for self diffusion in iron (from Oikawa [97]) ...... 177
xv
LIST OF FIGURES
Figure Page
2.1 Face-centered cubic unit cell ...... 5
2.2 Body-centered cubic unit cell ...... 6
2.3 Direction indices and the [101] direction in a cubic crystal...... 7
2.4 The intercepts of the (623) plane with the coordinate axes...... 8
2.5 The two basic forms of solid solutions...... 16
2.6 Portion of the Fe-Fe3C phase diagram with A3 and A1 temperatures defined with arrows...... 19
2.7 The Dubé morphological classification system for ferrite as modified by Aaronson...... 23
2.8 Typical high-temperature torsion shear stress-strain curve of a metal that recovers very quickly...... 30
2.9 Predicted stress-strain curves for dynamic recrystallization (a) critical strain to initiate recrystallization, εc > εx, the strain occurring in the time for a large fraction of recrystallization. (b) εc < εx...... 31
2.10 A microstructural mechanism map for distinguishing between the occurrence of two types of dynamic recrystallization...... 33
2.11 The substructure formation (1,2), the formation within a grain (3), and the growth and deformation (4,5) of a dynamic nucleus are shown. During steady-state deformation, nuclei are repeatedly forming from subgrains in different regions (6-9), including those which have previously recrystallized (8)...... 35
2.12 Nucleation during dynamic recrystallization as a result of a migrating boundary...... 36
2.13 Schematic illustration showing the relation between each of the softening stages and restoration processes operating mainly after dynamic recrystallization...... 38 xvi 2.14 Recrystallization by high-angle boundary motion. (A) undeformed structure. (B) the 50% compressed microstructure with a fine substructure. (C) new grain formation. (D) the nearly recrystallized structure...... 40
2.15 Recrystallization by subgrain coarsening. (A) undeformed structure. (B) the 50% compressed microstructure with a developed substructure. (C) coarsening subgrains. (D) fully recrystallized structure, nearly indistinguishable from a structure that recrystallized via high-angle boundary migration...... 41
2.16 Micrograph of ingot iron hot rolled sheet...... 45
2.17 Schematic of “friction stir butt welding” from 1991 TWI patent...... 47
2.18 Plan view of FSW showing accepted terminology...... 48
2.19 Results of radiographic analysis performed by Colligan...... 50
2.20 Schematic of marker placement used by Reynolds et. al...... 51
2.21 London et al method of using lamellae to study material flow (above) and a resulting cross-section showing lamellae interfaces and tool pin...... 53
2.22 EBSD patterns captured from crystals of different orientation in a polycrystalline iron sample...... 58
2.23 Central composite design for k=2 and α=√2...... 60
3.1 EWI Friction Stir Welding Machine #2...... 65
3.2 As received structure of the 14mm iron rod...... 68
3.3 Colony of fine pearlite in 6 inch iron bar stock ...... 68
3.4 Microstructure observed in as received HSLA-65 (0.5” plate shown)...... 70
4.1 Schematic of thermocouple placement on weld Fe-4 (top view) ...... 73
4.2 Schematic of thermocouple placement on weld Fe-6 (bottom view) ...... 74
4.4 Schematic of bottom view of Fe-5 plate prior to welding ...... 77
4.5 Typical stir zone microstructure observed in stir zone of iron welds...... 78
4.6 Mixed ferrite grain size region observed in iron friction stir welds ...... 79
xvii 4.7 Narrow region of subgrain boundary networks in friction stir weld (arrow points along approximate center of region)...... 80
4.8 Magnified view of boxed region in Figure 4.7 showing subgrain boundary region...... 80
4.9 Thermocouple data collected from weld Fe-4 collected at the plate surface outside the tool path...... 81
4.10 Thermocouple data collected from weld Fe-6, where thermocouples were forced out of the plate as the tool approached ...... 82
4.11 Machine data collected from friction stir weld in iron with markers ...... 83
4.12 Machine data collected from friction stir weld made without markers ...... 84
4.13 Section of iron plate near plate surface showing original and final position of 0.0625” markers (advancing side of weld on top)...... 85
4.14 Section of iron plate near bottom of plate showing original and final position of 0.0625” markers (advancing side of weld on top)...... 85
4.15 Plan view of marker material final position with outline of tool path and original position of pin (grey circle) ...... 86
4.16 Transverse section view of final marker position with original position of marker pin and outline of tool profile (weld direction into page)...... 87
4.17 Longitudinal section view of serial section sketches and original pin position from retreating side ...... 87
5.1 Schematic of thermocouple placement on weld HSLA-65-5 (bottom view) ...... 94
5.2 Schematic of top view of plate machined for metal sheathed thermocouples...... 95
5.3 Schematic of bottom view of plate machined for metal sheathed thermocouples...... 96
5.4 Schematic of top view of HSLA-65-4 prior to weld...... 97
5.5 Schematic of top view of HSLA-65-5 prior to weld...... 98
5.6 HSLA-65 stir zone microstructure showing Widmanstätten ferrite microstructure ...... 99
xviii 5.7 Transition from Widmanstätten ferrite in stir zone (left) to fine, equiaxed ferrite (right)...... 100
5.8 Fine grain region seen at edges of stir welds made in HSLA-65...... 100
5.9 Overview of microstructural transitions in HSLA-65 weld (weld at left, retreating side) ...... 101
5.10 Thermocouple data collected from weld HSLA-65-5 just outside tool path...... 102
5.11 Thermocouple data collected from weld HSLA-65-6 ...... 103
5.12 Image of weld HSLA-65-6 top surface after welding through thermocouples showing the rough surface where the thermocouples were stirred into the weld ...... 104
5.13 Radiograph of plate instrumented with sheathed thermocouples after welding...... 105
5.14 Increased magnification of radiograph showing thermocouple channels 3, 4 and 7 in HSLA-65-6 weld...... 105
5.15 Illustration of convention for position of tool geometry features relative to thermocouples in plate ...... 106
5.16 Temperature acquired on bottom of plate at thermocouple channels 1 and 2 plotted against the position of the leading edge of the tool pin relative to the centerline of the thermocouples ...... 107
5.17 Temperature acquired on top of plate at thermocouple channel 5 plotted against the position of the leading edge of the tool shoulder relative to the centerline of the thermocouple...... 108
5.18 Position at which temperature is measured as thermocouple on top surface is acted upon by the tool shoulder...... 109
5.19 Section of HSLA-65 plate near plate surface showing original and final position of 0.0625” markers...... 110
5.20 Section of HSLA-65 plate near bottom of plate showing original and final position of 0.0625” markers...... 111
5.21 Plan view of marker material final position with outline of tool path and original position of marker (grey circle)...... 111
xix 5.22 Transverse section view of final marker position sketches with original position of marker pin and profile of tool outlined (weld direction - into page)...... 112
5.23 Longitudinal section view of serial section sketches and original pin position from retreating side ...... 112
5.24 Machine data collected from friction stir weld in HSLA-65 with markers ...... 113
5.25 Unique grain color EBSD map of transition from rolled plate structure (left) to fine grained ferrite (right) ...... 114
5.26 Grain orientation deviation map of transition region from rolled ferrite and pearlite (left) to fine, equiaxed grains at right...... 115
6.1 As received microstructure of the 14mm iron rod...... 118
6.2 Microstructure of 14mm iron bar after heating to 1200°C and 20 revolutions at 1000 rpm (hardness 106Hv)...... 118
6.3 Modified hot torsion collets for gas quench with sample removed...... 120
6.4 Thermal data acquired from tests to improve cooling rate in the hot torsion test. Standard sample Δt8-5 = 81 seconds. Modified sample with gas quench Δt8-5 = 14 seconds...... 121
6.5 Photomicrograph showing varied microstructure in hot torsion sample heated to 1260ºC, rotated 10 revolutions at 1000 rpm (Simulated SZ to right, base metal at far left)...... 123
6.6 Refined ferrite microstructure near center of hot torsion sample ...... 123
6.7 Mixed ferrite grain size observed in hot torsion sample...... 124
6.8 Beginning of transition from mixed ferrite grain region (right) to subgrain boundary network structure (left) in hot torsion sample...... 124
6.9 Transition from subgrain boundary structure to larger ferrite grains of base metal in hot torsion sample...... 125
6.10 Left side of a hot torsion sample showing scribed line on surface and thermocouples welded at distances of 0.125” and 0.25” from the shoulder...... 126
6.11 Sketch depicting the two types of change in slope observed in the line scribed across the gage section for LCRSM samples. A) Sample with
xx strain concentrated in the center B) Samples with strain concentrated outside the center ...... 128
6.12 Plot of measured and modeled values for the distance to the localized deformed region in iron torsion samples (R2 = 0.92) ...... 129
6.13 Curves fit to acquired thermal data to give average temperature profiles across iron modified hot torsion samples...... 130
6.14 Measured changes in temperature at nominal distances of 0.125”, 0.25”, and 0.5” from the left shoulder of the torsion sample...... 131
6.15 Temperature and torsion for iron LCRSM experiment run 2 at 0.25” from shoulder...... 132
6.16 Picture of the apparatus used to make incremental strain measurements (arrows show rotation and traverse direction) ...... 134
6.17 Strain versus temperature plots for three standard samples tested in torsion ...... 135
6.18 Macroscopic image of polished and etched cross section of standard hot torsion sample heated to 875ºC and rotated 1 revolution at 325 rpm...... 136
6.19 Macroscopic image of polished and etched cross section of standard hot torsion sample heated to 900ºC and rotated 1 revolution at 1000 rpm...... 137
6.20 Macroscopic image of polished and etched cross section of standard hot torsion sample heated to 900ºC but not rotated ...... 138
6.21 Equiaxed ferrite microstructure observed in region of concentrated strain (run 6 sample) ...... 139
6.22 Network of subgrain boundaries seen at boundary between concentrated strain region (out of view at top of image) in hot torsion sample and the axis of the sample (out of view at bottom of image) ...... 139
6.23 Grains with subgrain boundary networks at the boundary between the region of concentrated strain (at right) and the base metal (out of view to left)...... 140
6.24 Bimodal ferrite structure seen at boundary between region of concentrated strain and center of the hot zone in run 6 sample ...... 141
6.25 Ferrite structure found in the center of the hot zone of standard iron torsion sample (run 6, 900ºC test temperature, 1 revolution, 775 rpm)...... 141
xxi 6.26 Ferrite structure found in the center of the hot zone of standard iron torsion sample tested without the application of torsion (run 6n, 900ºC test temperature) ...... 142
6.27 Grain orientation deviation map from standard iron torsion sample (axis of sample at bottom and strain concentrated region at top) ...... 143
6.28 Grain orientation deviation map at center of strain concentration region in iron torsion sample...... 145
6.29 Inverse pole figure map of strain concentration region in iron torsion sample ...... 146
6.30 Pole figure plot for the region mapped in Figures 6.28 and 6.29 ...... 147
6.31 Grain orientation deviation map from deformation concentration area (left) to material which experienced lower peak temperatures and less deformation (right)...... 148
7.1 Photomicrograph showing varied microstructure in HSLA-65 hot torsion sample heated to 1260ºC, rotated 10 revolutions at 1000 rpm (Simulated SZ to left, base metal at far right) ...... 150
7.2 Simulated HSLA-65 stir zone showing Widmanstätten ferrite microstructure ...... 150
7.3 Region of transition from Widmanstätten ferrite in stir zone (left) to fine, equiaxed ferrite (right) ...... 151
7.4 Fine grained region found in deformed region just prior to transition to base metal...... 151
7.5 HSLA-65 base metal microstructure found near the shoulder in preliminary testing of modified hot torsion samples ...... 152
7.6 Shear strain versus temperature plots for three HSLA-65 modified torsion samples from H-LCRSM 1 ...... 154
7.7 Shear strain versus temperature plots for three HSLA-65 modified torsion samples from H-LCRSM 2 ...... 155
7.8 Plot of measured and modeled values for the peak temperature reached during torsion for the H-LCRSM 2 experiment...... 156
7.9 Surface plot of the average calculated rate of heating due to torsion at the center of the hot torsion samples in H-LCRSM 2 (R2 = 0.992)...... 157
xxii 7.10 Shear strain versus temperature plots for all samples run in H-LCRSM 3 experiment...... 159
7.11 Peak and trough seen in strain versus temperature profile for samples heated to 925ºC in H-LCRSM 3 experiment ...... 160
7.12 Measured and modeled peak temperature due to heating caused by torsion...... 161
7.13 Surface plot of the average calculated rate of heating due to torsion at the center of the hot torsion samples in H-LCRSM 3 (R2 = 0.997)...... 162
8.1 Calculated equilibrium volume fraction of bcc and fcc in 14mm iron rod...... 164
8.2 Calculated equilibrium volume fraction of bcc and fcc in 6 inch iron bar ...... 165
8.3 Calculated equilibrium volume fraction of bcc and fcc in ¼” HSLA-65 plate...... 165
8.4 Calculated equilibrium volume fraction of bcc and fcc in ½” HSLA-65 plate...... 166
8.5 Dilatometer results for ~500ºC/s power angle controlled heating of iron rod ...... 168
8.6 Single sensor differential thermal analysis of ~500ºC/s power angle heated iron rod...... 169
8.7 Dilatometer results for ~600ºC/s power angle controlled heating of HSLA- 65 plate...... 170
8.8 Single sensor differential thermal analysis of ~600ºC/s power angle heated HSLA-65 plate...... 171
8.9 Thermal response of sheathed thermocouple held 1” from propane torch ...... 173
8.10 Single sensor differential thermal analysis for an Inconel 600 sheath heated by a propane torch ...... 174
8.11 Another single sensor differential thermal analysis for an Inconel 600 sheath heated by a propane torch...... 174
9.1 Change in volume percent phase averaged Zener-Holloman parameter for iron with 0.029 wt% C at a constant strain rate ...... 178
9.2 Change in the volume percent phase averaged Zener-Holloman parameter for varying strain and temperature...... 179
xxiii 9.3 Plot of the average e(Q/RT) value across the gage section of standard hot torsion samples (Run 5 – 875ºC at center, Run 6 - 900ºC at center) ...... 181
9.4 Conceptual representation of changes caused by torsion of non-uniform temperature sample (Isotherms represented by lines in left column, ferrite represented by white in right column) ...... 183
9.5 Temperature versus heating rate measured at the bottom of the plate during weld HSLA-65-6 ...... 186
9.6 Heating rate plotted as a function of distance from the leading edge of the advancing tool pin on the bottom of the plate in weld HSLA-65-6...... 187
9.7 Temperature versus heating rate measured at the top of the plate during weld HSLA-65-6...... 189
9.8 Heating rate plotted as a function of distance from the leading edge of the advancing tool shoulder on the top of the plate in weld HSLA-65 ...... 190
9.9 Magnified view of the surface of weld HSLA-65-6 showing repeating pattern of ridges ...... 191
9.10 Temperature versus cooling rate measured at the bottom of the plate during weld HSLA-65-6 ...... 193
9.11 Cooling rate plotted as a function of distance from the trailing edge of the advancing tool pin on the bottom of the plate in weld HSLA-65-6...... 194
9.12 Overlaying plots of heating relative to tool position and calculated e(Q/RT) for equilibrium conditions...... 196
9.13 Suggestions for nomenclature of zones in ferrous friction stir welds...... 199
xxiv
CHAPTER 1
INTRODUCTION
Improving efficiency and reducing cost are two of the most important tasks which occupy the time of engineers. In the 1980’s the U.S. Navy undertook a project to replace their high yield series steels (HY-80 and HY-100) with High Strength, Low Alloy (HSLA) plates in an effort to save weight and reduce fabrication costs [1]. The result was the development of HSLA-80 and HSLA-100. Estimates of cost savings from fabrication with HSLA-80 in place of HY-80 from 1984 through 2001 range from $80M to $120M. In the 1990’s another project was launched by the Navy to develop an HSLA steel certified for use in surface combatant structures with yield strength between that of the high strength steel, DH-36, already in use (50ksi) and HSLA-80 (80ksi). That project culminated in the development of HSLA-65. Shipbuilders found that the HSLA-65 could be welded with the same procedure and consumables used for DH-36 [2]. Using HSLA- 65 in place of DH-36 would allow the use of thinner plate and an estimated weight savings of 15 long-tons per aircraft carrier [1]. In an attempt to further reduce cost of fabrication, the Navy is considering friction stir welding as an alternative to fusion welding processes. The friction stir welding (FSW) process is a solid state joining process patented by TWI in 1991 [3]. Initially the process was used for materials with low melting temperatures such as aluminum and copper. Continued research into the FSW process has brought some success in welding “high temperature” materials such as iron, nickel, and titanium alloys.
1 Because it is a solid state process, FSW does not create the fume associated with arc welding processes. Studies by the Navy have shown that the fume created in current shipyard welding practices exceed the proposed Occupational Health and Safety Administration allowable limit for hexavalent chromium (Cr6+), a known carcinogen [4]. The Navy estimated that keeping the Cr6+ under the proposed limits would incur a one- time implementation cost of $30M and annual cost of $80M [4]. Using friction stir welding where possible would eliminate much of the potential fume and cut the costs of controlling Cr6+ generation. The solid state joining offered by the FSW process is also a potential cost saver due to reduced plate distortion. The navy has estimated that the cost of not controlling distortion can reach as high as $3.4M per ship for the DDG-51 class vessel (guided missile destroyer)[4]. The high temperatures of arc welding processes melt the metal being joined and create large thermal gradients. As the weld cools, thermal contraction can cause considerable deformation of the joined plates. FSW, on the other hand, is a solid state process, resulting in lower peak temperatures and reduced distortion. A comparison of the resultant deformation caused by welding plates with submerged arc welding, gas metal arc welding, and FSW showed less distortion in the FSW joined plates [4]. With the potential cost savings of using FSW and HSLA-65 in shipyards, the navy provided funding for several projects. Feasibility studies have shown that HSLA-65 may be joined through FSW with either tungsten based tooling or polycrystalline cubic boron nitride [5-7]. The focus of these studies was to show that HSLA-65 was weldable by the FSW process and that the weld would meet the Navy physical property requirements for HSLA-65. Now that it has been shown to be joinable, the challenge is to understand how the FSW process affects microstructure development in HSLA-65 friction stir welds. One way in which an understanding of the process effects on microstructure might be elicited is through physical simulation. Physical simulation recreates the conditions which formed a given microstructure. The Gleeble® system is a versatile thermo- mechanical simulator which has proven very useful in understanding how changes in temperature and mechanical loads affect the development of microstructures in metals. A 2 hot torsion conversion unit for the Gleeble® has been designed for simulation of rolling mill conditions. Since the FSW joining process has been modeled as a metalworking process [8], this hot torsion unit would seem to be ideal for developing an understanding of the creation of the microstructure in friction stir welds made in steel. Physical simulation offers several potential benefits and cost savings to the implementation of FSW of steels in shipbuilding. Simulations typically use less material to generate a given microstructure. A successful physical simulation provides material for characterization without the time and expense of setting up a FSW machine. Quantifiable data are readily available from the Gleeble® acquisition system, while collecting data such as strain and temperature from a friction stir weld has proven difficult at best. Microstructures with a quantifiable history would aid in the development of mathematical models of FSW HSLA-65 [9]. The repeatability and control offered by the Gleeble® might allow insight into the combined effects of temperature, strain, and strain rate. Finally, an understanding of how FSW process parameters affect microstructure would aid in selecting the correct operating parameters and save the time and material wasted by trial and error parameter setting.
3
CHAPTER 2
BACKGROUND
2.1 Metallurgy Principles
A basic overview of some of the principles of physical metallurgy, especially those relating to iron, will be provided for the uninitiated reader. Those with an understanding of physical metallurgy and steel metallurgy may wish to skip to section 2.5, which covers friction stir welding.
2.1.1 Crystal Structures Most metals form crystals in their solid state. Crystals are composed of three dimensional repetitive patterns of ions, molecules, or atoms. In the case of metals, the patterns are made with atoms. A metallic object consists of a collection of many very small crystals. Observing these crystals, or grains as they are often referred, requires magnification of 100 to 1000 times. Metal features requiring this range of magnification are referred to as microstructures. Using standard preparation procedures these features may be revealed and observed with an optical microscope [10]. Each individual metal grain also has a basic structure, determined by the arrangement of the atoms within the crystal, called the crystal structure. The smallest group of atoms which contain the basic structure of a crystal is called a unit cell. A unit cell, when repeated in all directions will form a crystal lattice. While there are very many crystal structures which appear in nature, each defined by a basic geometric shape, most metals solidify as one of three simple structures: close- 4 packed hexagonal (HCP), face-centered cubic (FCC), and body-centered cubic (BCC). Iron, with which this study is concerned, may be face-centered cubic or body-centered cubic. The face-centered cubic unit cell is depicted in Figure 2.1. Dark circles represent the position of atoms in the unit cell. As can be seen in the figure, the unit cell is composed of atoms on each corner of a cube as well as atoms on each face of the cube. The distance from one corner of the cube to an adjacent corner is called the lattice parameter.
Figure 2.1 Face-centered cubic unit cell
The body-centered cubic unit cell is shown in Figure 2.2. One atom is arranged in the center of the cube body and the others are positioned at each corner of the cube. This structure has more open space between atoms than does the face-centered cubic structure.
5
Figure 2.2 Body-centered cubic unit cell
The relative spacing between atoms in the cubic unit cell is not the same in every direction. In the BCC unit cell the distance between the centers of the atoms at adjacent corners is not the same as the distance to the atom diagonal across one of the cube faces. The result is material properties which vary with the orientation of the crystal to the applied load.
2.1.2 Cubic Crystal Coordinates Since material properties depend on crystal orientation, it is useful to have a system of defining directions in crystals. The universally accepted system for designating crystallographic planes and directions uses what are called Miller indices.
2.1.2.1 Direction Indices If one places a Cartesian coordinate system with the origin at the corner of a cubic unit cell and axes parallel to the edges of the cube, as shown in Figure 2.3, it is possible to demonstrate the index naming convention. The directions indices are written in the form of three dimensional integer vectors. The indices of the x-axis are [100], the y-axis [010], and the z-axis [001]. The direction from the origin to the corner of the cube diagonal from the origin in the x-z plane, shown by the arrow in Figure 2.3, would be written as [101]. 6
z
y
x
Figure 2.3 Direction indices and the [101] direction in a cubic crystal.
By the same convention, the direction from the origin through the center of the cube to the opposite corner would be labeled [111]; that is one step in the x-direction, one in the y-direction, and one in the z-direction. The smallest integers that give a desired direction should be used when reporting direction indices. So while the integers 2, 2, and 2 represent the same direction as 1, 1, and 1, the Miller indices would be reported as [111] and not [222]. When referring to specific directions, square brackets are used as shown above. However, when referring to all directions of the same form, carets are used. Thus, the [111], [111], [111], and [111] are all represented by <111>.
2.1.2.2 Plane Indices The indices which define crystallographic planes are also identified by sets of integers. Planes are defined by the reciprocals of their intersection points with the Cartesian coordinate system axes. Thus, a plane which intercepts the x-axis at 1, the y- axis at 3, and the z-axis at 2 would have Miller indices proportional to 1/1, 1/3, and 1/2. As is seen in Figure 2.4, this plane is defined by plane indices of (623). Using parentheses for specific planes enables differentiation between plane and direction indices. Directions with the same indices as a plane are perpendicular to that plane. A [111] direction, therefore, is perpendicular to a (111) plane. 7
Figure 2.4 The intercepts of the (623) plane with the coordinate axes. [11]
2.1.3 Vacancies and Dislocations Real crystals are not perfectly arranged arrays of atoms. Often there is an atom missing from a position in the lattice where an atom should be. This empty lattice site is called a vacancy. Vacancies are needed in crystals to maintain thermodynamic equilibrium (they contribute entropy to the crystal). If a crystal is heated, the number of vacancies in the crystal will increase to maintain this equilibrium. Atoms within a crystal may move within the crystal lattice to occupy vacancy sites, essentially swapping the position of the atom and vacancy. This motion of vacancies and atoms in the lattice is used to explain diffusion in crystals. Other defects which commonly occur in crystals are called dislocations. Dislocations are the means by which crystals accommodate deformation. When a crystal is deformed, a portion of the crystal may shear along a lattice plane. The atoms essentially “slip” over each other as the crystal is deformed. The plane on which the slipping occurs is termed the ‘slip plane’. The slipping may not progress completely from one side of the crystal to the other. The boundary on the slip plane between the slipped and un-slipped region is known as a dislocation. Dislocations are a source of stress fields within a crystal. The stress fields of dislocations interact with each other and make creation and movement of additional dislocations difficult. Larger external forces are required to continue 8 deforming the crystal. When this occurs, the crystal may be said to have been strain hardened. In a polycrystalline material, the many crystals which make up the material do not all have the same orientation. The boundary between two crystals, called a grain boundary, is a region full of dislocations and vacancies which accommodate the mismatch between the different orientations. When the angle of mismatch between two grains is above 15º it is considered to be a high angle boundary. Grains with similar orientation have low angle boundaries within them. It is also possible for a grain to have a network of low angle boundaries within it; these regions are called subgrains and compose the substructure of a grain.
2.1.4 Phase Transformations The transformation of water to ice at 0°C (liquid to solid) and to steam at 100°C (liquid to vapor) is perhaps the most well known phase transformation. In the above example, 0°C and 100°C are considered critical temperatures. When salt (NaCl) is dissolved in water the temperature at which the solution begins to form ice will drop, depending on the concentration of salt, to a minimum of -21°C when the salt reaches a concentration of 23.3%. Below -21°C the solution will become a solid with two constituents: ice and salt. The driving force for water not freezing at the standard 0°C when the salt is dissolved in it is thermodynamic stability. For a given temperature and pressure, matter exists in the state which has the lowest free energy. As heat is added to ice, the solid changes to a liquid because the liquid is the more stable form (lower free energy) at that temperature in atmospheric pressure. All metals undergo the same solid to liquid to vapor transformations described for water. For pure elemental metals, the critical temperatures at which these transformations take place are physical properties of the element. As with the water, having another species dissolved in the metal will affect the critical temperatures at which phases change. A phase change observed in metals which does not have an analogy in the water-
9 salt example, is solid state phase transformation. Some metals change from one crystal structure to another at critical temperatures while maintaining their solid state. Changes in the solid state are not as easy to observe as changes of state such as solid to liquid. There are two common methods for determining the temperatures at which solid state transformations occur in metals. Since different crystal structures often have different packing factors there is a volume change associated with changes from structure to another. A device called a dilatometer is able to measure the very small changes in dimension associated with the change in crystal structure. There are also changes in the rate of energy absorption or release when phase transformations take place. By monitoring the rate of heating or cooling for a sample, the critical temperatures for phase transformation may be ascertained.
2.1.5 Solid State Nucleation Nucleation is defined as formation, through thermally activated fluctuations, of the smallest stable particles of a new phase [12]. When a substance changes phase, whether it is from a solid to liquid, vapor to liquid, or one crystal structure to another, the phase change is governed by thermodynamics. The laws of nature require that the phase with the lowest free energy exist at a given temperature and pressure. In physical metallurgy, pressure is normally assumed to be atmospheric and the phase changes of interest are liquid/solid and solid/solid. Transitioning from one solid phase to another solid phase, FCC to BCC for example, is called solid state transformation. In order for a solid to change phases there must be a driving force, most often an increase or decrease in temperature. If the temperature has dropped below the critical temperature for a phase transformation, the driving force is to change to the phase which is stable at the lower temperature. The new phase will form and grow at the expense of the phase which is stable above the critical temperature. Nucleation may be homogenous or heterogeneous. In homogenous nucleation, random motion of atoms in the crystal lattice may bring a number of them to form what is called an embryo. If the embryo is less than a critical size, the atoms continue randomly moving in the lattice. If, however, the embryo reaches a critical size, it becomes a nucleus 10 from which the new phase will grow. A nucleus has been defined as the first structurally stable particle capable of initiating growth of a new phase and possessing an interface with the parent metallic matrix [13]. In heterogeneous solid state nucleation, the formation of embryos and nuclei are aided by favorable sites for nucleation such as impurity particles, grain boundaries, grain corners, and dislocations within the grain. Each of these features lowers the energy required to transform the phase [14].
2.1.6 Annealing Change to material properties by deformation was briefly touched upon in section 2.1.3. Strength, hardness, and electrical resistance are all increased by plastic deformation at temperatures well below the melting point of a metal (cold working), while ductility is decreased. The deformation of the metal creates defects in the crystal lattice, which are a source of retained energy. Given enough time this stored energy will be released. With the aid of increased temperature, the release of stored energy can be expedited, this is called annealing. The three main features of annealing are recovery, recrystallization, and grain growth.
2.1.6.1 Recovery The recovery phase of annealing is characterized by the return of the physical and mechanical properties to their values before cold working. This is thought to occur by two phenomena, both of which are related to the movement of dislocations. One phenomenon is the annihilation of excess dislocations. Dislocations of opposite sign are attracted to each other and cease to exist when they meet. The other phenomenon is called polygonization, and involves the realignment of dislocations to form a low energy dislocation structure.
2.1.6.2 Recrystallization A deformed polycrystalline metal may also lower its energy state by recrystallizing; forming new crystals with fewer dislocations. Recrystallization shares many characteristics with solid state phase changes. New crystals must form by a nucleation 11 event and the formation of nuclei is favored at crystal lattice defects, grain boundaries, and impurity particles. Recrystallization is associated with a greater release of energy than that observed for recovery only [11]. There is a strong relationship between temperature and the time required for recrystallization, τ. Researchers in the 1950’s [15] noted an empirical equation of the form:
1 = Ae −Qr RT τ
where 1/τ is the rate at which the structure is recrystallized, Qr is the activation energy for recrystallization, R is the gas constant, and T is the absolute temperature. From this equation it is evident that even small changes in temperature can have significant effect on the time required for recrystallization. The activation energy for recrystallization is dependant on the amount of cold work put into the metal. Metal which has been deformed a greater amount will have a lower activation energy for recrystallization. An example of this given by Reed-Hill [11] is the complete recrystallization of two zirconium rods, one with 13% reduction in area from cold work and the other with 51% reduction in area. At 826 K the time for complete recrystallization of the 13% reduced section sample was 40 hours versus just 1.6 hours for complete recrystallization of the sample with 51% reduction in area. Metal purity also has an effect on the rate of recrystallization. Extremely pure metals have rapid rates of recrystallization. The nature of the impurity atoms also has an effect on the recrystallization rate. Reed-Hill has compiled data showing the increase in recrystallization temperature of pure copper with the addition of 0.01 atomic percent of several different elements, shown in Table 2.1. It is thought that solute atoms interact with grain boundaries and retard their motion, which is required for the nuclei to form and grow.
12 Increase in Recrystallization Added Element Temperature K Ni 0 Co 15 Fe 15 Ag 80 Sn 180 Te 240
Table 2.1 Increase in Recrystallization Temperature of Pure Copper by the Addition of 0.01 Atomic Percent of the Indicated Element (after Reed-Hill [11])
2.1.6.3 Grain Growth In both recovery and recrystallization the driving force is reduction of free energy. Once a metal sample has completely recrystallized, the stored energy may be further reduced by decreasing the number of boundaries between grains. This is achieved by larger grains growing at the expense and eventual annihilation of smaller grains. This phenomenon is often shown through the use of soap bubbles. In soap froth, the bubbles with more than 6 sides grow as time passes, while the bubbles with less than six sides will shrink in size and eventually disappear [11]. If one assumes that grain size is very small at the beginning of grain growth, a formula may be used to express the cell size as a function of elapsed time:
D = kt n
In this equation D represents the mean diameter of the growing cells, k is a proportionality constant, and t is the elapsed time. In ideal situations, the mean diameter grows with the square root of time (n=1/2), but in reality the exponent n is often less than 0.5. Regardless of the value of the exponent in the growth law equation, it can be generalized that growth diminishes with the progression of time.
13 The proportionality constant in the growth law can be expressed as a function of temperature in the following form:
−Q 2RT k = koe
This shows that k is dependent upon both the temperature, T, and the heat of activation for the process of grain growth, Q. Unfortunately, actual data often fail to give a constant value of Q for the temperature dependence of grain growth [11]. It is interesting to note that rate grain growth can be affected by deformation of the crystals; much like the time for recrystallization can be affected.
2.1.7 Grain Size Effects The mean grain size in a polycrystalline material is another factor which can greatly influence the material properties. As was mentioned earlier, the boundaries between grains are made of dislocations and vacancies, which accommodate the mismatch in grain orientation. In a large grained material, dislocations that move through the material during deformation are able to travel a greater distance before they encounter a boundary and are stopped than dislocations in a smaller grained material. The result is that smaller grained material will be harder than a large grained material of identical composition. Hardness is proportional to strength; therefore, a smaller grain size can improve the strength in a metal material.
2.1.7.1 Measuring Grain Size The effect of grain size on mechanical properties was well documented by the turn of the twentieth century [16]. By the early 1900’s several researchers had proposed different methods for measuring the size of the grains in a metallographic sample. An ASTM committee was formed to develop standards for metallographic preparation and presentation in 1916 [16]. Years of review and revision have resulted in a simple exponential equation for the expression of grain size:
14 n = 2(G – 1)
Where n is the number of grains in a square inch of a 100x micrograph and G is the ASTM grain size number. From this equation, one can see that larger grains have a smaller grain size number, G, than small grains. Modern methods for calculating grain size often incorporate digital image analysis. A series of lines or concentric circles are superimposed on a digital image of a polycrystalline structure at a known magnification. The intercepts of the superimposed lines and grain boundaries, which are picked by computer algorithms, are tabulated. The resulting number of intercepts and known length of the superimposed lines or circles enables the calculation of an average length between intercepts. This average intercept length is then used to calculate a grain size number. A personal computer with analysis software can calculate the grain size in less than a second.
2.1.8 Alloying The addition of other metal elements to a pure element creates an alloy. As shown in Table 2.1 above, the addition of even small amounts of one element to another may have a great affect on the properties of the material. Adding elements may change the crystal structure, strength, corrosion resistance, toughness, electrical resistance, and just about any other physical property.
2.1.8.1 Precipitation Alloying elements are normally added to metals while the metal is in its liquid state so that they will dissolve into a solution. When the solution cools and solidifies the alloying elements may form precipitates if the solubility for the alloying element is exceeded at the lower temperature. Precipitates nucleate and form within the matrix according to the same thermodynamic laws which govern nucleation in phase transformation. Some precipitates are desirable, as they may provide barriers to the movement of dislocations, thus increasing the strength of the material. Other precipitates may be undesirable because they are brittle and act as sites for crack initiation. 15
2.1.8.2 Solid Solution Elements which do not form precipitates and remain in solution may occupy one of two positions within the solid crystal lattice. When atoms of the solute element occupy the lattice position normally filled by atoms of the solvent metal, it is said to be a substitutional solid solution. Solid solutions may also be formed by small atoms occupying the space between the solvent metal atoms in the crystal lattice. These normally unoccupied spaces are called interstitial sites. Solutions made by atoms occupying these sites are appropriately termed interstitial solid solutions.
Solvent Atoms
Solute Atoms A B
Figure 2.5 The two basic forms of solid solutions. A) Substitutional solid solution. B) Interstitial solid solution.
2.2 Steel Metallurgy
Steel is arguably one of the most versatile engineering materials available. Its versatility is due to the wide range of material properties which can be developed through alloying and processing. Steels are based on the iron-carbon binary system. Alloys of iron with up to approximately 2% carbon content are classified as steels.
16 2.2.1 Ferrite Pure iron at room temperature has a body centered cubic (bcc) crystal structure. The lattice parameter, or length along one edge of the cube, is 2.89 Å. The atomic packing factor, or volume fraction occupied by atoms, for this structure is 0.68. This phase of iron is called either α-iron or ferrite. It has very low solubility for carbon at room temperature (on the order of 10-5 wt%) with increasing solubility as temperature increases. At temperatures below 770°C, ferrite is ferromagnetic and at temperatures between 770°C and 912°C it is paramagnetic. The temperature at which the change in magnetic properties, from ferromagnetic to paramagnetic (770°C), takes place is called the Curie temperature.
2.2.2 Austenite At temperatures above 910°C, pure iron changes its crystal structure to a face centered cubic (fcc) structure. Its lattice parameter is 3.57 Å. The atomic packing factor for this atom arrangement is 0.74, which represents the closest packing possible. This phase of iron is called γ-iron or austenite. The changing packing factor between ferrite and austenite is responsible for a volume contraction when ferrite changes to austenite on heating above 912°C. Austenite is paramagnetic and is the stable form of iron between 912°C and 1394°C. Carbon is much more soluble in austenite than it is in ferrite, which is one of the reasons steel properties can be “tailored”. Both austenite and ferrite are soft and ductile. Their average properties are: a tensile strength of 40 ksi, elongation of 40%, and hardness of less than 150 BHN [14].
2.2.3 Delta Iron In pure iron, from 1394°C to its melting temperature at 1538°C, the structure reverts to a bcc structure. This form of iron is referred to as δ-iron or ferrite. The result is another volume change when the transformation from austenite to δ-iron occurs, except this time it is a volume expansion. The lattice parameter for δ-ferrite is slightly larger than that of α-ferrite at 2.89 Å.
17 2.2.4 Cementite Iron and carbon readily form a metastable intermetallic compound called cementite. It is represented by the formula Fe3C. Given enough time, cementite will decompose into iron and graphite. However, once formed, cementite is very stable and it is normally treated as an equilibrium phase. Unlike the ferrite and austenite phases of iron, cementite is non-cubic and has an orthorhombic crystal structure. It also exhibits no elongation, low tensile strength (~5 ksi), and hardness of more than 700 BHN [14].
2.2.5 Iron-Carbon Phase Diagram A phase is defined as: a physically homogenous and distinct portion of a material system [13]. A phase diagram is a graphical representation of the temperature and composition limits for a material system. The most common phase diagrams are binary equilibrium diagrams. These represent the phases present in a two component system at a given temperature under steady state conditions. Figure 2.5, shows a portion of the Iron- Cementite equilibrium phase diagram. As can be seen from the axis labels, very small changes in the carbon concentration have a large effect on phase equilibrium. The effect of carbon on the stability of austenite can also be seen. Carbon is an austenite stabilizer, and in sufficient concentration permits austenite to remain at temperatures much below the equilibrium temperature of austenite in pure iron. The diagram also shows that for a given composition and temperature it may be possible to have two phases present. The triangular shaped region bounded by the 727°C temperature line and the two lines coming down to intersect it from pure iron at 912°C is one such two phase region, known as the intercritical region. For future reference the line from 912°C in pure iron to 0.77% carbon at 727°C is called the A3 line and the horizontal line at 727°C is referred to as the
A1.
18 A3
A1
Figure 2.6 Portion of the Fe-Fe3C phase diagram [10] with A3 and A1 temperatures defined with arrows
As an example of a two phase region, a steel with 0.20% carbon held at 780° will have both austenite and ferrite present. All the ferrite present would have a composition of approximately 0.02% carbon and the austenite would all have a carbon content of about 0.42%. These values correspond with the equilibrium carbon concentrations for those phases at 780°C (where the 780°C line intersects with the lines denoting the change from single to two phase region). While the composition of the two phases present may differ, the bulk composition remains constant. The percentage of the two phases present may be calculated by using what is referred to as the lever law. The composition of the steel may be considered to be the fulcrum of a lever and the horizontal line between the compositions of the coexisting phases represents the lever. The amount of each phase must balance the lever. In the example above the percent ferrite in 0.20% carbon steel held at 780°C would be equivalent to: 19
0.42 − 0.2 ×100% = 50% ferrite 0.42 − 0.02
2.2.6 Phase Morphologies Phase diagrams such as those shown in Figure 2.5 are made under equilibrium conditions, samples are heated at very slow rates to allow atoms time to diffuse and energy barriers to be overcome, which is required for changing from one phase to another. While this is useful for determining the equilibrium phase transformation temperatures, in industrial fabrication using steel, rapid heating and cooling often take place. These rapid thermal processes do not always allow the time for atomic the diffusion required for the nucleation and growth of equilibrium phases. When cooling is fast enough, a phase may continue to exist below its critical transformation temperature in a phenomenon known as super cooling or under cooling. When transformations occur as a result of rapid cooling from elevated temperatures, the cooling rate has significant effect on the resulting structure. It should be noted that Linnert’s book on welding metallurgy [17] and Samuels’s book on carbon steel microscopy [18] point out that many terms have been used for the same microstructures over the years. There have been efforts to arrive at an internationally accepted terminology, but final agreement has not been reached. The following sections cover the some of the morphologies commonly found in steels and the names used for each by Samuels.
2.2.6.1 Pearlite Pearlite was given its name for its mother-of-pearl appearance when optically observed [18]. It is a lamellar product consisting of alternating lamellae of ferrite and cementite. Rather than grains, pearlite forms nodules [14]. Each nodule is composed of colonies of parallel lamellae which have different orientations than the lamellae of adjacent colonies. When resolved under a microscope, pearlite often resembles the stripes on a zebra. Very fine pearlite is often difficult to resolve and may appear as very dark or 20 even black grains. This difficulty lead early metallurgists to identify fine pearlite as a separate phase [18]. Pearlite may form under isothermal, continuous cooling, or directional growth conditions.
2.2.6.2 Bainite In ferrous metallurgy there are two classical forms of bainite form: upper bainite and lower bainite. The two types form over different temperature ranges; upper bainite forming at higher temperatures than lower bainite. Upper bainite is often characterized by a feathery structure of low carbon ferrite laths in cementite. It forms at temperatures between 350ºC and 550ºC [14]. Lower bainite generally forms below 350ºC, although carbon content may influence the temperature at which lower bainite begins to form [19]. Lower bainite is characterized by a plate-like morphology. Plates of ferrite are separated by cementite, as in upper bainite. However, the ferrite plates which form in lower bainite have carbide precipitates within them [19].
2.2.6.3 Martensite Martensite has a body centered tetragonal crystal structure in iron. This structure is similar to the bcc crystal structure, but four of the faces of the cube are rectangular, rather than square. The martensite phase is given its name due to its formation by a martensitic transformation. The martensitic transformation has been defined as: the coherent formation of one phase from another without change in composition by a diffusionless, homogeneous lattice shear [14]. Transformation to martensite is achieved by rapid cooling from an austenitic state. When resolved with optical microscopy, martensite appears as a needle like structure. Martensite may be differentiated from bainite by hardness, with martensite being harder, and by etching, with martensite etching lighter [19].
2.2.6.4 Ferrite Morphologies Ferrite, which was previously described as the bcc structure of iron which is thermodynamically stable at temperatures below 912ºC, may form in a variety of 21 geometries. The classical work by Dubé and Aaronson [20,21] resulted in the morphological classification system for ferrite depicted in Figure 2.7. Allotriomorphic ferrite begins forming along austenite grain boundaries when the austenite is cooled below the A3 temperature. The ferrite grows preferentially along boundaries and its shape is therefore influenced by the boundary. Widmanstätten ferrite has a plate-like morphology. Given sufficient undercooling the plates will begin to form at low angle austenite grain boundaries [14]. Aaron and Aaronson [22] have reported that the nucleation rate for these plates is very high and that it is more common to find secondary sideplates, which grow from alltriomorphs which have already formed at grain boundaries. According to Sinha [14] the morphology which has been given the name sawteeth ferrite should be regarded as an intermediate between allotriomorphs and sharp tipped sideplates. Recent work on determining the 3D morphology of ferrite structures, by Kral and Spanos [23], appears to show that sawteeth grow only as secondary structures from alltriomorphs.
22
a)
b)
c)
d)
e)
f)
Figure 2.7 The Dubé morphological classification system for ferrite as modified by Aaronson [20]. a) grain boundary allotriomorphs; b) Widmanstätten sideplates (primary and secondary); c) Widmanstätten sawteeth (primary and secondary); d) idiomorphs, e) intragranular Widmanstätten plate; and f) massive structure.
23 Intragranular Widmanstätten are formed at large undercooling. They have needle- or platelike shape, often having the appearance of double-ended isosceles triangles. Their formation is favored by large austenite grain size. Sinha [14] points out that this type of ferrite forms at isolated dislocations or low angle boundaries in austenite, but that direct determination of the nucleation sites has not been determined. At lower temperatures the precipitation of non-lamellar carbides converts the plates to bainitic ferrite [19]. Ferrite idiomorphs are thought to nucleate heterogeneously at non-metallic inclusions and dislocations. They form at small undercoolings and have a roughly equiaxed (equal in all dimensions) morphology. They may form intragranularly or at austenite grain boundaries. Massive ferrite is normally associated with rapid cooling from the austenitic temperature region and what is called a “massive” transformation. The transformation falls somewhere between the diffusional transformations which form pearlite and bainite, and the diffusionless martensitic transformation. While there is no general agreement on an acceptable definition for a massive transformation [24], terms often used to describe it are: composition-invariant, interface-controlled, and lack of lattice orientation relationships. Growth of a new phase in a massive transformation takes place by random atomic transfer across a high energy, incoherent interface [24,25]. It has been estimated by Hillert [25] that the growth rate of the product phase in a massive transformation may be as high as 1 cm/sec. This rapid rate of growth normally results in large or “massive” grain size, from which the transformation received its name. In his review of metallurgical nomenclature Samuels [18] points out a criticism that large ferrite grains are not always the result of a massive type transformation.
2.2.7 Alloying Additions As was mentioned in Section 2.1.7, the addition of even very small amounts of other elements to a pure metal may have a significant effect on material properties. In general, alloying elements added to steel either widen the γ-phase field, making austenite stable over a wide range of compositions, or shrink the γ-phase field, promoting the formation of ferrite over a wide range of compositions. Austenite stabilizers and ferrite stabilizers 24 are the respective terms for such effects. This section will deal with common elements found in steels and the reason for their presence [14,17].
2.2.7.1 Carbon Carbon has a greater affect on iron than any other alloying element. It is a potent austenite stabilizer and forms an interstitial solid solution with austenite. Room temperature solid solubility is only about 0.008%, which means the carbon is rejected from the solution in the form of cementite as steel cools from the austenitic temperature range. The maximum attainable hardness for steel has direct correlation to the amount of carbon in the steel.
2.2.7.2 Manganese Manganese is used commonly found in steels because it is inexpensive compared to many other alloying elements and has many helpful attributes. Manganese combines with sulfur to form manganese sulfide (MnS) and with oxygen to form manganese oxide (MnO). In molten steel manganese reduces the amount of both oxygen and sulfur in the melt by forming these compounds, most of which are removed as slag. Manganese which is not consumed in the formation of MnS may form manganese carbide (Mn3C), which is indistinguishable from cementite. Manganese refines pearlite nodule and ferrite grain sizes, which increase the yield strength of carbon steel. The combination of these actions by manganese normally brings about an increase in fracture toughness.
2.2.7.3 Sulfur Although sulfur may be added to steels to promote ease of forming chips when machining, it is generally considered a “tramp” element and held to very low levels (below 0.05%). When present in iron alloys, sulfur forms iron sulfide (FeS), which has a relatively low melting point, 1200ºC, when compared to the iron solidus temperature. The effect of this low melting temperature constituent in steel is hot shortness; a reduction in the hot-working properties. As was mentioned in the previous paragraph, the addition of manganese to the melt removes and ties up most of the sulfur in the form of MnS. 25
2.2.7.4 Phosphorus Very small amounts of phosphorus may increase the strength, hardness, and corrosion resistance of steel. However, phosphorus is considered a tramp element. In solid state phosphorus forms Fe3P, which is extremely brittle. The presence of this compound in steel causes cold shortness; the tendency to crack during cold working. Phosphorus causes a decrease in fracture toughness of steels designed to be strengthened by heat treatment. Another problem caused by phosphorus is segregation during solidification. Phosphorus tends to become enriched in the last metal to solidify, and as a weak ferrite former promotes the formation of ferrite and rejection of carbon to the surrounding metal. This results in a band in the microstructure with less cementite and greater ferrite. These negative effects of phosphorus keep its content in most steels to 0.04% or less.
2.2.7.5 Silicon Silicon is used in the steelmaking process to remove oxygen from the melt. When silicon is not used as a killing agent (removing oxygen from molten steel) it is only a residual element and may be found in trace amounts (approximately 0.008%). It is a promoter of hardenability; the formation of martensite when cooled from above the A3 temperature. Silicon is a strong ferrite stabilizer, which in large enough quantities can prevent the transformation to austenite altogether. Silicon also promotes the fluidity of molten steel, which makes it a useful addition in casting and welding applications.
2.2.7.6 Copper Copper is a very weak austenite stabilizer, but its use in alloying is for other purposes. Until the early 1900’s copper was regarded as a tramp element responsible for surface checking and hot cracking. This problem was solved with the addition of some nickel. The motive for most modern copper additions is the significant delay of corrosion when copper is present in concentrations above 0.20%. The additions of about 1.25% copper with an equal amount of nickel forms precipitates that significantly increase hardness.
26 2.2.7.7 Chromium Chromium is a very strong ferrite stabilizer. Like silicon, sufficient chromium can completely prevent the transformation to austenite in steels. It has a strong effect on the corrosion resistance of steel. When present in sufficient quantities it promotes formation of a protective oxide surface film which is the basis of the stainless steel alloys. Chromium is also added to maintain the strength of steel at elevated temperatures. Finally, chromium strongly increases the hardenability of steel.
2.2.7.8 Nickel Nickel is a strong austenite stabilizer and is added in stainless steels to counterbalance the ferrite stabilizing effect of chromium. It is completely soluble in iron and when alloyed with iron in concentrations greater than about 25%, it makes austenite stable at all temperatures. Nickel also has the unique ability to increase hardenability while also increasing fracture toughness. Nickel has a lesser affinity for oxygen and carbon and therefore forms no carbides or oxides when alloyed with iron. As was mentioned earlier, nickel has found use in some steels with copper as a precipitation hardening agent.
2.2.7.9 Molybdenum Molybdenum is a potent ferrite stabilizer. Additions of just 3% to iron will cause the retention of ferrite at all temperatures. It readily forms carbides and increases hardenability. It is frequently added in concentrations ranging from 0.25% to 0.5% along with chromium and nickel for this purpose. In steels which are used at elevated service temperatures, molybdenum may be added in amounts from 0.5% to 4% for the improvement of strength and creep resistance in service. In steels with low alloy composition molybdenum is added in small amounts (0.05% to 0.25%) along with manganese and some nickel to suppress pearlite formation or produce fine carbide lamellae and reduce the size of pearlite areas.
27 2.2.7.10 Niobium Niobium has a bcc crystalline structure and is a ferrite stabilizer when added to iron. It is added to steels in very small amounts to form niobium carbide and carbonitride precipitates, which increase strength. Niobium carbides begin to precipitate in steel at about 1200ºC. Additions of as little as 0.05% niobium can produce a significant increase in strength. When properly controlled, niobium additions promote fine ferrite grain size which tends to improve toughness. Niobium is commonly added with vanadium and nitrogen to form complex niobium and vanadium carbonitrides. Optimum size and distribution of niobium precipitates and refining of ferrite grains is achieved by hot working the steel (working above the recrystallization temperature). This process, called Thermo-Mechanical Control Processing (TMCP), will be discussed in section 2.3.5.
2.2.7.11 Vanadium Vanadium, like niobium, is a ferrite stabilizer. It has traditionally been added to steels, especially tool steels, to promote hardenability. When a sufficient amount of manganese is present, small additions of vanadium (0.05% to 0.10%) provide effective strengthening. A benefit of vanadium is a reduction in austenite grain coarsening when heated above the A3 temperature. Vanadium has a strong affinity for nitrogen and a tendency to form carbides. Strengthening of steels alloyed with vanadium is achieved by controlled rolling, heat treatment, or a combination of the two.
2.2.7.12 Aluminum Aluminum is a very strong ferrite stabilizer; as little as 1% addition of aluminum to iron will make ferrite stable at all temperatures. It is used primarily in the steelmaking process to remove oxygen from the melt by forming Al2O3. Aluminum also has the ability to form aluminum nitride particles. Excess nitrogen can adversely affect the toughness of ferrite. Finally, aluminum acts to restrict austenite grain coarsening when steel is heated above the critical temperature range.
28 2.2.8 Calculation of Alloying Effects In his chapter on iron-carbon alloys, Sinha points out that in 1965 empirical formulas for calculating the practical A1 and A3 temperatures had been developed through reviewing published data on more than 150 steels [14]. The formulas are shown below.
AC1 (ºC) = 723 – 10.7Mn – 16.9Ni + 29.1Si + 16.9Cr + 290As + 638W
AC3 (ºC) = 910 – 203√C – 15.2Ni + 44.7Si + 104V + 31.5Mo + 13.1W
From the time when these formulas were developed, the modern PC has become powerful enough to calculate and prepare phase diagrams for complex alloying systems. Software, such as JMatPro and Thermo-Calc, use databases of thermodynamic stability to calculate and predict stable phases for a variety of conditions.
2.3 Hot Working of Steel
The ASM Materials Engineering Dictionary gives two definitions for hot working: “1) The plastic deformation of metal at such a temperature and strain rate that recrystallization takes place simultaneously with the deformation, thus avoiding any strain hardening. 2) Controlled mechanical operations for shaping a product at temperatures above the recrystallization temperature.” [13] A review of strength and structure under hot working conditions [26] points out that hot working normally involves extremely large strains applied at high rates at temperatures above 0.6 times the absolute melting temperature of the material. The strength and ductility of the material are dependent upon the temperature at which the deformation occurs and the rate at which the strain is applied. The microstructure developed as a result of hot working is dependent on the alloy composition, temperature during deformation, strain rate, applied strain, and the cooling rate after deformation.
29 2.3.1 Dynamic Annealing As was discussed in section 2.1.6, annealing is the recovery of material properties by the processes of recovery, recrystallization, and grain growth by heating the material after cold working. At elevated temperatures, these processes may occur as the deformation happens. When this occurs, the processes are termed dynamic (as opposed to static). Testing dynamic annealing properties in the laboratory often incorporates the hot torsion test, which is capable of achieving shear stress versus shear strain measurements to very high strains. In hot torsion tests a bar is heated to the test temperature and one end of the bar is rotated about its axis while the other is fixed. In metals which recover very quickly, dynamic recrystallization may not occur. Aluminum and ferritic steels crystal structure often exhibit this property [26]. McQueen has pointed out that materials which experience only dynamic recovery often exhibit elongated grains [27]. Figure 2.8 below shows a typical high temperature for a material which exhibits this quick recovery trait.
Figure 2.8 Typical high-temperature torsion shear stress-strain curve of a metal that recovers very quickly. (from Reed-Hill and Abbaschian [11])
30 As can be seen in the figure, the stress initially increases quickly as the material is strained. The slope of the stress-strain curve then droops until the stress reaches a steady value.
2.3.1.1 Luton and Sellars Model Materials which do not recover easily, such as nickel, copper, and austenitic iron [26], deviate from the example curve shown in Figure 2.8 when recrystallization occurs. Luton and Sellars [28] determined that there is a critical strain, εc, at which recrystallization begins. The softening due to recrystallization causes a drop in the stress. This drop may be followed by either an oscillating stress-strain curve or a steady stress which is lower than the peak stress at which the recrystallization began. Figure 2.9 is helpful in illustrating the differences between these two reactions.
Figure 2.9 Predicted stress-strain curves for dynamic recrystallization (a) critical strain to initiate recrystallization, εc > εx, the strain occurring in the time for a large fraction of recrystallization. (b) εc < εx. (from Luton and Sellars [28])
31 Luton and Sellars explained the two different responses phenomenologically. There is a strain, εx, associated with the time required for a large fraction of recrystallization to occur after the critical strain, εc, has been attained. They proposed that when the time for recrystallization is less than the time required to reach the critical strain, the stress will oscillate as shown in Figure 2.9a. However, when the time for recrystallization is longer than the time to reach the critical strain for recrystallization, the stress will remain nearly constant as the strain hardening and strain softening events overlap. The study by Luton and Sellars included nickel alloys with increasing amounts of iron. Increasing iron content decreased the rate of recrystallization and increased the rate of work hardening, resulting in a higher peak flow stress. They concluded that the recrystallized grain size was determined entirely by flow stress (the stress required to cause plastic deformation), and that dynamic recrystallization (DRX) changed from periodic to continuous as stress increased. They also stated that the activation energy for deformation was determined mainly by the activation energy for DRX.
2.3.1.2 Sakai and Jonas Model After Luton and Sellars [28] proposed their simple model, continuing work by other researchers brought criticism of the model and provided new models of dynamic recrystallization. Sakai and Jonas, in their 1984 review of dynamic recrystallization [29], pointed out that the values for εc determined experimentally from torsion experiments are higher than the values measured in tension or compression tests. They also claimed that
εx in their tension and compression tests never exceeded εp. This was in direct contrast to Luton and Sellars critical strain criterion for transition from cyclic to single peak recrystallization, εp = εx. Sakai and Jonas proposed that the single peak stress-strain curves were associated with grain refinement while flow stress oscillations were associated with grain coarsening. They also claimed that the change from single peak to multiple peak stress- strain curves was dependent upon the initial grain size of the material as well as a temperature corrected strain rate, Z. The Z term is also called the Zener-Holloman parameter and can be calculated with the following formula: 32 . Z = ε⋅ e(Qdef / RT )
Where ε˙ is the strain rate, Qdef is the activation energy for deformation, R is the universal gas constant, and T is the absolute temperature. Jonas and Sakai’s proposed model is best summarized by the plot in Figure 2.10.
Figure 2.10 A microstructural mechanism map for distinguishing between the occurrence of two types of dynamic recrystallization. (from Sakai and Jonas [29])
In the plot D0 represents the initial grain size and Ds the stable dynamic grain size. Sakai and Jonas considered that when D0 was larger than 2Ds, new grains nucleate at the grain boundaries and begin growing. This forms a “necklace” like structure of small grains around the interior of the initial grain. The process repeats itself, with successive necklaces forming until the large grain is consumed. For grains which are initially small compared to Ds, the authors suggested that nucleation is limited and grains will tend to
33 coarsen. The solid line between the hatched and un-hatched region in Figure 2.9 is representative of Zc, the critical Zener-Holloman parameter, for a given initial grain size. Changing the strain rate or temperature during deformation may therefore cause a change from coarsening to grain refinement or vise versa.
2.3.1.3 McQueen’s Model McQueen, a contemporary of Sakai and Jonas, praised their model as a great advancement in the understanding of dynamic restoration mechanisms, but criticized it for not considering substructure [30]. McQueen asserted that the steady-state flow stress depends on the sub-grain size during steady state deformation. He contended that the number of nuclei that form in the necklace along the original grain boundaries depends on the density of subgrains along the grain boundaries. He also pointed out that work on single crystals showed nucleation could occur in the interior of grains and that nucleation in polycrystalline materials need not nucleate new grains only at grain boundaries, especially at high strain rates. McQueen proposed two substructure models for nucleation in his criticism of Sakai and Jonas. The first model McQueen proposed is illustrated in Figure 2.11. He proposed that the formation of nuclei was dependent upon the substructure cell size and the cell-wall density.
34
Figure 2.11 The substructure formation (1,2), the formation within a grain (3), and the growth and deformation (4,5) of a dynamic nucleus are shown. During steady-state deformation, nuclei are repeatedly forming from subgrains in different regions (6-9), including those which have previously recrystallized (8). (from McQueen [30])
McQueen’s second model for nucleation considered the varying states of strain in a dynamically recrystallizing material. In static recrystallization (SRX), all the material has roughly the same dislocation density and new grain boundaries migrate until they impinge upon another recrystallized region. McQueen suggested that varying degrees of dislocation density would exist in the dynamically recrystallizing material depending on the strain applied since each area recrystallized. A dynamically recrystallized nucleus would grow preferentially into regions of high dislocation density and be retarded by regions of low dislocation density. The result, he surmised, would be bulging of migrating boundaries to form new nuclei. This phenomenon is illustrated in Figure 2.12.
35
Figure 2.12 Nucleation during dynamic recrystallization as a result of a migrating boundary. (from McQueen [30])
In the figure, N represents boundaries between high and low dislocation density regions; A’, A, B, and C represent new nuclei. Nuclei A’ initially grows into surrounding material until the migrating boundary is retarded by the low density boundaries. Straining continues while the nucleus is growing and the boundary bulges into regions which have high dislocation density. This mechanism would be favored at lower strain rates according to McQueen.
2.3.2 Measuring Critical Strain A common concept in the theories discussed is that of a critical strain for nucleation of dynamic recrystallization. A method for finding the critical strain for dynamic recrystallization that has been proposed is plotting the strain hardening rate, θ (dσ/dε), against the stress [31]. Extrapolating the curve to θ = 0 gives the portion of the curve due to dynamic recovery and where the experimental curve deviates from the extrapolated curve is where dynamic recrystallization occurs. Other researchers prefer to plot -dθ/dσ
36 against σ [32,33]. The minimum in this curve represents the initiation of dynamic recrystallization.
2.3.2 Softening After Dynamic Recrystallization The experiments performed in developing the models of dynamic recrystallization previously described involved quenching of the test samples following deformation in order to prevent grain growth. After deformation new grains may nucleate and grow by normal SRX. Another possibility is the continued growth of dynamic recrystallization nuclei after deformation, called metadynamic recrystallization (MDRX). MDRX is considered a special case of static recrystallization due to its lack of an incubation period [34]. It may also be referred to by some as post-dynamic static recrystallization [35]. Sinha’s chapter on thermomechanical treatment [14] claims that MDRX is an order of magnitude faster than static nucleation and results in a finer grain structure than classical recrystallization due to a higher density of nuclei. Another softening mechanism which has been proposed is metadynamic recovery (MDRV). Sakai and his coworkers [34] suggested the DRX grains have a dislocation density gradient. The regions of low dislocation density are below the critical strain for static nucleation and therefore the DRX grains do not fully soften. Some researchers have proposed that the softening mechanism after deformation at elevated temperature is dependent upon the amount of strain put into the material [35,36]. Static recovery, static recrystallization, metadynamic recovery, metadynamic recrystallization and grain growth may act alone or in various combinations. Differentiating between the different modes can be difficult. Xu and Sakai performed a series of tensile tests on a carbon steel to develop a model for the mode of softening [36]. They heated a specimen to the desired temperature, strained it a given amount, unloaded the specimen while maintaining the temperature and then reloaded it. The test was repeated for a variety of temperatures, strains, and strain rates. The degree of softening, X, was defined as:
X = (σε-σy2)/(σε- σy1) 37 where σy2 and σy1 are the yield stresses at reloading and pre-straining respectively, and σε is the flow stress at a strain of ε immediately before unloading. Xu and Sakai’s results for the different stages of restoration are summarized in Figure 2.13. They considered three stages of restoration following dynamic recrystallization. In stage I they suggested three regions exist: dynamically recrystallized nuclei, fully work hardened grains, and growing dynamically recrystallized grains. The region around the nuclei undergoes metadynamic recrystallization, the fully workhardened grains experience classical recovery, and the dynamically recrystallized grains are subject to metadynamic recovery.
Figure 2.13 Schematic illustration showing the relation between each of the softening stages and restoration processes operating mainly after dynamic recrystallization. (from Xu and Sakai [36])
In stage II, softening is largely associated with classical static recrystallization of the fully work hardened regions. Softening in stage II is terminated when statically recrystallized grains and MDRV grains impinge on each other. At the termination of
38 stage II and the beginning of stage III there are three types of grains: SRX, MDRX, and MDRV. In stage III the recrystallized grains grow, but growth is arrested by the MDRV grains. The MDRV grains can exist stably for long annealing times, leading to incomplete softening [34]. Recent work by Perry et. al. considered the recrystallization behavior of hot-deformed ferrite [37]. Using a Gleeble 1500 they deformed a low carbon steel (0.03%) to 0.75 true strain in compression at 1.0/s strain rate for a variety of temperatures, all in the ferrite range. Following straining, the specimens were brought to 621ºC and held for 100 seconds and then rapidly cooled to room temperature. The authors reported higher flow stresses for samples heated above the Ac3 temperature, due to an increase in the activation energy for deformation of austenite. All data from samples which formed austenite during heating were excluded from the results. From the hot-deformation of ferrite tests they concluded two mechanisms for recrystallization occurred following deformation. High angle boundary motion of statically recrystallized grains and recrystallization by subgrain coarsening were determined to be the competing mechanisms. High angle boundary motion was characterized by large, strain free recrystallized grains mixed with grains of unrecrystallized material (see Figure 2.14). They claimed this type of structure was observed in samples strained at low temperatures. As deformation temperature increased the recrystallization mode was determined to change to the coarsening of subgrains. This recrystallization mechanism is illustrated in Figure 2.15.
39
Figure 2.14 Recrystallization by high-angle boundary motion. (A) undeformed structure. (B) the 50% compressed microstructure with a fine substructure. (C) new grain formation. (D) the nearly recrystallized structure. (from Perry et. al. [37])
40
Figure 2.15 Recrystallization by subgrain coarsening. (A) undeformed structure. (B) the 50% compressed microstructure with a developed substructure. (C) coarsening subgrains. (D) fully recrystallized structure, nearly indistinguishable from a structure that recrystallized via high-angle boundary migration. (from Perry et. al. [37])
2.3.4 Effect of Carbon on Flow Stress While the effect of carbon on hardenability in steels has been known for some time, its effect on elevated temperature flow stress was not studied until the 1970’s. Glover and Sellars determined that increasing the purity of iron could result in a transition from continuous to discontinuous dynamic recrystallization [38]. They determined that a critical strain for the onset of recrystallization was the most important factor in determining deformation characteristics. More recently, Desrayaud et. al. studied the influence of pure iron with precisely controlled amounts of carbon additions varying from less than 0.5 ppm to 220 ppm [39].
41 These researchers did not find the expected transition from discontinuous to continuous recrystallization, but they were using compression rather than torsion for deformation. They suggested that other impurity elements may have an effect on the transition from steady state to oscillating flow stress. They found that carbon had different effects on the activation energy, Q, for deformation depending on the strain rate. They found that at low strains carbon additions decreased the value of Q, most likely by limiting grain growth prior to straining. At high strains they reported increased values of Q, and theorized that the interaction of the solute atoms and moving grain boundaries was weakened in this situation. A year later Serajzedah and Taheri published their work on hot compression of a high carbon (0.7%) and low carbon (0.1%) steel [40]. Their series of hot compression tests showed that increasing strain rates resulted in higher flow stress. They also showed that the higher carbon content steel had lower flow stress than did the low carbon steel. In 2004, work by Elwarzi and coworkers [32] supported Serajzadeh and Taheri’s work. They used a 0.91% carbon steel and a 0.71% carbon steel in a series of hot compression tests. Their data showed that the 0.71% carbon steel developed higher flow stresses.
2.3.4 Phase Stability in High Strain There has been considerable work showing the thermodynamic stability of a phase can be influenced by the application of energy in the form of strain [41-46]. The research by these authors has shown that, in the presence of strain, steels may form ferrite in quantities and at rates not achieved without strain. Hurley and Hodgson, in their work on ultra-fine ferrite [41], found that with a 40% reduction in thickness and sufficient undercooling, they could induce the nucleation of ferrite grains within large austenite grains at temperatures above the Ar3. They used the term “dynamic strain-induced transformation” for this reaction. Researchers from Korea also noted this reaction and gave it the term “strain induced ferrite” [42]. They found that the amount of reduction required for the onset of ferrite formation was reduced as the degree of undercooling increased. In both the work by Hurley and Hodgson and the work by Hong et. al., the formation of ferrite during deformation was deduced from the 42 decrease in flow stress and the presence of ferrite in metallographic samples prepared from the test specimens quenched after deformation. Lewis et. al. examined the ductility trough in carbon-manganese steels associated with the austenite to ferrite transformation [43]. Their tension and compression tests in the intercritical region in steel with 0.1% carbon and 1.43% manganese showed the formation of what they called “deformation induced ferrite” at temperatures between the equilibrium A3 temperature and the Ar3 temperature. They found that ductility was linked to the formation of ferrite; ductility was at a minimum when 5 to 10% ferrite is present, and recovered when more than ~ 50% ferrite was present.
Studies of microstructural evolution during thermomechanical processing of interstitial-free steels led Rauf and Boyd to conclude that transformation to massive ferrite was possible at cooling rates much lower than those normally associated with massive ferrite transformation [44]. They also suggested that the rate of transformation to both polygonal ferrite and massive ferrite could be decreased by the presence of substitutional solute atoms. Yada and his coworkers proposed a direct transformation of the “massive” type from austenite to ferrite [45]. They reported a decrease in the deformation stress in both the two phase region and at temperatures above the A3. They suggested ferrite grains could be nucleated even at these temperatures. Their thermodynamic calculations showed that the energy saved by the transformation was greater than the energy consumed by the transformation, indicating that conservation of energy was the driving force for the transformation. An excellent argument for the formation of ferrite as a result of deformation was continued work by Yada and his coworkers [46]. Hot torsion experiments similar to the ones performed in previous work [45] were conducted while in-situ X-ray diffraction was used to analyze the phases present. The diffraction patterns clearly showed the presence of ferrite at temperatures above the A3. Once again, the driving force for the transformation was deemed to be conservation of energy.
43 2.3.5 Controlled Processing From all the above sections on hot deformation of steels it should be apparent that the processing of steel at elevated temperature can vary tremendously and that the resulting structures can have just as much variation. When steel is rolled into plate, care must be taken in processing to achieve the desired material properties. Rolling steel at temperatures well above the A3 temperature is called hot rolling. Reheating the steel slightly into the austenitic temperature range after cooling below the A1 temperature can reduce the grain size in hot rolled steel. It is possible to achieve a reduction in grain size after hot rolling by making the last rolling passes just above the A3 temperature. This process is called controlled rolling. The benefit of this process is time saved from not having to reheat the steel to achieve grain refinement. Another process which achieves a uniform distribution of fine grains is thermomechanical control processing (TMCP). This is a term used for very precise control of temperature and deformation at and just below the A3 temperature. Materials processed with this technique may be quenched directly out of the rolling mill (direct quench) to produce even higher strength and toughness. Steels processed by this technique often include niobium, titanium, or vanadium (strong carbide and nitride formers). The carbides, nitrides, and carbonitrides formed by these elements pin grain boundaries and facilitate the formation of fine-grained ferrite.
2.4 Study Steels
This section gives a brief history and description of the alloys used in this study: ingot iron and HSLA-65.
2.4.1 Armco Ingot Iron A patent for a high-purity iron was issued to the American Rolling Mill Company in 1909 [47]. This iron came to be known as Armco iron. Armco ingot iron has a maximum allowed carbon content of 0.03% and typical hardness of 45 RB [17]. It is used in
44 enameling, galvanizing, and deep-drawing sheets [17]. Armco iron has been and continues to be used for basic research into material properties [48-56] and is ideal for such studies; its low alloying content makes it a simple system to study and understand.
Figure 2.16 Micrograph of ingot iron hot rolled sheet (0.008 C, 0.006 Si, 0.03 Mn, 0.07 O, 0.005 N) [18]
Figure 2.16 shows a typical micrograph of a high-purity ingot iron. The carbon content of these irons, while significantly low, exceeds the equilibrium concentration of carbon in iron at room temperature. The result is the formation of cementite, seen in the micrograph as films at the grain boundaries of equiaxed ferrite grains. Etch pits have formed in the iron (right micrograph) and are evidence of discrete carbide particles.
2.4.2 HSLA-65 As mentioned in Chapter 1, HSLA-65 was developed in the 1990’s by the US Navy. Its ASTM designation is A945 Grade 65. Table 2.3 gives the limits for the chemical composition of A945 Grade 65. HSLA-65 has required minimum yield strength of 65 ksi and tensile strength requirements of 78 ksi minimum and 100 ksi maximum. Achieving these requirements is accomplished through TMCP.
45 Element Wt% C 0.10 Mn 1.10/1.65 Si 0.10/0.50 S 0.010 P 0.025 Cr 0.20 Ni 0.40 Mo 0.080 Cu 0.35 V 0.10 Nb 0.05 Al 0.08
Table 2.2 A945 Grade 65 chemical specification (ranges and maximums)
2.5 The Friction Stir Welding Process
TWI described the process of friction stir welding in a patent application in December of 1991 [3]. The patent outlines a method whereby a rotating tool generates frictional heat on the faying surfaces of a joint and external fixturing keeps the faces of abutted plates from moving. The heat causes a plasticized region, which is mixed by the tool to form a common bond. The welding probe is composed of a pin, which is plunged into the material, and a shoulder of larger diameter to provide constraint. Translating the probe along a joint results in a butt weld. The authors of the patent called the process “friction stir butt welding” [3]. The process is a solid state welding process, meaning there is no melting involved in joining the two workpieces. There was very little work published in the open literature on the new friction stir process until 1999 when TWI hosted the first international symposium on friction stir welding. In the subsequent years there has been four more friction stir welding symposiums as well as papers published in scholarly journals and presented at other conferences.
46
Figure 2.17 Schematic of “friction stir butt welding” from 1991 TWI patent [3]
Aluminum proved to be one of the easiest engineering materials to join with FSW and was the first to be joined in an industrial process [57,58]. Other researchers were interested in the possibility of joining harder materials and began looking at the possibility of joining steel with FSW [59]. The main hurdle in developing production processes for these materials is the development of a tool able to withstand the mechanical loads and elevated temperatures required. Materials such as 316L [60], HSLA-65 [5], Al-6XN [61], and Ti-6Al-4V [62] have been welded by FSW in limited quantities. A polycrystalline cubic boron nitride tool has shown promise of being able to stir these materials while maintaining a long tool life [60]. Molybdenum and tungsten alloys have also been reported to have some degree of success in FSW of hard materials [63].
2.5.1 Terminology While some terminology for the FSW process is evolving as the process is developed, there are some terms which have become standard. The tool is composed of a shoulder
47 and pin; the pin being of lesser diameter than the shoulder. As seen in Figure 2.18, the workpieces being joined by the weld are said to be on either the retreating or advancing side of the weld. The workpiece for which the direction of tool rotation and the direction of tool travel relative to the workpiece are the same is said to be on the advancing side of the weld. When the direction of tool travel relative to the workpiece is opposite the velocity of tool rotation, the workpiece is said to be on the retreating side of the weld.
Advancing Side
Joint
Retreating Side Tool Rotation
Figure 2.18 Plan view of FSW showing accepted terminology
2.5.2 FSW Characterization 2.5.2.1 Weld Regions There has been a great deal of work on characterizing the microstructures developed in friction stir welds, most of it focusing on aluminum. The result of a friction stir process is two major regions: a thermomechanically affected zone (TMAZ), and the heat affected zone (HAZ). The TMAZ is affected by both the heat caused by the friction of the tool and the severe stresses caused by the stirring process. The HAZ in a friction weld is similar to the HAZ developed in fusion welding processes. The HAZ does not undergo any mechanical deformation and any changes to the microstructure are entirely dependent on
48 time and temperature relationships such as heating rate, peak temperature, and cooling rate. There is some disagreement about the terminology of the weld. Some have referred to the TMAZ as a Heat and Deformation Affected Zone (HDAZ) [64]. Some divide the TMAZ into separate regions, one which is directly associated with the passing of the tool pin and undergoes dynamic recrystallization, another defined by material which is heated and plastically deformed, but not to the point of recrystallizing. The recrystallized region at the center of the weld is referred to as the Stir Zone (SZ) by some [64] and the nugget [65] by others. Those who refer to the stir zone as a separate region call the surrounding region the HDAZ while others have argued that the dynamically recrystallized region at the centerline of the weld is part of the TMAZ [66,67].
2.5.2.2 Flow Visualization One challenge which confronted researchers trying to better understand the effects of the spinning tool on the stirred material was determining the how the plasticized zone flows. One of the first published studies aimed at giving insight to the movement of material during FSW was by Colligan [68]. His novel method of studying material flow was to machine a small groove into one of the abutting faces of the plates to be joined and fill it with steel shot. By machining the groove to various depths, the position of the “tracer” material relative to the welding tool pin was varied. While making the weld, the forward progression of the tool was stopped so that the path of the tracers around the tool, as well as their final position, could be ascertained. After making a weld the joint was radiographed to reveal the distribution of the tracer material around the tool and in the weldment. Figure 2.19 shows an example of the results presented by Colligan.
49
Figure 2.19 Results of radiographic analysis performed by Colligan [68]
50 From this work, Colligan concluded that much of the material affected by the tool pin is not stirred, but rather extruded around the pin. The material that was stirred was forced down by threads on the pin and deposited in the weld nugget, while the extruded material moves up and around the pin on the retreating side of the welding tool. One drawback to this method is that the steel shot used to determine material flow is harder than the surrounding aluminum and may have an effect on the stirring of the weld material. Work by researchers at the University of South Carolina used an aluminum alloy of different composition than the base material placed into machined notches in the faying surfaces of the joint to visualize material flow [65,69]. The 5454 alloy markers were placed at various predetermined positions along the joint to be welded in 2195 base material. After welding, the top surface of the weld was etched to reveal the marker flow. After digital images of the etched surface were taken, the surface was milled down 0.25mm and re-etched. This process was continued so that successive digital images could be built up to form a three-dimensional picture showing the resulting flow of material induced by the welding process.
Figure 2.20 Schematic of marker placement used by Reynolds et. al.[69]
51 Reynolds and his co-workers determined, like Colligan, that the FSW process is an extrusion process. The rotating tool produces the heat necessary to reduce the local flow stress of the material while the shoulder, backing plate, and surrounding cold material contain the extruded material which flows around both sides of the pin to fill the cavity being vacated by the moving pin. The non-plasticized region around the extruded material was referred to as a moving “extrusion die” by Reynolds [69]. The plasticized body of material which is being extruded has been referred to as the “third body” [59,66]. London and his fellow researchers utilized a novel technique [70] to determine whether the extruded material in a FSW nugget was extruded around both sides, as suggested by the work of Reynolds [69] or if Colligan’s assertion that material moved around the advancing tool pin to be deposited on the retreating side of the weld [68]. London used a series of lamellae, thin sheets pressed together, with the surfaces of the sheets parallel to a normal butt joint interface. The welding process was stopped mid- weld and the sheets sectioned to examine the interfaces just ahead of the tool pin. The researchers determined that the material directly in the pin path flows from the advancing side, around the leading edge of the tool pin, to the retreating side. London also utilized Al-SiC composite markers implanted in the faying surface of plates to study the flow of the welded material. Welds made in plates with markers were sectioned to reveal the flow of the marker material around the pin. The marker material also appears to be stirred around the pin leading edge and some of the material was reported to have traveled around the pin more than once before being deposited.
52
Figure 2.21 London et al method of using lamellae to study material flow (above) and a resulting cross-section showing lamellae interfaces and tool pin. [70]
2.5.3 Modeling of FSW There have already been attempts at modeling different aspects of FSW in attempts to better understand and predict the effects of variables in the process. Some have been simple models focusing on thermal analysis [71-73], while others have focused exclusively on material flow [74]. Others have tried to incorporate both the thermal and mechanical analysis into a robust model [75-77]. It has been generally agreed that the tool shoulder is responsible for the majority of the heat generated in the welding of thin sheet [71-73], and models which include the pin as a heat source vary only slightly from models that ignore it [76]. The heat generated in
53 these models is estimated as the power required to overcome the frictional forces at the tool/material interface. The diameter of the pin tool has little effect according to these models. These models also suggest that there is a maximum temperature above which the welding process will not proceed because the formation of liquid films will result in a loss of friction [75]. Two of the thermal models were used to predict resulting hardness of stir welds in aluminum with reasonable accuracy [71,72]. Time-temperature relationships determined from isothermal hold tests were used to estimate hardness values for one thermal model [72]. The other model used predicted stable and metastable solvus boundaries for strengthening precipitates to estimate the hardness [71]. The flow of material around the pin has been modeled by Reynolds et. al. as an incompressible, non-Newtonian fluid flowing in a laminar condition past a rotating cylinder [74]. Interestingly, this model showed that the material will flow across the front of the pin to the retreating side of the weld before being deposited behind the tool pin.
2.5.4 Physical Simulation of FSW In published literature there are, at present, two reports on physical simulation of friction stir welding [9,78]. Work performed at the Naval Surface Warfare Center on HSLA-65, by Forrest et al. [9], in Gleeble hot compression tests has been carried out to simulate the microstructures developed in the TMAZ outside the stir zone. Short bars of HSLA-65 were resistively heated to the desired temperature before being deformed by compression along their axis. Data provided from this simulation was used in preliminary development of a computer model for FSW of HSLA-65. The researchers determined that axial compression with their testing apparatus could not achieve the strains and rates necessary to simulate the stir zone. The other work on simulation of FSW involved a hot torsion experiment for simulation of stir zone microstructures in aluminum alloys [78]. Samples were inductively heated and held at temperature for 2 minutes before being strained at a relatively low rate of 0.005 s-1. When the desired amount of strain was achieved, the sample was quenched with a water spray. This hold time at peak temperature was considerably longer than those reported in published work of 54 thermocouple analysis on actual aluminum welds [79,80]. The water quench used would impart a far greater cooling rate than that published in the same papers. Also, the applied strain rate was significantly lower than the 10 s-1 calculated by Jata and Semiatin [81]. The authors of the hot torsion study concluded that plastic strains greater than 20 were necessary for the simulation of stir zone type microstructures in aluminum alloys.
2.6 The Gleeble
The Gleeble is a thermomechanical simulator which was developed at RPI for the simulation of fusion weld heat affected zones [82]. The most recent Gleebles have fully integrated digital control loops and offer much better control and resolution than early simulators. Electrically conductive samples are heated by resistive heating while temperature is controlled by a feedback loop monitoring either thermocouples or an infrared pyrometer. Well developed models for fusion welding allow simulation of HAZ regions based on parameters such as weld heat input, plate thickness, and distance from the weld centerline. A mechanical system consisting of a hydraulic piston attached to one end of test specimens allows for combined simultaneous thermal and mechanical simulations. The newest Gleeble is capable of exerting 20 tons of static force in tension and 10 tons in compression and can achieve displacement rates of 2 meters per second [83]. This allows the system to be used for elevated temperature mechanical testing. The hydraulic ram system can utilize feedback from a load cell, ram displacement, or one of a series of extensometers.
2.6.1 Gleeble Hot Torsion The most recent addition to the Gleeble is the torsion mobile conversion unit (MCU). The torsion MCU adds a hydraulic motor to the system while maintaining the tension/compression and thermal parts of the system. A torque cell provides accurate torque measurements during hot torsion tests. An integrated optical pyrometer provides thermal feedback, allowing for rotation of the sample, which would not be possible with
55 thermocouples. Also integrated into the testing chamber of the torsion MCU are quench heads for quenching samples after deformation. The advantage of the torsion MCU over the standard tension/compression MCU is the ability to create high strains and strain rates. The hot torsion system was developed for simulating the high strains and hot deformation developed in the rolling process. Shear strain developed by twisting a sample is governed by the following equation:
r ⋅θ γ = l where r is the radius of the sample, θ is the rotation in radians, and l is the gage length of the sample [84]. Since the shear strain varies with radius, the calculated strain is valid at the outer surface of the sample. Shear strain can be converted to equivalent strain by dividing the shear strain by the square root of 3, as shown in the equation below.
γ ε = 3
The standard Gleeble hot torsion sample has a 14mm diameter and the reduced 10mm diameter gage section in the center. A schematic of the standard sample with labeled dimensions is provided in Appendix A. The dimensions of the sample were designed to give identical cross-sectional area along the length, which results in a more uniform temperature in the gage section. The strain developed in the specimen can be altered by changing the number of revolutions or the length of the gage section. The collets which hold the sample in the hot torsion MCU are designed for a 14mm diameter rod. The total length of the sample cannot be changed as this would cause a misalignment of the integrated optical pyrometer.
56 2.7 Single Sensor Differential Thermal Analysis
In standard differential thermal analysis (DTA) a small volume of an inert reference material, such as Al2O3 is heated along with a small volume of the material to be studied. The two materials are heated at the same time with thermocouples attached to each. Whenever the material under study experiences a phase transformation, the associated latent heat of transformation causes a difference in output from the thermocouples. This technique is commonly used to measure the equilibrium phase transformation temperatures for a variety of materials. Single sensor differential thermal analysis (SS-DTA) is a novel technique developed at The Ohio State University for in-situ measurement of thermal events, such as phase transformations, in welding and heat treating. It has been described in a series of papers by Alexandrov and Lippold [85-90]. What makes SS-DTA so unique is the lack of a reference material. A curve based on a mathematical model is fit to the recorded thermal data. Deviations of the recorded data from the fit model are used to determine transformation temperatures. The use of a single sensor, be it thermocouple or pyrometer, allows the use of this technique on bulk samples. Comparison of SS-DTA data to dilatometry on Gleeble specimens showed equal accuracy and better sensitivity to detecting phase changes [88]. It also allows the study of phase transformation behavior in applications such as welding, where there are extremely high heating and cooling rates. Continuing work on SS-DTA shows many exciting possibilities.
2.8 Electron Backscatter Diffraction Analysis
Electron backscatter diffraction (EBSD) analysis or orientation imaging microscopy (OIM) is a technique for determining the orientation of individual grains in bulk samples. This gives EBSD a distinct advantage over transmission electron microscope orientation analysis in ease of sample preparation (bulk vs. thin foil) and the size of the area which may be analyzed (anywhere on polished surface vs. thinned region in foil). When the focused electron beam of a scanning electron microscope impinges on the surface of a polished, bulk sample which has been tilted to a sufficiently large angle (70º 57 is common), the beam is scattered elastically in all directions. The scattered beam interacts with the first few layers of thickness in the crystal lattice. If the electrons through the lattice just the right angle, called the Bragg angle (θB), the electrons will be reflected. The Bragg angle may be calculated from Bragg’s law, which is:
λ = 2d sin(θB ) where λ is the wavelength of the beam and d is the spacing between planes in the crystal lattice. The many crystallographic planes within a single grain will each reflect electrons at specific angles. If a phosphor screen is placed close to region where the beam is deflecting, a series of lines, unique to the orientation of the grain being struck, will appear on the screen. Distortion of the lattice will affect the width and sharpness of the lines. Figure 2.22 shows an example of diffraction patterns captured from two different crystals in an iron sample.
Figure 2.22 EBSD patterns captured from crystals of different orientation in a polycrystalline iron sample
58 Modern personal computers have made interpretation of these patterns trivial. A digital camera focuses on the phosphor screen and captures images of the pattern. A computer compares the pattern to theoretical patterns for the expected phase and is able to determine the orientation of the crystal upon which the beam is impinging. The time taken for a computer to analyze the data from a single point can be less than 0.02 seconds. By stepping the beam across the region of interest, a map of orientation for each point at which the beam stops may be created. The data may be used to determine relative strain within a single crystal, relative angle between adjacent crystals (boundary angle), and to identify phases in a multiphase, polycrystalline sample.
2.9 Response Surface Methodology
The response surface method (RSM) is a means of determining the effects on the measured response of a system [91]. A designed experiment has input variables which are controlled by the scientist or engineer controlling the experiment. Data recorded from the experiment is labeled as the response. An example would be a welding process in which the input variables (often termed independent variables or factors) are the weld process parameters: voltage, current, and travel speed; and the weld width is the response. Through statistical regression analysis, a first or second order polynomial which relates the independent variables to the response may be formulated. A graphical representation of the polynomial often results in a multi-dimensional surface, from which the term “surface response” is derived. It is possible to have more than one response for an experiment. In the example given, the example response was the width of a weld. A second response for the same experiment could be the height of the weld above the plate.
2.9.1 Coded variables RSM work often uses coded variables, which are dimensionless variables representing the range over which the independent variables are being used. Coded variables are normally defined to have a mean value of zero. If a designed experiment
59 were conducted with test temperatures of 1000°C, 1250°C, and 1500°C, the conversion to coded units would yield -1, 0, and 1 respectively.
2.9.2 Types of Experiments 2.9.2.1 Central Composite One of the most commonly used design experiment which may yield a response surface is the central composite design. This design was first described by Box and Wilson in 1951 [92]. Typically, this experiment is used to fit a second order polynomial and requires three levels of each variable (ie. a high, medium and low value). For an experiment with k variables there is also a parameter α, which may vary from 1 to √k. The experiment is designed with multiple runs at the centerpoint, where all variables are at their medium value (ie. 0 in coded units). This center point is enclosed by runs at combinations of the maxima and minima (ie. 1 and -1 in coded units). There are also axial points which are made by setting one variable to α, in coded units, while holding the other variables to 0. Figure 2.23 gives an example of a central composite designed experiment for two variables.
(√2,0) (-1,1) (1,1)
(0, -√2) (0, √2) (0,0)
(1,-1) (-1,-1) (-√2,0)
Figure 2.23 Central composite design for k=2 and α=√2. 60
One drawback of the central composite design is the number of runs required as the number of variables increases. Central composite designs with repetition of the centerpoint for 2, 3, and 4 variables require 14, 20, and 30 runs respectively.
2.9.2.2 Low Cost Response Surface Method The low cost response surface method (LCRSM) is a relatively new design proposed by Allen and Yu [93]. The low cost of the experiment is related to the decreased number of runs required as compared to a central composite design. An LCRSM with 3 factors requires only 9 runs and a 4 factor LCRSM requires just 14 runs compared to the 30 required for a central composite experiment with the same number of factors. Allen and Yu showed in their proposal for the LCRSM that it generated lower model errors than other commonly used experiment designs. The design of a four factor LCRSM in coded units is shown in Table 2.2. The variables are designated as A, B, C, and D.
Run A B C D 1 -0.5 -1 -0.5 1 2 1 1 -1 1 3 -1 1 1 1 4 1 -1 -0.5 -0.5 5 0 0 -1 0 6 0 1 0 0 7 -0.5 -1 1 -0.5 8 -1 0 0 0 9 1 1 1 -1 10 -1 1 -1 -1 11 0 0 0 -1 12 0.5 -0.5 0.5 0.5 13 0.5 -0.5 0.5 0.5 14 0.5 -0.5 0.5 0.5
Table 2.3 LCRSM with four factors in scaled (-1,1) units. (After Allen and Yu [93]) 61 2.9.3 Determining Significance After randomizing the run order and completing all the runs in the design, the experimenter has a measured response for each experiment. In general, an experiment with two variables, A and B, and measured response, y, a second order polynomial (model) of the form:
2 2 y = β + β A + β B + β AB + β 2 A + β 2 B 0 A B AB A B is fit to the data; easily done with a computer and software such as Microsoft’s Excel program. The model includes coefficients for: the intercept, β0; linear influences, βA and
βB; interaction between and factors, βAB; and second order influences, βA2 and βB2. While this is generally the form of the model, the suggested method for LCRSM is to fit a series of models that neglect the interaction and second order values of one factor, a different factor for each model, and choose the model which exhibits the lowest sum of squares error (it is common to leave off the word error). The sum of squares is the squared differences between the average of the y values and the actual y values. The next step, for all designs, is to determine the level of confidence that the curve fit to the input data is significant. The first statistical value which is inspected is the coefficient of determination, R2, which is calculated as the regression sum of squares divided by the total sum of squares. The regression sum of squares is the difference between the total sum of squares and the squared difference between the predicted y values and actual y values. The closer R2 is to 1, the better the correlation between the predicted value of the model and the actual data. Adding additional variables to the model will always increase R2, regardless of whether the variable is significant or not. It is possible then to have a model with a high value of R2 which does a poor job of estimating the mean response. Testing model significance by use of the F-test is also referred to as analysis of variance (ANOVA). The F-test is a statistical test to determine whether the degree of correlation between the model and the data could happen by chance. To do this, the degrees of freedom of the system are first determined. The degrees of freedom is calculated as the number of runs 62 in the designed experiment minus the non-collinear columns in the model (which is 5 in our example model: βA, βB, βAB, βA2, and βB2) minus 1. If our example model were being developed from a 14 run experiment, the degrees of freedom would be equal to 8. The observed F value (FO) would be equal to the regression sum of squares times the degrees of freedom divided by the product of the residual sum of squares and the number of non- collinear columns in the model. This FO is then compared to a critical F value (Fcrit) which can be looked up in a statistical table. The Fcrit value is the value for FO that might happen purely by chance for a system with a defined degree of freedom. If the calculated
FO is larger than Fcrit then the model is shown to be statistically significant. The next test which may be applied is a special F test which tests the significance of each coefficient in the model. This special test is called a t-test. The t value is calculated as the value of a coefficient divided by the standard deviation for the coefficient. As with the F-test, there is a critical t value, tcrit, above which the coefficient is considered significant. The tcrit value for a given significance factor (usually 0.05) and degrees of freedom may be looked up in a t table. It should be noted that the t-test checks the significance of a coefficient when all the other coefficients in the model are included. If a coefficient is removed, the t values for each coefficient must be recalculated for the new degrees of freedom and standard deviation.
63
CHAPTER 3
OBJECTIVES, EQUIPMENT, & MATERIALS
3.1 Project Objectives
The purpose of the proposed work can be broken down into three distinct objectives; 1. Examine the thermomechanical effects of the friction stir weld process on steel using traditional metallography, markers, and embedded thermocouples. 2. Develop a Gleeble test capable of physically simulating the steel FSW microstructures. 3. Develop a conceptual model for the thermomechanical effects of the friction stir welding process in steel by combining the data from the welds and Gleeble simulations. The data and model generated from the second and third objectives is to be used by researchers at the Naval Surface Warfare Center to improve the mathematical model of FSW they have been developing [9].
3.2 Equipment
Achieving these objectives requires a considerable number of machines and systems for simulation, welding, and measurement of data. Major equipment used follows in the following sections and information on all the equipment is available in Appendix B.
64 3.2.1 Friction Stir Welder The friction stir welding machine used in this study was a large gantry type milling machine which has been converted by the Edison Welding Institute (EWI) into a friction stir welder. An added water rotary union provides for cooling of the tool. A picture of the equipment is shown in Figure 3.1 below.
Figure 3.1 EWI Friction Stir Welding Machine #2
This machine is capable of developing 50-hp at the spindle and can rotate at speeds up to 5000rpm. The mill table can move at travel speeds up to 125 ipm and the welding envelope is 52 inches by 52 inches. The spindle is instrumented with transducers which allow control of the load on the tool in the Z and X directions. The entire machine is controlled by a hardware and software package developed at EWI.
65 3.2.2 Gleeble 3800 The Gleeble used in this study was a 3800 model housed in the Welding Engineering Department of The Ohio State University. This particular machine has both the Pocket Jaw MCU and Hot Torsion MCU available to connect to the system. The system used building process water for cooling during this study. A complete description of the machine functions and capabilities can be obtained from the manufacturer [94].
3.2.3 Electron Microscope All electron microscopy was performed at the Campus Electron Optics Facility in the Materials Science Engineering department of The Ohio State University. Scanning electron microscope images were obtained with a Philips XL-30 ESEM. Electron backscatter diffraction patterns were collected using the Philips XL-30 ESEM with EDAX TSL OIM™ Collect software. Analysis of collected backscatter data was performed with the EDAX TSL OIM™ Analysis package.
3.2.4 Optical Microscopes A Nikon Epiphot binocular microscope with a PAXcam digital camera attached to it was used for all optical microscopy performed in this study. PAX-it!™ software (versions 4, 5, and 6) was used for capture of digital images from the camera. Spatial measurements of features in micrographs were also made with the PAX-it!™ software [95].
3.3 Materials
Two different materials were chosen for use during this project: Armco iron and HSLA-65. The goal was to use the less complex iron alloy to develop a simulation technique for the HSLA-65, which there was less of.
66 3.3.1 Armco Iron The high-purity iron used for this project came in the form of round stock with two different diameters. One of the materials was a bar approximately 6 inches (152.5 mm) in diameter and the other an iron rod which was 14 mm in diameter. The two irons had differing initial grain size and hardness.
6 inch 14 mm Property (152 mm) iron rod iron bar Grain Size (ASTM#) 10.5 5.2 Average Grain diameter (μm) 88 125 Hardness (Hv) 160 110
Table 3.1 As received properties for irons used in study
Both materials were composed of equiaxed ferrite grains with small carbides scattered in the matrix (Figure 3.2). The slightly higher carbon content of the 6 inch bar resulted in pearlite colonies forming at some of the ferrite grain boundaries (see Figure 3.3). The chemical compositions are given below in Table 3.2.
14mm 6 inch Element iron rod iron bar C 0.020 0.029 Mn 0.300 0.300 Si 0.050 0.013 S 0.018 0.014 P 0.007 0.011
Table 3.2 Chemical composition (wt%) of iron used in study
67
Figure 3.2 As received structure of the 14mm iron rod.
Figure 3.3 Colony of fine pearlite in 6 inch iron bar stock
68 3.3.2 HSLA-65 The HSLA-65 plate used in this study was provided by the Naval Surface Warfare Center Carderock Division (NSWCCD). The plate was provided in both 0.25 inch and 0.5 inch thicknesses. The plates had similar grain size as shown in Table 3.3.
Property 0.25” plate 0.5” plate Grain Size (ASTM#) 13.1 12.9 Average Grain diameter (μm) 79 80 Hardness (Hv) 208 181
Table 3.3 As received properties for HSLA-65 plates used in study
Samples of both plates were sent for analysis which yielded the chemical compositions shown in Table 3.4.
Element 0.25” plate 0.5” plate C 0.085 0.071 Mn 1.33 1.44 Si 0.218 0.286 S 0.007 0.007 P 0.017 0.008 Cr 0.058 0.023 Ni 0.056 0.009 Mo 0.010 0.010 Cu 0.046 0.021 V 0.040 0.071 Nb 0.034 0.034 Al 0.035 0.035
Table 3.4 Chemical composition (wt%) of HSLA-65 used in study.
69 As can be seen in the table, the compositions of the two plates were within the specifications for ASTM A945 grade 65 steel (see section 2.4.1). The higher carbon content may explain the higher hardness of the 0.25” plate. Both plates reveal fine grained ferrite and fine pearlite in a banded structure caused by the rolling process (see Figure 3.4).
Figure 3.4 Microstructure observed in as received HSLA-65 (0.5” plate shown)
70
CHAPTER 4
IRON FRICTION STIR WELDS
A series of 6 friction stir welds was made in 0.25 inch thick plates of Armco Ingot Iron. The process parameters were “tweaked” between and sometimes during welds in an attempt to obtain welds that looked good; that is with no visible galling or lack of fusion. After parameters for a successful weld were found, welds were attempted with thermocouples placed at various places on the plate as well as on plates with marker material embedded along the weld path. All welds were made with a tungsten-rhenium tool with 25% rhenium. The tool had a featureless, straight pin 0.375” in diameter, 0.180” in length, and a 0.75” diameter shoulder. Following welding, the welds were sectioned transverse to the weld, polished by standard procedure to 0.05 μm, and etched with 2% nital. Additionally, the hole left by retracting the tool at the end of the weld was sectioned both longitudinally and transversely. Some welds were prepared for EBSD by electro-polishing in Struers A2 solution (see Appendix B for chemical composition) after mechanical polishing to 0.05 μm.
4.1 Armco Ingot Iron FSW Procedure
Plates for friction stir welding were machined from the 6” bar stock. Dimensions for the plates were 3.5” x 6” x 0.25”. Welds were made down the center of the plates in some instances and along the boundary between abutted plates in others. The composition and microstructure of the material have already been described in Chapter 3 (Table 3.1 and Figure 3.3) 71
4.1.1 Process Parameters Three welds were first made in the iron plates, with some tweaking of process parameters each time to obtain a weld with no visible galling or lack of fusion. Table 4.1 shows the weld schedule used for each of the ingot iron welds.
Plunge Dwell Weld Plunge Rate Weld Travel Weld Rotation Rotation Rotation (ipm) Speed (ipm) (rpm) (rpm) (rpm) Fe-1 0.2 450 350 6 350 Fe-2 0.2 450 200 8 200 Fe-3 0.2 450 400 8 400 Fe-4 0.2 450 400 8 400 Fe-5 0.2 450 400 8 400 Fe-6 0.2 450 400 8 400
Table 4.1 Weld Schedule development for Armco ingot iron FSW
After plunging the tool into the plate enough for the shoulder of the tool to make contact with the surface of the plate, there was a dwell time to allow the tool to develop some additional heat before traversing the plate. The first weld had a rough surface where the tool had passed and visible galling on the retreating side of the weld. The second weld made, labeled Fe-2, looked very similar to the first weld and had significant galling on the retreating side of the weld. The process parameters used for the third weld yielded a smooth surface finish with particle like flash that could be brushed from the surface of the plate. The process parameters used for the third weld were used for successive welds made in the ingot iron.
4.1.2 Thermocouple Instrumented Plates Two attempts at measuring thermal history at various points on the plate were made. Welds designated Fe-4 and Fe-6 both had eight type-K thermocouples welded to them for 72 acquiring temperature data during welding. Data was acquired at 500 Hz and collection began when the tool started rotating before being plunged. The native acquisition system of the FSW machine begins the moment the tool starts rotating and the desire was to correlate the data collected from both systems. Figure 4.1 shows a schematic of the plate and thermocouple placement as viewed from the top of the plate. Thermocouples numbered 1 to 3 on the plate with weld Fe-4 were all attached to the plate in 0.0625” diameter holes drilled to a depth of 0.12”. This positioned these three thermocouples at the center of the plate thickness. The remaining thermocouples were attached to the top surface of the plate. Numbers beside the four- pointed stars represent the data acquisition channel for the thermocouple at that position.
1 4 0.25” 0.25” 2 5 0.25” 0.25” 3 6 0.5” 0.5” 7
8 Weld Direction
2.5” 1.5”
Figure 4.1 Schematic of thermocouple placement on weld Fe-4 (top view)
Thermocouples on the plate with weld Fe-6 were all attached to the plate from the bottom. Figure 4.2 shows a schematic of the plate and thermocouple placement as viewed from the bottom of the plate. Numbers beside the four-pointed stars represent the data
73 acquisition channel for the thermocouple at that position. Channels 1 to 4 were attached in holes drilled to just below the surface of the plate. The channel 5 thermocouple was attached to the bottom surface of the plate. The thermocouples for channels 6, 7, and 8 were attached in 0.0625” diameter holes drilled to a depth of 0.13” from the plate bottom. The holes for the thermocouples were drilled at 0.5” intervals with the first hole on the center-line and the succeeding three holes drilled at 0.125” increments away from the center-line. This was done to place the outermost thermocouple beneath the outer edge of the tool shoulder. The next four holes (channels 5 to 8) were drilled at similar increments to the first four (see Figure 4.2).
Weld Direction
5 1 7 6 3 2 8 4
0.5” 0.5” 0.5” 0.5” 0.5” 0.5” 0.5” 1.5”
Figure 4.2 Schematic of thermocouple placement on weld Fe-6 (bottom view)
Accommodation of the thermocouple wires under the plate was made possible by using a 0.5” thick steel plate with holes to match the holes in the plate to be welded and grooves machined for the wires to run in. A picture of this special backing plate is shown in Figure 4.3.
74
Figure 4.3 Backing plate for accommodating thermocouple wires attached to the bottom side of the workpiece (bottom view).
Acquisition of thermal data was made with a secondary system. To coordinate thermal data with loading and tool position data collected by the friction stir welding machine, thermal data acquisition was not initiated until the tool began turning; the moment data collection begins for the friction stir welding system used. Thermal data was collected at 500Hz in an attempt to utilize single sensor differential thermal analysis to ascertain phase changes and any other thermal affects in the weld.
4.1.3 Marker Embedded Plates The success of placing marker materials in the path of the friction stir tool to determine material flow, as shown by other researchers in aluminum alloys[68-70], led to a desire to try implementing marker material in friction stir welds made in iron. One plate of the ingot iron was prepared with 308 stainless steel and 304 stainless steel markers embedded at places along which the weld would traverse. There were six markers in the
75 plate. Three of the markers were 0.25” diameter 304 stainless steel rod and the other three wires were 0.0625” diameter 308 stainless steel welding filler wire. Figure 4.4 below is a schematic of the locations of the markers before the welding tool traversed the plate. Following welding the plate was fusion welded around its perimeter to a 1” thick steel backing plate with the top of the weld visible. The top surface of the plate was cleaned with acetone and etched with 10% nital. After taking a digital picture of the etched surface, a layer 1” wide and 0.01” deep was machined from the plate with a vertical mill. The milled surface was etched with the 10% nital and another picture of the surface was captured.
76 Weld Direction
4.0” 3.5” 3.0”
2.0” 1.5” 1.0”
Figure 4.4 Schematic of bottom view of Fe-5 plate prior to welding
77 4.2 Armco Ingot Iron Friction Stir Weld Results
4.2.1 Microstructures Welds made in the iron plate had a refined grain size in the stir zone. There was not a visible difference between the stir zone microstructure observed for the different welds. Figure 4.5 is an example of this refined ferrite microstructure.
Figure 4.5 Typical stir zone microstructure observed in stir zone of iron welds
The ASTM grain size number in this region for all the welds averaged 9.5. There was no apparent correlation between the changes in the welding process parameters and the grain size, and the number of samples run was too small to check for statistical significance. Moving out from the center of the weld, the next structure encountered was a region of bimodal ferrite grains, having both refined ferrite grains and large ferrite grains. Figure 4.6 gives an example of this region from one weld.
78
Figure 4.6 Mixed ferrite grain size region observed in iron friction stir welds
The transition from the bimodal region to the large grained base metal was marked by a narrow region of ferrite grains which exhibited a dense subgrain boundary network. Figure 4.7 shows this region and Figure 4.8 shows a closer view of the boxed area shown in Figure 4.7
79
Figure 4.7 Narrow region of subgrain boundary networks in friction stir weld (arrow points along approximate center of region). Boxed region shown in Figure 4.8
Figure 4.8 Magnified view of boxed region in Figure 4.7 showing subgrain boundary region.
80 4.3.2 Thermal Data Data from the two thermocouple instrumented plates (Fe-4 and Fe-6) was not as plentiful as had been hoped. The first attempt showed that the thermocouples on the surface outside the shoulder did not heat above 600ºC. Figure 4.9 shows a plot of the collected data for channels 1, 2, and 3 in weld Fe-4.
Fe-4 Termocouple Data
600
500 Ch1 Ch2 Ch3 400
300
Temperature (°C) 200
100
0 0 100 200 300 400 500 600 Time (s)
Figure 4.9 Thermocouple data collected from weld Fe-4 collected at the plate surface outside the tool path
The second attempt, with the thermocouples coming from the bottom into holes drilled into the stir zone did not yield acceptable results in the stir zone due to the thermocouples and plasticized material being extruded into the holes in the bottom plate. Figure 4.10 gives an example of some of the data acquired from the holes drilled from the bottom setup. Channel 1 begins to increase in temperature after channel 2, which is 81 expected from their positioning. However, the peak temperature for channel 1, which was on the centerline of the tool is expected to be near or above that acquired by channel 2. This data was clearly unreliable and not in order with temperatures reported by other researchers [63,96]. While the data may not have been useful, the fact that this technique did not produce reliable results is important and included here for future researchers that they might not waste time attempting the same procedure.
Fe-6 Thermocouple Data
1000
900
Ch1 800 Ch2
700
600
500
400 Temperature (°C) 300
200
100
0 65 75 85 95 105 115 125 135 Time (s)
Figure 4.10 Thermocouple data collected from weld Fe-6, where thermocouples were forced out of the plate as the tool approached
While the data collected from these welds were not useful in determining phase transformation effects, there was useful information. The heating rate for the channel 2 thermocouple in weld Fe-6 was just over 500ºC/s at its steepest point. Additionally, the
82 cooling portion of this data showed a decrease in the heating rate at about 730ºC, around the temperature one would expect a phase transformation to occur.
4.3.3 Marker Data The marker experiments yielded valuable information. Acquisition of load data from the friction stir welding machine showed spikes in the load on the tool in the x-direction when the 0.25” markers were encountered. This can be seen in Figure 4.11.
Fe-5 FSW Machine Data
1400 9
8 1200
7 1000 6 ZWload Xload 800 5 RPM Xfeed 4
Load (lbf) Load 600
3 400 Rate (in/min) Feed Tool 2
200 1
0 0 00.511.522.533.544.55 Weld Distance (in)
Figure 4.11 Machine data collected from friction stir weld in iron with markers
The three peaks in the x-direction come at 0.5” intervals, which was the distance between consecutive markers. The loading in the z-direction, or resistance to the downward force of the tool on the surface of the material shows some increase when the 0.0625” markers were met by the tool and an increase of much greater magnitude where 83 the large markers were encountered. Figure 4.12 is shown for comparison to loading in a weld made without markers.
Fe-3 FSW Machine Data
1400 8
7 1200
6 1000 ZWload Xload 5 800 RPM Xfeed 4
Load (lbf) 600 3
400 (in/min) Rate Feed Tool 2
200 1
0 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Weld Distance (in)
Figure 4.12 Machine data collected from friction stir weld made without markers
After examining the load data it appeared the smaller markers were less likely to have impacted the flow characteristics of the iron. Examination of the serial sectioning work was therefore focused on the 0.0625” diameter markers. The milled sections of the marker embedded plate showed that the material moves in the direction of tool rotation to the retreating side of the weld before being deposited behind the tool. At the surface of the weld, where the shoulder was in contact during welding, the marker material was not discernable. Marker material near the top of the weld, where the shoulder has an influence, appeared to have traveled a greater distance and was deposited further back than material which was nearer the bottom. Figures 4.13
84 and 4.14 show the position of marker material relative to the marker position in a section near the top of the weld and a section near the bottom of the weld respectively.
Weld Direction Rotation
Figure 4.13 Section of iron plate near plate surface showing original and final position of 0.0625” markers (advancing side of weld on top)
Weld Direction Rotation
Figure 4.14 Section of iron plate near bottom of plate showing original and final position of 0.0625” markers (advancing side of weld on top) 85 For the 0.0625” marker on the retreating side of the weld, outlines of the marker position at 0.010” increments in depth were sketched. The individual sketches were drawn in the 3D-modeling software Solid Edge®. This allowed the marker sketches to be drawn on successive planes and displayed as a wireframe plot. It also enabled representation of the tool path, tool profile, and original marker position for comparison to the sketches of the final marker position. Figures 4.15 through 4.17 depict images created with the 3D software which show the initial marker position and the position of the marker material after welding.
Weld Direction Rotation
Edge of Pin
Edge of Shoulder
Figure 4.15 Plan view of marker material final position with outline of tool path and original position of pin (grey circle)
86
Figure 4.16 Transverse section view of final marker position with original position of marker pin and outline of tool profile (weld direction into page)
Figure 4.17 Longitudinal section view of serial section sketches and original pin position from retreating side
4.3.4 Electron Backscatter Diffraction Data A section from the retreating side of weld Fe-6 was analyzed using EBSD. The region of interest contained both the weld and the base metal. This region was chosen for the inclusion of the transition region between the base metal and the refined grains of the stir zone. Figure 4.18 shows the region mapped to show individual grains.
87 200 μm
Figure 4.18 Unique grain map across boundary between stir zone (right) and base metal (left) of weld Fe-6
The figure clearly shows a boundary between the large grains of the iron base metal and refined grains in the weld. Grains are determined by boundary orientation. The software was set to associate any difference in orientation of 15º or greater to be a boundary between unique grains. It is also possible to output the data as a map of orientation boundaries. Figure 4.19 shows a map of the grain boundary analysis. This map shows the network of subgrain boundaries which were seen with optical microscopy as depicted in Figure 4.8.
88 200 μm
Figure 4.19 Boundary map across stir zone (right) and base metal (left) of weld Fe-6
Two more methods of mapping were used for the weld. One is an inverse pole figure map, which assigns colors by orientation. Grains with similar orientation have similar color. Variations in orientation within a grain will result in changing shades of color. This type of map is shown in Figure 4.20. The fine and large grained regions are still apparent, however, the region which was shown in Figure 4.19 to have a network of subgrain boundaries appears to have considerable variation in orientation within the grains. The mottled coloring of individual large grains is evidence of this.
89 200 μm
Figure 4.20 Inverse pole figure map at boundary between weld and base metal on the retreating side of weld Fe-6
90 The final mapping method used was grain orientation deviation. This map assigns color to points within a grain based on their deviation from the orientation of adjacent points within the grain. As can be seen in Figure 4.21, the region of high subgrain density has considerable orientation deviation.
200 μm
Figure 4.21 Grain orientation deviation map at boundary between weld and base metal at retreating side of weld Fe-6
91
CHAPTER 5
HSLA-65 FRICTION STIR WELDS
A series of 6 friction stir welds was made in 0.25 inch thick plates of HSLA-65. As with the iron welds, the process parameters were “tweaked” between and sometimes during welds in an attempt to obtain welds that looked good; that is with no visible galling or lack of fusion. After parameters for a successful weld were found, welds were attempted with thermocouples placed at various positions on the plate as well as on plates with marker material embedded along the weld path. All welds were made with the same tungsten-rhenium tool used in the iron welds. Following welding, the welds were sectioned transverse to the weld, polished by standard procedure to 0.05 μm, and etched with 2% nital. Additionally, the hole left by retracting the tool at the end of the weld was sectioned both longitudinally and transversely. Some welds were prepared for EBSD by electro-polishing in Struers A2 solution after mechanical polishing to 0.05 μm (See Appendix B for composition of Struers A2 solution.
5.1 HSLA-65 FSW Procedure
HSLA-65 for friction stir welding was provided in plate form and was machined to match the dimensions used for the ingot iron plates. Dimensions for the plates were 3” x 6” x 0.25”. Welds were made down the center of the plates in some instances and along the boundary between abutted plates in others.
5.1.1 Process Parameters The parameters used in each of the six welds made in HSLA-65 are shown below in Table 5.1.
92
Plunge Dwell Weld Plunge Weld Travel Weld Rotation Rotation Rotation Rate (ipm) Speed (ipm) (rpm) (rpm) (rpm) HSLA-65-1 0.2 600 400 6 400 HSLA-65-2 0.2 500 350 6 350 HSLA-65-3 0.2 500 300 6 300 HSLA-65-4 0.2 450 300 6 280 HSLA-65-5 0.2 450 270 6 270 HSLA-65-6 0.2 450 270 6 270
Table 5.1 Weld Schedule development for HSLA-65 FSW
After plunging the tool into the plate enough for the shoulder of the tool to make contact with the surface of the plate, there was a dwell time to allow the tool to develop some additional heat before traversing the plate. The first weld appeared smooth on the surface, but showed galling on the retreating side of the weld, especially in the flash. The second HSLA weld looked very similar to the first weld, with the flash galling on the retreating side of the weld. The pin was sheared from the end of the tool after making about 2” of weld. Interestingly, the plates were still joined with only the rotating shoulder passing over the interface. The welded region following the pin break did not demonstrate galling in the flash. While making the third weld, the rotation speed of the tool was increased to nearly 400 rpm before being dropped to about 275 rpm. The flash associated with the drop in spindle speed formed a sheet and did not show the galled flash observed in the previous welds. The process parameters used for the third weld were used, with slight modification for the following welds made in HSLA-65.
5.1.2 Thermocouple Instrumented Plates A single plate of HSLA-65 was instrumented with thermocouples for data acquisition in the same manner described for the iron plates described previously. Thermocouples on the plate for weld HSLA-65-5 were all attached to the plate from the bottom. Figure 5.1
93 shows a schematic of the plate and thermocouple placement as viewed from the bottom of the plate.
Weld Direction
4 8 2 3 6 7 1 5
0.5” 0.5” 0.5” 0.5” 0.5” 0.5” 0.5” 1.5”
Figure 5.1 Schematic of thermocouple placement on weld HSLA-65-5 (bottom view)
Numbers beside the four-pointed stars represent the data acquisition channel for the thermocouple at that position. Channels 1 to 3 were attached in 0.0625” diameter holes drilled to a depth of 0.15” from the plate bottom. The channel 4 thermocouple was attached to the bottom surface of the plate. The thermocouples for channels 5 to 8 were attached in holes drilled to just below the top surface of the plate. In a pattern similar to that used for the Fe-6 Armco iron plate described previously. This was done so the same backing plate used to accommodate the wires could be used for the HSLA-plate. A second thermocouple instrumented weld was made in HSLA-65 using an entirely different configuration for thermocouple placement. Type-K thermocouples were again used; however the thermocouples used in this experiment were sheathed in a 0.0625” diameter Inconel 600 tube. Grooves 0.0625” in width and depth were machined into the top and bottom surfaces of the plate. The grooves were machined perpendicular to the planned tool path. Schematics of the groove placement in the top and bottom of the plate
94 are shown in Figures 5.2 and 5.3. Four holes were drilled through the plate to allow the bottom four thermocouples to be brought through the plate and connected to the data acquisition system. After pressing the sheathed thermocouples into the grooves, a center punch was used to deform the edge of the groove. This deformation effectively pinched the thermocouple and locked it in place. The welding parameters for this weld were the same as the previous thermocouple instrumented plate and are listed in Table 5.1 as HSLA-65-6.
Weld direction
Figure 5.2 Schematic of top view of plate machined for metal sheathed thermocouples
95
Figure 5.3 Schematic of bottom view of plate machined for metal sheathed thermocouples
5.1.3 Marker Embedded Plates Two of the HSLA-65 plates were prepared with 308 stainless steel markers embedded at places along which the weld would traverse. One plate had six markers, similar to the ingot iron plate with markers, as shown in Figure 5.4. The weld labeled HSLA-65-4 was made in this plate. This plate was etched, milled, and photographed in the same manner described previously for the ingot iron plate. The other HSLA plate had only three markers of 0.25” diameter rod as shown in Figure 5.5. The weld in this plate was labeled HSLA-65-5, which was one of the HSLA-65 welds made with thermocouples on the plate.
96 Weld Direction
4.0” 3.5” 3.0”
2.0” 1.5” 1.0”
Figure 5.4 Schematic of top view of HSLA-65-4 prior to weld
97 Weld Direction
4.0” 3.5” 3.0”
Figure 5.5 Schematic of top view of HSLA-65-5 prior to weld
98 5.2 HSLA-65 Friction Stir Weld Results
5.2.1 Microstructures The strain, high peak temperatures, and fast cooling rates destroyed the rolled ferrite and pearlite microstructure seen in the as received plates. The stir zone of the weld was characterized by a variety of Widmanstätten type ferrites as shown in Figure 5.6.
Figure 5.6 HSLA-65 stir zone microstructure showing a Widmanstätten ferrite microstructure
As one moves from the center of the weld toward the base metal, the length of the ferrite laths decreased. There was a transition from the microstructure in the center of the stir zone to a fine, equiaxed grain region. This transition region is shown in Figure 5.7. The fine grained region is shown in Figure 5.8 and an image showing the stir zone, fine grained region, and the base metal is shown in Figure 5.9.
99
Figure 5.7 Transition from Widmanstätten ferrite in stir zone (left) to fine, equiaxed ferrite (right)
Figure 5.8 Fine grain region seen at edges of stir welds made in HSLA-65
100
Figure 5.9 Overview of microstructural transitions in HSLA-65 weld (weld at left, retreating side)
5.2.2 Thermal Data The experiment to measure temperature with holes drilled through the bottom of the anvil plate yielded similar results to the experiment attempted in iron; the data was noisy and only one channel was smooth enough for processing. Figure 5.10 shows the data collected from a thermocouple 0.10” below the surface of the plate, in line with the outer edge of the tool shoulder on the advancing side of the tool.
101 HSLA-65-5 Channel 1 Data
700
600
500
400
300 Temperature (°C)
200
100
0 0 50 100 150 200 250 300 350 Time (s)
Figure 5.10 Thermocouple data collected from weld HSLA-65-5 just outside tool path
Data collected from the final friction stir weld, using sheathed thermocouples pressed into grooves in the plate proved to be the most productive means of measuring thermocouple data, with all seven channels acquiring data before and after the passage of the tool. Figure 5.11 shows the data acquired from this weld. The rapid heating rate, peak temperature, and cooling are observed at each thermocouple position.
102 HSLA-65-6 FSW Sheathed Thermocouple Data
Ch1 Ch2 1200 Ch3 Ch4 Ch5 1000 Ch6 Ch7
800
600 Temperature (°C)
400
200
0 50 100 150 200 250 300 Time (s)
Figure 5.11 Thermocouple data collected from weld HSLA-65-6
The peak heating rates seen at the top surface were about 600ºC/s and peak temperatures greater than 1250ºC. Temperatures on the weld centerline at the bottom of the plate reached 1000ºC. The thermocouple just outside the stir zone on the top of the weld recorded temperatures similar to those recorded in weld HSLA-65-5 at a similar position. The thermocouples on the top surface of the plate were stirred from their original position. The shearing action of the tool shoulder on the sheath caused the sheath to tear, allowing the silica powder inside the sheath to be added to the weld. The result was a rough, gauled surface as shown in Figure 5.12.
103 Ch 5 Ch 6
Figure 5.12 Image of weld HSLA-65-6 top surface after welding through thermocouples showing the rough surface where the thermocouples were stirred into the weld
A radiograph of the plate was taken after welding to help ascertain where the thermocouples moved. X-ray images of the plate are shown below. The two thermocouples in the weld centerline were stirred back and left craters in the weld on the trailing side of the tool. The welds on centerline of the tool path on the bottom of the plate were moved back slightly. Thermocouples for channels 3 and 7, off the centerline on the bottom and just outside the shoulder on the top, respectively, did not move at all. The white spots which appear in the centerline of the weld are most likely tool material abraded from the tool and deposited in the weld.
104 Ch 1 Ch 2 Ch 3 Ch 4
Ch 5 Ch 6 Ch 7
Figure 5.13 Radiograph of plate instrumented with sheathed thermocouples after welding
Figure 5.14 Increased magnification of radiograph showing thermocouple channels 3, 4 and 7 in HSLA-65-6 weld
105 Feed rate data collected from the machine allowed calculation of the tool position. The successful collection of temperature data allowed comparison of the temperature at the thermocouple position to the relative position of different parts of the tool geometry such as the leading edge of the shoulder, the side of the shoulder, or the leading edge of the pin. By plotting the acquired temperature at a given position against the position of the tool, one can begin to understand the effect of the tool on the heating rate as well as determine the temperature gradient in the material. The centerline of a thermocouple was considered to be the x-axis origin so that when the tool feature of interest was at the centerline of the thermocouple, the position on the graph was zero on the x-axis. Figure 5.15 shows a schematic of a thermocouple and the tool to illustrate the convention for determining feature position.
-X +X
Distance from leading edge of Direction of Tool Travel shoulder
Distance from leading edge of pin
Figure 5.15 Illustration of convention for position of tool geometry features relative to thermocouples in plate
Figure 5.16 shows a plot of the temperature acquired by the thermocouples on the bottom of the plate relative to the position of the leading edge of the tool pin.
106 1200
1000
800
600 Channel 1 Channel 2
Temperature (°C) Temperature Channel 4 400
200
0 -0.6 -0.4 -0.2 0 0.2 0.4 Position of Leading Edge of Pin (in)
Figure 5.16 Temperature acquired on bottom of plate at thermocouple channels 1, 2 and 4 plotted against the position of the leading edge of the tool pin relative to the centerline of the thermocouples
The acquired data shows what appears to be heating by conduction until the pin reaches a point about 0.18” from the thermocouple. There is a sudden change in the heating rate at this point. The steel heats rapidly to just above 800ºC where the heating rate drops significantly. This drop in heating rate as the tool approaches takes place at a temperature associated with the intercritical region in steels. The temperature nearly plateaus at 900ºC as the leading edge of the pin passes over the thermocouple and then continues to increase as the bottom of the pin moves over. The second thermocouple on the bottom showed a temperature profile very similar to the first thermocouple. The thermocouples on the top revealed a different response to the approach of the tool. The heating rate as the tool approached suddenly increased when the tool was approximately 0.13” from the thermocouple position. The heating rate remained very steep, but slowly decreased until the peak temperature was reached. The peak temperature was reached about the same time the tool shoulder reached the 107 thermocouple. The response of the thermocouple can be seen in Figure 5.17. The temperature remained at this peak temperature until the retreating side of the shoulder had cleared the thermocouple position. Most likely, the shoulder sheared the thermocouple as it passed so that the position at which the thermocouple actually read the temperature was the point of contact with the shoulder. This position relationship may be better understood with the aid of Figure 5.18.
Temperature on Weld Centerline Related to Leading Edge of Shoulder Top Thermocouple, Channel 5
1400
1200
1000
800
600 Temperature (°C) Temperature 400
200
0 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 Shoulder Position (in)
Figure 5.17 Temperature acquired on top of plate at thermocouple channel 5 plotted against the position of the leading edge of the tool shoulder relative to the centerline of the thermocouple
108
A B
Figure 5.18 Position at which temperature is measured as thermocouple on top surface is acted upon by the tool shoulder
When the tool shoulder has just reached the thermocouple, at position A, the temperature is measured at the tip of the probe. As the tool moves past the thermocouple, the point of contact with the shoulder is where the temperature is measured. At point B, the thermocouple is reading the temperature at the outer edge of the weld. The distance traveled by the tool from the point of first contact to the point when contact with the thermocouple is lost is equal to the radius of the shoulder. For the tool used in this study, that distance is 0.375”, which corresponds to a leading edge of the shoulder position of 2.875 for the thermocouple used to create the plot in Figure 5.17. It can be seen in that figure that the temperature begins to drop in the thermocouple when the leading edge of the shoulder reaches this position on the plate.
5.2.3 Marker Data The plates with embedded markers were prepared in the same manner as the iron marker plate. The surface of the plate was etched and an image captured after removing 0.010” of material. The process was repeated until the entire weld had been milled from the plate. The marker data for the HSLA-65 welds yielded results similar to those 109 observed in the iron marker studies. The marker material nearer to the surface was acted upon by the shoulder and stirred back further than material which was closer to the bottom. Figure 5.19 and 5.20 show examples of these phenomena. Figures 5.21, 5.22, and 5.23 depict different views of the serial section sketches for the 0.0625” marker on the weld centerline.
Figure 5.19 Section of HSLA-65 plate near plate surface showing original and final position of 0.0625” markers
110
Figure 5.20 Section of HSLA-65 plate near bottom of plate showing original and final position of 0.0625” markers
Weld Direction Rotation
Edge of Pin
Edge of Shoulder
Figure 5.21 Plan view of marker material final position with outline of tool path and original position of marker (grey circle) 111
Figure 5.22 Transverse section view of final marker position sketches with original position of marker pin and profile of tool outlined (weld direction - into page)
Weld Direction
Figure 5.23 Longitudinal section view of serial section sketches and original pin position from retreating side
The data acquired from the friction stir welding machine’s acquisition system was also similar to that collected in the iron. The 0.0625” markers did not have an effect on the loading of the machine, while the 0.25” markers had some effect on the loading in the 112 x-direction. The loading was not as significant in the HSLA-65 as it was in the iron due to the higher strength of the HSLA-65 plate.
HSLA-65-4 Machine Data
3000 450
ZWload 400 Xload 2500 RPM 350 Xfeed
300 2000 250
1500 200 RPM
Load (lbf) Load 150 1000 100
50 500 0
0 -50 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Weld Distance (in.)
Figure 5.24 Machine data collected from friction stir weld in HSLA-65 with markers
The loading in the x-direction is low as the tool begins to travel through material preheated by the plunge and dwell stage of the process. After almost 1” of travel the tool begins to experience increased resistance as material is encountered which has not been heated enough to soften. At 1.5” of travel the loading has reached steady state in both the x and z directions. The tool pin encounters the 0.25” marker on the advancing side just before traveling 3” and the marker on the weld centerline between 3” and 3.5”. These two events are represented in the x-direction data as increases in the load. Interestingly, the
113 0.25” marker on the retreating side of the tool did not register an increase in the x- direction load.
5.2.4 Electron Backscatter Diffraction Data A cross section of weld HSLA-65-3 was prepared for EBSD. The transition between the fine, equiaxed grains and the rolled ferrite and pearlite was the region chosen for scanning. An area which provided good indexing was found near the upper surface of the plate, where the boundary between the two regions is nearly vertical. Figure 5.25 shows a unique grain color map of the scanned region.
100μm
Figure 5.25 Unique grain color EBSD map of transition from rolled plate structure (left) to fine grained ferrite (right)
The etchant used to prepare the sample preferentially attacked the cementite in the microstructure, and as a result, some regions were too severely attacked to obtain diffraction patterns. Also, the region of interest was marked with a diamond indenter prior to scanning in the SEM. One of the indentions, placed roughly along the boundary to be scanned, shows up as a black diamond on the bottom in the center of the scan. A grain orientation deviation map was also created from the EBSD data collected during the scan of this region. The map shows the grains in the rolled plate have greater grain orientation deviation than the fine grains between the weld and the base metal. That
114 there appears to be more deviation near the top could be a result of the scanned area being near the surface of the plate, where the shoulder may have provided strain to the fine grained region.
100μm
Figure 5.26 Grain orientation deviation map of transition region from rolled ferrite and pearlite (left) to fine, equiaxed grains at right
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CHAPTER 6
ARMCO IRON TORSION EXPERIMENTS
6.1 Preliminary Study
To begin hot torsion testing, the standard hot torsion specimen design described in Chapter 2 was used. The 14mm diameter iron rod was used for this preliminary study. A central composite designed experiment was chosen for the initial investigation of the effects of the Gleeble control parameters on the resulting microstructures in hot torsion experiments.
6.1.1 Experiment Design The first experiment was to be a learning experience in the capabilities and operation of the hot torsion MCU. A three factor central composite design with control variables of number of revolutions, rate of rotation, and peak temperature at rotation, was chosen. The experiment included five runs of the centerpoint and the run order was randomized. The temperature range chosen was to be between 1000ºC and 1360ºC. The rate of revolution varied from 500rpm to 1500rpm. The number of revolutions ranged from 6 to 34 revolutions. The entire designed experiment is shown in Appendix C.
6.1.2 Procedure Samples were heated by setting the power angle to degrees. Once the sample reached 750ºC, control of the heating was switched to the optical pyrometer feedback loop. The sample was heated to the test temperature determined by the designed experiment and 116 held there for 10 seconds. Thrust control was used throughout the heating phase of the test to accommodate thermal expansion of the sample. At the end of the 10 second hold, the current through the sample was stopped and the sample was turned the number of revolutions set forth in the experiment design at the rate set forth in the design. In addition to the hot torsion designed experiment tests, a single sample was heated to 1200ºC at 100ºC/s, held for 10 seconds, and then allowed to free cool. All tests were conducted with the high vacuum operating, which kept the chamber pressure at approximately 5x10-6 torr. After removal from the Gleeble, the samples were sectioned and mounted. The samples were then polished by standard metallographic procedure with silicon carbide paper to 1200 grit. Polishing continued with 9 μm, then 3 μm diamond paste. Final polishing was done with 1 μm alumina using ethyl alcohol as the lubricant. Samples were etched by dipping in 2% nital for 25 seconds. Digital images of the etched samples were taken at a depth 0.5 mm from the sample surface at the center of the gage section. Grain size measurements were performed on the images with the Pax-it!™ software using the concentric circles method. Longitudinal and transverse micro-hardness traverses were performed on each sample.
6.1.3 Results ANOVA was used to determine whether the control parameters of the Gleeble test had an effect on the measured grain size or hardness. No statistical correlation between the control parameters and the grain size or hardness could be found. In fact the samples all had very large grains which were softer than those of the as received rod. The as received ASTM grain size was 10.5 and the average grain size of the samples run in the preliminary designed experiment was 9.4. The hardness of the as received material was 160 Hv, while the samples which were tested in torsion had an average hardness of only 106 Hv. Figure 6.1 shows the as received rod and Figure 6.2 shows one of the samples run at the centerpoint conditions of the central composite design (1200ºC, 20 revolutions, 1000 rpm).
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Figure 6.1 As received microstructure of the 14mm iron rod
Figure 6.2 Microstructure of 14mm iron bar after heating to 1200°C and 20 revolutions at 1000 rpm (hardness 106Hv)
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The single sample which was heated but had no torsional load applied showed the same large grains of the samples which were twisted and had hardness of 105 Hv. Examination of the free cooling data acquired after torsion, showed that the sample cooled very slowly. While the optical pyrometer could only record temperatures reliably to approximately 730ºC, extrapolation of the cooling curve showed that the iron cooled from 800ºC to 500ºC in roughly three minutes. Data provided by the Naval Surface Warfare Center and the data collected from the weld described in Chapter 5 showed that the cooling time from 800ºC to 500ºC (Δt8-5) in the welds was between 12 and 17 seconds.
6.2 Modification of Hot Torsion Test Procedure
The large space between the grips in the hot torsion unit, and the poor thermal conduction of the collets prevented sufficient cooling of standard hot torsion samples to simulate the cooling observed in friction stir welds made in steel. To overcome this limitation, new jaws were designed and a modified torsion sample was created for use in the new jaws. The new torsion sample was of annular design, with a 0.1875” diameter hole through its axis. The total length of the sample was reduced from 6.5” to 5.5”. The gage section diameter was reduced to 0.375” in diameter. A schematic of the modified sample geometry is shown in Appendix A. The hole through the sample, the reduced cross sectional area, and the shorter sample were all used to increase the cooling rate. The hole through the sample was for use with a quench gas, to be applied in conjunction with the external quench heads of the torsion MCU. The new jaws were modeled after the standard ones, but each was made 0.5” longer than the standard collets. This allowed the sample to be shorter in length and brought the faces of the jaws closer together. The new jaws have a hole which aligns with the hole through the modified samples. A second hole in each jaw provides for a threaded hose fitting on the non-rotating jaw and an exhaust port on the rotating jaw. Figure 6.3 shows the modified collets in the torsion chamber with a hose for blowing quench gas through
119 the sample. Bringing the gas to the jaws required a plug in the chamber wall. The plug had a hole through it, with internal threads for attaching hose barbs (See Appendix A).
Helium in
External quench heads
Helium out
Figure 6.3 Modified hot torsion collets for gas quench with sample removed
After the modified collets and samples were manufactured, a series of cooling tests were conducted in the Gleeble. Samples were heated at 100ºC/s to 1300ºC and then cooled. Standard samples and modified samples were used. Cooling was by either conduction to the collets, external quench, or combined internal and external quench. The modified sample with combined quench provided significant improvement and yielded a
Δt8-5 of 14 seconds. Acquired thermal data from the tests are shown in Figure 6.4.
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Torsion Sample Cooling
1400
1200 standard, vacuum standard, He backfill Standard, Ext. quench 1000 modified, vacuum modified, Int. & Ext. quench
800
600 Temperature (°C) Temperature
400
200
0 0 20 40 60 80 100 120 140 160 180 200 Time (sec)
Figure 6.4 Thermal data acquired from tests to improve cooling rate in the hot torsion test. Standard sample Δt8-5 = 81 seconds. Modified sample with gas quench Δt8-5 = 14 seconds
6.3 Modified Torsion Tests
Once it was shown the modified hot torsion sample and collets could achieve cooling rates similar to those observed in friction stir welds made in steel, hot torsion tests were conducted to make use of the increased cooling capability. First another central composite experiment was designed. After the completion and analysis of data acquired from this test, a second designed experiment was implemented. The second experiment utilizing the modified sample geometry and collets used the test temperature, number of revolutions, and rate of revolution as control factors, but a fourth factor, Δt8-5, was included. The use of four factors in a central composite experiment would have required
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30 samples. A Low Cost Response Surface Method (LCRSM) design, which requires only 14 samples for a four factor experiment, was chosen instead.
6.3.1 Modified Sample – Central Composite 6.3.1.1 Procedure Samples made with the modified geometry were machined from the 6” iron bar. The temperature range for the experiment was from 1100ºC to 1300ºC. The number of rotations was decreased from the previous experiment to a range of 2 to 12 rotations. Finally, the rate of revolution was varied between 195 rpm and 1205 rpm. When rotation was completed, helium was delivered at 40 CFH to both the chamber external quench heads and the internal cooling inlet. The full design is shown in Appendix C. With the exception of the helium quench, the method of heating, the vacuum environment, and the preparation of samples after testing was the same as used in the preliminary central composite experiment.
6.3.1.2 Results The microstructures observed in the modified hot torsion samples were similar to those which were reported for the iron friction stir welds in Chapter 4. Figures 6.5 through 6.9 show the microstructures commonly observed in the modified hot torsion samples.
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Figure Figure 6.9 Figure 6.7 Figure 6.8 6.6
Figure 6.5 Photomicrograph showing varied microstructure in hot torsion sample heated to 1260ºC, rotated 10 revolutions at 1000 rpm (Simulated SZ to right, base metal at far left)
Figure 6.6 Refined ferrite microstructure near center of hot torsion sample
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Figure 6.7 Mixed ferrite grain size observed in hot torsion sample
Figure 6.8 Beginning of transition from mixed ferrite grain region (right) to subgrain boundary network structure (left) in hot torsion sample
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Figure 6.9 Transition from subgrain boundary structure to larger ferrite grains of base metal in hot torsion sample
The average ASTM grain size of the center section of the modified sample geometry central composite experiment was 8.2. This was finer than the as received grains for the iron bar, which were ASTM grain size 5.2. This confirmed that the improved cooling rate brought about by the quench was able to prevent the grain growth experienced with the standard samples in the preliminary study. However, ANOVA revealed no significance between the ferrite grain size at the center of the samples and the control factors. It was surmised this was due to all the samples cooling at the same high rate with the helium quench.
6.3.2 Modified Sample – LCRSM It is well known that the temperature profile of a resistively heated metal bar being cooled at its ends by conduction is parabolic, with the highest temperature in the center. The modified geometry samples showed changes in microstructure along the length of the sample. This suggests an importance of the temperature on the microstructure developed when torsion is applied. A second designed experiment using the modified 125 samples was pursued to determine the temperatures at which the different microstructures were formed. To do this, temperatures above and below the equilibrium A3 temperature were used. The apparent importance of cooling rate on grain size at the center of the sample led to the inclusion of cooling rate as a variable.
6.3.2.1 Iron LCRSM Procedure Modified hot torsion samples were prepared from the 6” iron bar. Prior to testing, a line was scribed across the gage section, parallel to the sample axis. Pairs of K-type thermocouples were welded onto the sample at distances of 0.125” and 0.25” from the left shoulder. This side is fixed, and the thermocouples were more likely to remain attached during torsion. A picture of a modified hot torsion sample with scribed line and thermocouples is shown in Figure 6.10.
Figure 6.10 Left side of a hot torsion sample showing scribed line on surface and thermocouples welded at distances of 0.125” and 0.25” from the shoulder
126
The temperature range and number of rotations were reduced from the values used in the previous experiments. Temperatures ranged from 850ºC to 950ºC and the number of rotations was from 1 to 3. The rate of revolution was dropped only slightly from previous experiments and varied from 100 rpm to 1000 rpm. A cooling rate term was used in the experiment. The value for Δt8-5 was varied from 15 seconds to 35 seconds. The complete experimental design is shown in Appendix C. Temperature was acquired at the center of the sample by the integrated pyrometer. Helium at 40 CFH was blown through the samples once torsion was stopped. After testing at the prescribed parameters and prior to sectioning, the distance from the left shoulder to the point at which the scribed line was deemed to deviate from horizontal was measured and recorded. Samples were mounted, polished, and etched in the same manner described earlier.
6.3.2.2 Iron LCRSM Results While testing the first sample, it was obvious that the cooling rate control was going to be difficult. The pyrometer used in the feedback loop for control of the temperature could only reliably control the cooling rate down to about 730ºC. The result was that samples could only be control cooled to that temperature before the cooling control had to be terminated and the helium quench determined the cooling rate. The desired Δt8-5 values could not be achieved due to this limitation. The first thing noted about the samples was that in some of them, the slope of the scribed line changed across the sample. The line began horizontally at the shoulder and slowly began to deviate from horizontal as one moved from the shoulder toward the sample center. There was a point where the line turned sharply and began to travel around the sample in a helical path. The distance to this point was recorded. The line became indistinguishable at this point as it moved into a region of the sample which had a surface texture similar to that of an orange. In some samples, the line became visible and returned to a more horizontal slope across the center of the gage section, while in others it did not reappear until a point about the same distance from the right shoulder as the distance at
127 which the line became indiscernible on the left. Figure 6.11 offers a sketch of the two different modes for change in the slope of the scribed line.
Fixed Side
A
Fixed Side
B
Figure 6.11 Sketch depicting the two types of change in slope observed in the line scribed across the gage section for LCRSM samples. A) Sample with strain concentrated in the center B) Samples with strain concentrated outside the center
The run order of the samples which exhibited the strain concentration outside the center (B in Figure 6.11) was 1, 3, 4, 10 and 14. All the samples which had two regions over which the line disappeared had been heated above 900ºC. Samples in which the line disappeared on the left and reappeared on the right were all heated to temperatures of 900ºC or lower. ANOVA was used to check for significance of the control factors on the distance from the shoulder to the point at which the line disappeared in the orange peel texture. The analysis showed a significant effect of the test temperature, number of revolutions, and rate of revolution on the distance measured from the left shoulder to the point at which the line disappeared. The form of the model, using coded units, was:
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0.2882 - 0.0578·temp – 0.0309·rev – 0.0173·rev·rpm – 0.0167·temp·rev
This model for the observed results shows that there is some interaction between the number of revolutions (rev) and the rate of revolution (rpm) as well as between the number of revolutions and the test temperature (temp). In both instances of interaction, an increase in the product of the two variables shifted the distance at which the line disappeared toward the shoulder. In addition to the interaction coefficients, the test temperature and the number of revolutions had linear effects on the distance. As both the number of test temperature and the number of revolutions increased, the distance from the shoulder to the disappearance of the line was decreased. The intercept value of 0.2882 means that for a sample run at the median for all three variables, the expected distance from the shoulder to the point at which the line disappears in the deformed region is 0.2882”.
Distance from Shoulder to Beginning of Deformed Region
0.4
0.35
0.3
0.25
0.2 Measured Modeled Distance (in) 0.15
0.1
0.05
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Run Order
Figure 6.12 Plot of measured and modeled values for the distance to the localized deformed region in iron torsion samples (R2 = 0.92)
129
The use of multiple thermocouples on the hot torsion samples allowed a temperature versus distance curve to be fit to the data. The actual distance from the shoulder in the fixed jaw to the thermocouple was measured for each thermocouple. Plotting temperature measured by the pyrometer and each thermocouple just before the initiation of torsion and fitting a second order polynomial to the points gave an average temperature profile for each test temperature used (Figure 6.13). The average distance from the shoulder to the point at which the sample is 700ºC decreases as the peak temperature increases.
Armco LCRSM Average Thermal Profile at Start of Torsion
1000
900
800
700 Temp (°C)
600
500
400 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Distance from Left Shoulder
Figure 6.13 Curves fit to acquired thermal data to give average temperature profiles across iron modified hot torsion samples
Thermal data collected from multiple points on the sample surface also allowed examination of the heating caused by internal friction during torsion. The acquired data showed that additional heating of the sample differed across the length of the gage section. As can be seen in Figure 6.14, the temperature in the center of the sample (0.5” from the shoulder) dropped in temperature during torsion, while the temperature of the 130 sample at a point 0.25” from the shoulder increased in temperature (runs 1 to 4, 10, 12, and 14). The temperature at the thermocouples nearest the shoulder (0.125”) registered a decrease in temperature in all but one sample (run 2).
Temperature Change from Beginning to End of Torsion
100
0.125 80 0.25 0.5
60
40
20 Delta T (C)
0
-20
-40 1234567891011121314 Run Order
Figure 6.14 Measured changes in temperature at nominal distances of 0.125”, 0.25”, and 0.5” from the left shoulder of the torsion sample
With the exceptions of run 2 and run 12, there is excellent correlation between the where the scribed line was not discernable and where the greatest increase in temperature occurred during torsion. Samples 5 through 9 were all run at temperatures of 900ºC or lower, which corresponds to the test temperature below which all samples exhibited a concentration of strain in the center of the sample. The data acquired from run 2 (all variables at their highest value for the experiment), at 0.25” from the shoulder, showed the most significant increase in temperature during torsion. Examination of the data suggests that the heating caused by the application of torque is dependant upon the temperature. Figure 6.15 gives the plots of rotation during
131 the application of torsion and the measured temperature at 0.25” from the shoulder. The rate of rotation was constant during the test. As can be seen in the figure, the sample began heating at the position of the thermocouple when rotation began. The rate of heating increased as temperature increased until the temperature reached about 880ºC. At this point, the rate of heating decreased sharply, although the sample continued to rotate at the same rate of rotation.
Heating Due to Torsion in Run 2 at 0.25" from Shoulder 920 3.5
900 Decrease in 3 heating Rate 880 2.5
860 2
840
1.5 Revolutions 820 Temperature (ºC) Temperature Temperature Rotation 1 800
0.5 780
760 0 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 Elapsed Time (s)
Figure 6.15 Temperature and torsion for iron LCRSM experiment run 2 at 0.25” from shoulder
The results of these tests suggest that heat generation during torsion occurs where the deformation is greatest and that in iron, strain occurs in some regions preferentially. The extent of this localized strain region is dependant upon the material temperature, the total applied strain, and the strain rate. The temperature concentration of strain appears to occur at temperatures below 900ºC.
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6.4 Strain – Temperature Relationships in Iron
A final set of tests was conducted to determine the relationship between temperature and strain in hot torsion samples with a temperature gradient across the sample. 6.4.1 Iron Strain vs. Temperature Procedure Four standard iron samples, made from the 14mm iron rod were used for the experiment. Samples were tested using the same programs used for runs 1 and 5 in the modified sample LCRSM experiment and a modified version of run 6 (a test temperature of 900ºC rather than 875ºC). From this point on, the samples will be called run 1, run 5, and run 6. The fourth sample was heated in the hot torsion MCU with the same heating and cooling cycles recorded for the sample which followed the run 6 program. However, no torque was applied to the fourth sample. This sample was designated run 6n (n for no torsion). The test conditions and sample designations are shown in the table below.
Test Sample Rate of Temperature Revolutions Designation Rotation (rpm) (ºC) Run 1 925 2.5 775 Run 5 875 1 325 Run 6 900 1 1000 Run 6n 900 0 0
Table 6.1 Strain versus temperature sample designations and test conditions
A line was scribed across the gage section of the three samples tested in torsion prior to the application of torque. Thermocouples were attached at 0.125” and 0.25” from the shoulder. The pyrometer was used to measure the temperature at the center of the sample (0.375” from shoulder). Cooling was achieved by blowing helium at 40 CFH through the external quench heads of the torsion MCU. Following testing in the Gleeble, the samples were mounted in an apparatus which allows the slope of the scribed line to be measured incrementally. The sample was held in 133 a chuck attached to a dial which was divided into one degree increments. The chuck was attached to a rod which could traverse in the direction of the sample axis. A stereo microscope with a scale in one eyepiece was positioned over the gage section of the sample. Figure 6.16 shows a picture of the apparatus.
Figure 6.16 Picture of the apparatus used to make incremental strain measurements (arrows show rotation and traverse direction)
The degrees of rotation and axial position were recorded when the scribed line and the left shoulder were centered in the eyepiece with the scale. The sample was moved a small distance, measured with the scale, and rotated until the scribed line crossed the centerline of the scale. This process was repeated, with the degrees of rotation and distance traversed recorded for each point. After all points were measured across the gage section, the shear strain over each increment was calculated using the formula for shear strain in torsion: r ⋅θ γ = l
134
Next, the strain was plotted against the distance traversed. Normal curves were fit to the distribution of strain. The temperature measurements from the pyrometer and thermocouples were used to fit a second order polynomial to the data. Using the curves which were fit to the strain and the temperature profile at the initiation of torsion, a plot of shear strain versus temperature for each sample was created. All the samples were sectioned, mounted, polished, and etched using the same procedure described earlier. Macroscopic and microscopic images were captured for each of the four samples. In addition, the run 5 and run 6 samples were prepared for EBSD scanning in the SEM.
6.4.2 Iron Strain vs. Temperature Results 6.4.2.1 Strain vs. Temperature Plots of the strain versus the temperature created from the curves fit to the strain and temperature distributions for the three samples tested with torsion applied are shown in Figure 6.17.
Strain Distribution in Ingot Iron Hot Torsion Samples 35
30
25 875°C, 1 rev, 325 rpm 925°C, 2.5 rev, 775 rpm 20 900°C, 1 rev, 1000 rpm
15 Shear Strain
10
5
0 650 700 750 800 850 900 950 Temperature (°C)
Figure 6.17 Strain versus temperature plots for three standard samples tested in torsion 135
The plots show that strain is concentrated in the region where the temperature is between 800ºC and 900ºC. The peak in strain for the three samples occurred at a temperature between 865ºC and 868ºC. The strain appears to be concentrated in the temperature range associated with the intercritical temperature region for low carbon steel.
6.4.2.2 Images Macroscopic images of two of the samples are shown in Figures 6.18 and 6.19. Included in each figure are boxes highlighting areas representative of those used for higher magnification images in figures which follow. The image shown in Figure 6.18 is from the run 5 sample. The region in which strain was concentrated is clearly visible at the center of the gage section of the solid sample.
Figure 6.27
Figure 6.22
Figure 6.18 Macroscopic image of polished and etched cross section of standard hot torsion sample heated to 875ºC and rotated 1 revolution at 325 rpm (run 5)
136
Figure 6.23 Figure 6.24 Figure 6.31
Figure 6.25
Figure 6.21
Figure 6.19 Macroscopic image of polished and etched cross section of standard hot torsion sample heated to 900ºC and rotated 1 revolution at 1000 rpm (run 6)
The total strain imparted to both samples was the same (1 revolution), but the strain rate (rpm) and temperature profiles differed. The region of strain localization is shifted out from the center toward the shoulders in the sample heated to a higher temperature. The sample which was given the same thermal treatment as the run 6 sample but not twisted is shown in Figure 6.20. The sample lacks the regions of deformation concentration seen in the other samples.
137
Figure 6.26
Figure 6.20 Macroscopic image of polished and etched cross section of standard hot torsion sample heated to 900ºC but not rotated
Higher magnification images revealed that the regions of concentrated strain were composed of equiaxed ferrite grains. Figure 6.21 shows the center of the strain concentrated region in the sample designated ‘run 6’. In the run 5 sample, the entire region was bounded by grains with visible subgrain boundary networks. The sample designated ‘run 6’ showed the same type of boundary between the strain concentrated region and the axis of the sample and on the side of the concentrated strain region nearer the shoulder. An example of this boundary region from run 5 is shown in Figure 6.22 and from run 6 in Figure 6.23.
138
Figure 6.21 Equiaxed ferrite microstructure observed in region of concentrated strain (run 6 sample)
Figure 6.22 Network of subgrain boundaries seen at boundary between concentrated strain region (out of view at top of image) in hot torsion sample and the axis of the sample (out of view at bottom of image)
139
Figure 6.23 Grains with subgrain boundary networks at the boundary between the region of concentrated strain (at right) and the base metal (out of view to left)
The boundary between the region of concentrated strain and the center of the gage section, where the material was at a higher temperature at the initiation of torsion than the region where the strain was concentrated, in the sample designated ‘run 6’ exhibited a bimodal ferrite structure. This structure is shown in Figure 6.24. The center of the gage section in this sample exhibited a structure composed of equiaxed ferrite grains. The center of the sample which was heated in the Gleeble with the same thermal history recorded at the center of the run 6 sample also had an equiaxed ferrite structure where the temperature was greatest during testing. Figures 6.25 and 6.26 show the microstructures of run 6 (with torsion) and run 6n (no torsion) at the center of the hot zone.
140
Figure 6.24 Bimodal ferrite structure seen at boundary between region of concentrated strain and center of the hot zone in run 6 sample
Figure 6.25 Ferrite structure found in the center of the hot zone of standard iron torsion sample (run 6, 900ºC test temperature, 1 revolution, 775 rpm)
141
Figure 6.26 Ferrite structure found in the center of the hot zone of standard iron torsion sample tested without the application of torsion (run 6n, 900ºC test temperature)
The upper left corner of Figures 6.25 and 6.26 show the grain size measurement results from the Pax-it!™ software concentric circle method. Grain size measurements were also made in the region of concentrated strain in the run 6 sample and the portion of the gage section from the sample designated run 6n which was heated into the intercritical temperature region. These grain size measurements are summarized below in Table 6.2.
Region of Interest Run 6 Run 6n Center of Hot Zone 10.4 9.4 Intercritical Temperature 8 6.5 Region
Table 6.2 ASTM grain size measurements for samples with same temperature history and different strain conditions (run 6 – torsion, run 6n – no torsion)
142
From the grain size measurements, it is apparent that the strained sample has smaller grains in both regions than the sample given identical thermal treatment but not strained. The application of strain through torsion results in refined grain size.
6.4.2.3 Electron Backscatter Diffraction Data Three EBSD scans were made of the iron torsion samples. One scan was a low resolution scan which covered an area at the center of the run 5 sample from the axis of the sample into the region where strain was concentrated. A grain orientation deviation map of this scan is shown in Figure 6.27.
600 μm
Figure 6.27 Grain orientation deviation map from standard iron torsion sample (axis of sample at bottom and strain concentrated region at top)
Another scan was made at the center of gage section in this sample, but the area scanned included only material which was in the portion of the sample where strain was concentrated. Maps of this scan are shown in Figures 6.28 and 6.29. The grain orientation deviation map shows that there was little deviation in the orientation within the grains in this region. This suggests the grains have recrystallized and there is little strain in them. 143
The inverse pole figure map in Figure 6.29 appears to have a significant amount of blue and purple colored grains. A pole figure plot was created to determine whether there was texturing (preferred orientation of grains) in the mapped area. The pole figure plot, in Figure 6.30, shows texturing in the region of strain concentration. The grains in the center of the gage section of the sample tested at 875ºC with 1 revolution at 325 rpm have a preferred orientation of <111>.
144
200 μm
Figure 6.28 Grain orientation deviation map at center of strain concentration region in iron torsion sample
145
200 μm
Figure 6.29 Inverse pole figure map of strain concentration region in iron torsion sample
146
Figure 6.30 Pole figure plot for the region mapped in Figures 6.28 and 6.29
The final area scanned by EBSD was from the region where deformation was concentrated toward the material which did not reach as high a temperature at the shoulder in run 6 (see Figure 6.19 for an outline of the area scanned). A map of grain orientation deviation was created from the data (Figure 6.31). The map shows relatively strain free grains in the area where the deformation was concentrated (left) and increasing misorientation within grains as one moves toward the shoulder (right).
147
300 μm
Figure 6.31 Grain orientation deviation map from deformation concentration area (left) to material which experienced lower peak temperatures and less deformation (right)
148
CHAPTER 7
HSLA-65 TORSION EXPERIMENTS
7.1 Modified Hot Torsion Tests
After gaining experience in hot torsion testing with the iron, hot torsion tests were conducted with modified hot torsion samples machined from the 0.5” HSLA-65 plate. The thickness of the plate prevented making standard hot torsion samples, so the same geometry for the iron modified samples was used (see Appendix A). The low cost surface response method was chosen for the experiment designs after its effectiveness was demonstrated by tests on the iron samples.
7.1.1 Hot Torsion Microstructures Before the designed experiments were conducted a couple samples were heated using a program from the central composite designed experiment used on the first modified torsion samples made from iron. The program for run order 11 had a test temperature of 1260ºC, with 10 revolutions at 400 rpm. The microstructures developed, shown in Figures 7.1 through 7.5, were very similar to those observed in the HSLA-65 friction stir welds.
149 Figure 7.2 Figure 7.3 Figure Figure 7.4 7.5
Figure 7.1 Photomicrograph showing varied microstructure in HSLA-65 hot torsion sample heated to 1260ºC, rotated 10 revolutions at 1000 rpm (Simulated SZ to left, base metal at far right)
Figure 7.2 Simulated HSLA-65 stir zone showing Widmanstätten ferrite microstructure
150
Figure 7.3 Region of transition from Widmanstätten ferrite in stir zone (left) to fine, equiaxed ferrite (right)
Figure 7.4 Fine grained region found in deformed region just prior to transition to base metal
151
Figure 7.5 HSLA-65 base metal microstructure found near the shoulder in preliminary testing of modified hot torsion samples
7.1.2 General Procedure Three different LCRSM experiments were conducted with the 0.5” HSLA-65 material. The experiments were designated H-LCRSM 1, H-LCRSM 2, and H-LCRSM 3. All three experiments were conducted with a high vacuum environment (5x10-6 torr). The helium quench system was used in each test with the flow rate set at 40 CFH. The samples were all prepared with a line scribed across the gage section, as was done in some of the iron experiments. Each sample also had thermocouples attached at distances of 0.125” and 0.25” from the shoulder on the fixed side of the sample. Samples were heated with power angle control until the sample reached 750ºC. At this temperature the optical pyrometer was used to control the temperature at the center of the sample through a feedback loop. Samples were heated to the peak temperature at 90ºC/s and held for 5 seconds at the test temperature. The current through the sample was cut and the sample rotated at the prescribed rate and number of rotations. When the set number of rotations was achieved, the current was returned and the quench system turned
152 on. The cooling rate was controlled to 730ºC, then current was terminated and the sample cooled by forced convection from the helium blowing through it and on it. After removal from the Gleeble, the strain distribution in the sample was measured using the apparatus and technique described in section 4.1 of Chapter 6. The samples were then sectioned, mounted, polished, and etched with 2% nital.
7.2 H-LCRSM 1 Experiment
The initial hot torsion experiment in HSLA-65 was aimed at determining whether localized regions of deformation, as were observed in the iron, would occur in HSLA-65.
7.2.1 H-LCRSM 1 Design
Temperatures which were above and below the equilibrium A3 temperature, as read from the iron-carbon phase diagram for a carbon content of 0.071%, were used. The temperature range was from 810ºC to 910ºC. High and low values for the number of rotations were 1 and 7 respectively. Rate of rotation was varied from 100 rpm to 1000 rpm. The full design is shown in Appendix C.
7.2.2 H-LCRSM 1 Results The three samples with test conditions which prescribed just 1 revolution were the only samples to survive the testing intact. All the other samples failed in shear after approximately 2 revolutions. The three intact samples were examined for the existence of regions of concentrated deformation. A plot of the shear strain versus temperature at start of torsion was created using the technique described previously and is shown in Figure 7.2.
153 HSLA-65 Strain Response
7
6
5 Run 9 Run 12 Run 13 4
3 Shear Strain
2
1
0 650 700 750 800 850 900 950 Temperature (°C) at Start of Torsion
Figure 7.6 Shear strain versus temperature plots for three HSLA-65 modified torsion samples from H-LCRSM 1
The peak in shear strain for the three samples which remained intact during the H- LCRSM 1 experiment varied from 819ºC to 825ºC. In the sample from run 9 of the experiment, the strain was at a minimum where the temperature at the start of torsion was 877ºC. These temperatures were lower than the temperatures associated with the same response in the iron samples.
7.3 H-LCRSM 2 Experiment
The second hot torsion experiment was designed to test at temperatures in the same range as those measured during friction stir welding.
7.3.1 H-LCRSM 2 Design This experiment was designed with test temperatures ranging from 1100ºC to 1300ºC. The number of revolutions and rate of revolution was kept the same as those reported in 154 H-LCRSM 1 (1 to 7 revolutions and 100 to 1000 rpm). After the initial 14 samples were run, three samples were found to have been incorrectly run with 5.5 revolutions instead of 2.5. Three additional samples were run at the correct settings, for a total of 17 samples. The complete designed experiment is shown in Appendix C.
7.3.2 H-LCRSM 2 Results It was not possible to follow the path of the scribed line on all the samples after torsion. The samples where the line was visible all the way to the center showed that the shear strain increased exponentially with temperature (see Figure 7.2).
H-LCRSM 2 Shear Strain Distribution
18
16
14
12 Run 4 Run 11 10 Run 5 Run 7 8 Run 13 Shear Strain
6
4
2
0 600 700 800 900 1000 1100 1200 1300 1400 Temperature (°C)
Figure 7.7 Shear strain versus temperature plots for three HSLA-65 modified torsion samples from H-LCRSM 2
When ANOVA was used to examine the data collected for significance of the test variables, the effect of the controlled factors was found to have a significant effect on the peak temperature reached in the center of the sample during torsion. The polynomial 155 model created by fitting the significant variables to the measured peak temperatures had the following form:
1240.65 + 78.366*temp + 18.533*revs + 26.766*rpm + 20.189*temp2 – 20.288*revs2 – 11.411*rpm2 -21.24*temp*rpm + 21.095*revs*rpm
The fit was very good, with an R2 value of 0.9975. A plot of the peak temperature from the model and the measured temperature during the experiment is shown in Figure 7.8.
1400
1350
1300
1250
1200
1150 Temperature (°C) Temperature Experimental Model 1100
1050
1000 1 2 3 4 5 6 7 8 9 1011121314151617 Standard Run Order
Figure 7.8 Plot of measured and modeled values for the peak temperature reached during torsion for the H-LCRSM 2 experiment
The duration of the torsion portion of each test was known. By subtracting the temperature at the initiation of torsion from the peak temperature achieved during torsion and dividing by the time during which torque was applied, an average heating rate for each run could be calculated. ANOVA showed that the control factors had a significant 156 effect on the heating rate at the center of the sample. The heating rate was affected most by the rate of rotation and the test temperature. A surface plot of the heating rate was created for the ranges of the test temperature and rate of rotation used in the designed experiment. The number of rotations was held constant at 1 revolution to calculate the surface.
H-LCRSM2 Heating Rate Surface Plot for constant number of revolutions (1)
350
300
250 300-350 250-300 200 200-250 150-200 150 100-150 50-100 100 0-50 -50-0 Heating Rate (°C/s) Rate Heating 50
900 0 700 500 -50 RPM 300 1100 1125 1150
100 1175 1200 1225
1250 Test Temperature (°C) 1275 1300
Figure 7.9 Surface plot of the average calculated rate of heating due to torsion at the center of the hot torsion samples in H-LCRSM 2 (R2 = 0.992)
The surface plot of the average heating rate shows the general trend as temperature and strain rate (rpm) are changed. Material which had a higher temperature at the center does not experience as much heating when twisted as material with a lower start temperature when twisted at the same rate. Also, the rate of heating during torsion was higher for materials with a higher strain rate when the starting temperature is the same.
157 7.4 H-LCRSM 3 Experiment
The goal of the final experiment was to test over a range of temperatures which encompassed the previous tests. The amount of rotation was reduced to make measurement of the scribed lines easier.
7.4.1 H-LCRSM 3 Design The temperatures used for this test ranged from 800ºC to 1300ºC. The number of rotations was reduced from previous tests, to range from 0.25 revolutions to 1.25 revolutions. The rate of rotation varied from 300 rpm to the machine maximum 1500 rpm. It was hoped the higher rate of strain would allow the average heating rate to reach or exceed the rates observed in the friction stir welds. Two additional runs were made after the original 14 were completed. A sample labeled run 6a was run to correct the incorrect value for the number of rotations used in run 6. Also a run to validate the models developed by ANOVA was run with coded units for temperature, revolutions, and rpm of 0.7, 0.3, and -0.375. The complete designed experiment is shown in Appendix C.
7.4.2 H-LCRSM Results The lower rotation was successful in making possible the measurement of strain distribution across the gage section of the sample. Figure 7.10 shows the plot of the strain versus temperature created by fitting curves to the temperatures acquired by the Gleeble and the strain measurements.
158 14 Run 1 Run 2 12 Run 3 Run 4 Run 5 10 Run 6 Run 7 Run 8 8 Run 9 Run 10 Run 11 6
Shear Strain Run 12 Run 13 4 Run 14 Run 6a validate 2
0 650 750 850 950 1050 1150 1250 1350 Temperature (°C)
Figure 7.10 Shear strain versus temperature plots for all samples run in H-LCRSM 3 experiment
The two samples heated to 925ºC showed a peak in the shear strain at temperatures from 833ºC to 844ºC. This peak was followed by a trough with a minimum at temperatures of 874ºC to 880ºC. This trough corresponded in temperature to the one seen in the H-LCRSM 1 experiment.
159 1
0.9
0.8
0.7
0.6 Run 10 Run 12 0.5
Shear Strain 0.4
0.3
0.2
0.1
0 400 500 600 700 800 900 1000 Temperature (°C)
Figure 7.11 Peak and trough seen in strain versus temperature profile for samples heated to 925ºC in H-LCRSM 3 experiment
The peak temperature due to torsion was found in the acquired data for each sample and ANOVA used to determine the significance of the control factors. An excellent fit with R2 value of 0.9999 was found. The form of the polynomial fit to the data included all three of the control factors, as well as all interactions and second order terms. Plots of the measured and modeled peak temperatures are shown in Figure 7.12. It should be noted that the last two runs were not included in creating the model, but their values were accurately predicted.
London also utilized Al-SiC composite markers implanted in the faying surface of plates to study the flow of the welded material. Welds made in plates with markers were sectioned to reveal the flow of the marker material around the pin. The marker material also appears to be stirred around the pin leading edge and some of the material was reported to have traveled around the pin more than once before being deposited.
160 1400
1300
1200
1100 Temperature (°C) Temperature
1000 Measured Modeled 900
800 123 45678910 11 12 13 14 15 16 Standard Order
Figure 7.12 Measured and modeled peak temperature due to heating caused by torsion
Next, the average heating rate for each sample was calculated and ANOVA used to check for significance. The surface created from fitting a curve to the data also had an excellent fit (R2 = 0.997). A plot of the surface is shown in Figure 7.13. The trend found earlier in H-LCRSM 2 holds true for the wider range of temperatures and rates of revolution used in H-LCRSM 3. The rate of heating is strongly dependent upon the temperature and the rate of strain. Once again, higher temperature test temperatures resulted in lower heating rates for the same applied strain rate (rpm). Increasing the strain rate causes an increase in the rate of heating for identical test temperatures.
161 H-LCRSM3 Heating Rate Surface for constant number of revolutions (0.5)
1200 1100 1100-1200 1000-1100 1000 900-1000 900 800-900 700-800 800 600-700 700 500-600 400-500 600 300-400 500 200-300 100-200 400 0-100 300 Rate (°C/s) Heating 200 100 900 0 700 800
RPM 500 850 900 950
300 1000 1050 1100 Test Temperature (°C) 1150 1200 1250
Figure 7.13 Surface plot of the average calculated rate of heating due to torsion at the center of the hot torsion samples in H-LCRSM 3 (R2 = 0.997)
162
CHAPTER 8
PHASE TRANSFORMATIONS
The changes in heating rate acquired as the welding tool approached thermocouples in the HSLA plate and the concentration of strain in hot torsion samples both occurred over temperature ranges normally associated with the intercritical region of the iron carbon binary system. The peak temperatures on both the bottom and top of the plate occurred when a single phase austenite structure would be expected. It is believed the majority of material flow takes place in this single phase region. Phase stability calculations and a series of experiments were conducted to study the phase transformation temperatures for the alloys used in the welding and hot torsion studies.
8.1 Calculated Equilibrium Volume Fraction
The software Thermo Calc was used to create pseudo binary phase diagrams for the alloys tested. Pseudo binary phase diagrams are diagrams of phase stability created by varying the composition of two elements while holding the composition of other alloying elements in the material constant. Iron-Carbon pseudo binary phase diagrams output by the software for the compositions of the four materials used in the study are shown in Appendix D. From the calculated stability, the lever law can be used to determine volume percent of bcc and fcc iron present at equilibrium conditions between the A1 and A3 temperatures. While the lever law is for use in binary systems, it can provide a reasonable approximation of the volume of phases present when making calculations based on a
163 pseudo-binary phase diagram. Figures 8.1 through 8.4 show the fraction of the two phases calculated by Thermo Calc.
1
0.9
0.8
0.7
0.6
BCC iron 0.5 FCC iron
0.4
0.3 Volume Fraction Fraction of Volume Phase
0.2
0.1
0 700 720 740 760 780 800 820 840 860 880 900 Temperature (°C)
Figure 8.1 Calculated equilibrium volume fraction of bcc and fcc in 14mm iron rod
The transformation from ferrite to austenite begins at about 720ºC and finishes at 900ºC under equilibrium conditions. An equal ratio of the phases occurs at a temperature of approximately 880ºC. The higher carbon content of the 6 inch ingot iron bar resulted in an equilibrium intercritical temperature range between about 720ºC and 883ºC. The equal ratio of the two phases occurs at a lower temperature of about 860ºC as shown in Figure 8.2.
164 1
0.9
0.8
0.7
0.6
BCC iron 0.5 FCC Iron
0.4
0.3 Volume Fraction of Phase Volume
0.2
0.1
0 700 720 740 760 780 800 820 840 860 880 900 Temperature (°C)
Figure 8.2 Calculated equilibrium volume fraction of bcc and fcc in 6 inch iron bar
1
0.9
0.8
0.7
0.6
BCC Iron 0.5 FCC Iron
0.4
0.3 Volume Fraction of Phase of Volume Fraction
0.2
0.1
0 650 670 690 710 730 750 770 790 810 830 850 Temperature (°C)
Figure 8.3 Calculated equilibrium volume fraction of bcc and fcc in ¼” HSLA-65 plate
165 1
0.9
0.8
0.7
0.6
BCC Iron 0.5 FCC Iron
0.4
0.3 Volume Fraction of Phase Volume
0.2
0.1
0 650 670 690 710 730 750 770 790 810 830 850 Temperature (°C)
Figure 8.4 Calculated equilibrium volume fraction of bcc and fcc in ½” HSLA-65 plate
Both the HSLA-65 plates had similar intercritical temperature ranges and equal fraction temperature as shown in Figures 8.3 and 8.4. The transformation from ferrite to austenite begins between 670ºC and 680ºC and finishes just below 830ºC. The temperature at which there are equal fractions of the two phases is approximately 790ºC.
8.2 Differential Thermal Analysis
While the calculated equilibrium phase stability is useful for understanding the changes in phase stability caused by composition, the welds were not in an equilibrium condition. The rapid heating rate acquired by thermocouples in both the iron and HSLA- 65 plates should result in the presence of bcc beyond the equilibrium transition temperature. Single sensor differential thermal analysis seemed an ideal candidate for determining the Ac1 and Ac3 temperatures at high heating rates in the Gleeble.
166 8.2.1 Procedure The standard Gleeble pocket jaw mobile conversion unit was used for these studies. An initial sample was placed in the grips and the distance between the jaw faces measured. The sample was heated in an argon atmosphere to 1200ºC at the desired rate. Temperature and power angle were acquired. A second sample was then heated by using power angle control. The power angle used to heat the sample was picked from the data acquired during the heating of the first sample. The jaw faces were brought to the same distance as that used in the test to heat the sample with thermocouple control. A dilatometer was used to measure volume changes. Temperature, power angle, and dilatometer measurements were all acquired. The acquisition rate used in the power angle heating tests was 500 Hz. The acquired temperature data was processed with proprietary software being developed at The Ohio State University. Changes in the heating rate due to the consumption or release of energy were determined by fitting curves to the heating data and taking the difference between the fitted curve and the acquired data.
8.2.2 Gleeble Phase Transformation Results Heating rates similar to those determined from the data acquired in the thermocouple instrumented welds, were used for both the iron rod and the 0.25” HSLA-65 plate. Figures 8.5 through 8.8 give the results from dilatometry and SS-DTA for the high heating rate tests in these materials.
167 Iron Rod Dilatometry 500°C/s Heating Rate
1000
950
900 872ºC 850 820ºC 800 Temperature (°C) 750
700
650 80 85 90 95 100 105 110 115 120 Change in Diameter (μm)
Figure 8.5 Dilatometer results for ~500ºC/s power angle controlled heating of iron rod
At these high heating rates the dilatometer results showed the transformation ended at 872ºC. The volume contraction appeared to begin at 820ºC.
168 Iron Rod SS-DTA 500°C/s Heating Rate
1000
950
900 875ºC 850 820ºC 800
Temperature (°C) 776ºC 750
700
650 012345678910 Delta T (°C)
Figure 8.6 Single sensor differential thermal analysis of ~500ºC/s power angle heated iron rod
The thermal analysis yielded multiple transitions in the actual rate of heating when held at a constant power angle. A peak occurred at 743ºC and a valley at 750ºC. The magnetic transition was apparent in a peak at 776ºC. There was a gradual shift in heating which had a minimum at approximately 820ºC, which correlates well with the volume contraction from the dilatometer data. Another sharp peak was observed at 875ºC, which is close to the 872ºC observed for the end of the transformation to austenite.
169 1/4" HSLA-65 Plate Dilatometry 600°C/s Heating Rate
1000
950
900 883ºC
850 835ºC
800 Temperature (°C) 750 750ºC
700
650 110 115 120 125 130 135 140 145 150 Change in Width (μm)
Figure 8.7 Dilatometer results for ~600ºC/s power angle controlled heating of HSLA-65 plate
The HSLA-65 plate registered a volume contraction beginning at 835ºC and changed back to steady expansion at 883ºC. There was a noticeable change in the rate of expansion due to heating which began just before 750ºC and continued until the volume contraction at 835ºC.
170 1/4" HSLA-65 Plate SS-DTA 600°C/s Heating Rate
1000
950
900 885ºC
850 823ºC 800
Temperature (°C) 778ºC 750
700
650 -2024681012 Delta T (°C)
Figure 8.8 Single sensor differential thermal analysis of ~600ºC/s power angle heated HSLA-65 plate
The SS-DTA data for the HSLA-65 plate with a high heating rate was surprisingly very similar to that of the iron rod with a high heating rate. There was a definite change in heating just below 750ºC, followed by another change before a peak at the magnetic transformation. The transformation to austenite appears to begin at 823ºC and finishes in a sharp peak at 885ºC. There was some difficulty in processing the data from the high heating rate tests. First, the heating rate produced less than one data point per degree of temperature increase. Second, the Gleeble® acquisition system is only able to acquire data while no current is being passed through the sample. Since the heating system runs at 60 Hz and the current passes through zero twice per cycle, the maximum true acquisition rate can not exceed 120 Hz. The system software accommodates this limitation by only using 110 degrees of each 180 degree half cycle of the AC current. During the 70 degrees of no current through the sample the system makes multiple data collection cycles and then
171 interpolates the data points which would have been acquired while the current was on. So while great confidence can be placed in observed changes to the heating rate, the exact temperatures at which those changes take place cannot be deduced due to this system limitation.
8.3 Testing Inconel Sheathed Thermocouple Response
The thermocouples used in the successful acquisition of friction stir weld thermal data were sheathed in a thin walled Inconel 600 tube, as was mentioned in Chapter 5. A test of the response of the thermocouple to heating was conducted to determine whether the sheath material affected the rate of heating.
8.3.1 Test Procedure A thermocouple was fixed in a vice so that the tip of the probe was held 1” from the end of an unlit propane torch. The torch was ignited with a flint and the flame adjusted until the steady state temperature of the thermocouple was 1200ºC. The position of the flow valve was noted and the torch extinguished. The test was repeated two more times, but with the propane set to the desired flow rate (noted in the first test) prior to ignition of the torch. The same data acquisition system used to record the thermal data in the friction stir weld experiments was used (see Appendix B for details). The acquisition rate was 500 Hz. The data collected was analyzed using single sensor differential thermal analysis. A second order polynomial was fit to the data from 800ºC to 1000ºC. The measure temperature was plotted against the difference between the fit curve and the measured temperature. Figure 8.9 shows the data collected from one thermocouple from torch ignition to roughly 40 seconds after the flame was extinguished.
172
Thermal Response of Inconel Sheathed K-Type Thermocouple in Torch Flame
1400
1200
1000
800
600 Temperature (°C) Temperature 400
200
0 0 10203040506070 Time (s)
Figure 8.9 Thermal response of sheathed thermocouple held 1” from propane torch
Figures 8.10 and 8.11 show SS-DTA plots for the two tests in which the propane was set to the desired flow rate before ignition of the torch. Both plots showed a sudden change at 950ºC. The effect occurred over a very small temperature range. Conversations with Dr. Boian Alexandrov have revealed that the same spike has occurred in his analysis of materials heated in a furnace. Tests to determine the cause of this phenomenon are ongoing. The current theory is that it is caused by the K-type thermocouple itself.
173 SS-DTA of Inconel Sheathed Termocouple Heated by Torch - Test 1
1000
980
960
940
920
900
880 Temperature (°C) 860
840
820
800 -1 -0.5 0 0.5 1 1.5 2 Delta T (°C)
Figure 8.10 Single sensor differential thermal analysis for an Inconel 600 sheath heated by a propane torch
SS-DTA of Inconel Sheathed Thermocouple Heated by Torch - Test 2
1000
980
960
940
920
900
880 Temperature (°C) 860
840
820
800 -1.5 -1 -0.5 0 0.5 1 1.5 2 Delta T (°C)
Figure 8.11 Another single sensor differential thermal analysis for an Inconel 600 sheath heated by a propane torch 174 8.4 Summary of Phase Transformation Data Processing
Comparison of the equilibrium phase diagrams to the dilatometer and SS-DTA measurements show that the transition temperatures can be affected by the rate of heating. In both the iron rod and the HSLA-65 plate the A1 temperature during rapid heating was elevated from equilibrium A1 temperatures near 700ºC to temperatures above 800ºC. The completion of the transformation from bcc to fcc iron was similar in both alloys as well and occurred at or just above 880ºC. Table 8.1 summarizes the results of dilatometry and SS-DTA results for both alloys.
Dilatometry SS-DTA Dilatometry SS-DTA SS-DTA Material Ac1 Ac1 Ac3 Ac3 A2 Iron Rod 820 820 872 875 776 0.25”HSLA-65 835 823 883 885 778
Table 8.1 Summary of phase change temperature tests for iron rod and 0.25” HSLA-65 plate (all temperatures ºC)
175
CHAPTER 9
DISCUSSION
The data collected from the experiments three types of experiments (friction stir welds, hot torsion, and differential thermal analysis) point to two important factors which have tremendous effect on the friction stir welding process in iron and its alloys: the allotropic phase transformation and the activation energy for deformation.
9.1 Localized Strain
The hot torsion tests in iron and HSLA-65 which utilized a scribed line for the measurement of strain showed strain localized in the intercritical temperature region. The localization of the deformation when the torsional load was applied is due to the parabolic temperature profile and the difference in activation energy in ferrite and austenite. Researchers studying the hot deformation properties of metals have reported that the calculated activation energy for deformation (derived from the Zener-Holloman parameter) is very close to the activation energy for self diffusion. In his review of literature of reported values for the activation energy of self diffusion [97], Oikawa presented suggested values for the activation energy of self diffusion for magnetic ferrite, paramagnetic ferrite, and austenite in iron. These suggested values are given in Table 9.1.
176 Phase Qdiff (kJ/mol) Magnetic Ferrite 294.4 Paramagnetic Ferrite 240.9 Austenite 291.3
Table 9.1 Suggested values for activation energy for self diffusion in iron (from Oikawa [97])
9.1.1 Changes in Iron Flow Stress Flow stress is a function of the Zener-Holloman parameter which is described by the formula:
. Z = ε⋅ e (Qdef / RT )
If strain rate (ε˙) is held constant, then Z becomes dependent upon e(Q/RT). Thus, at constant strain rates, the flow stress is a function of the activation energy for deformation and the temperature of the material. By using Oikawa’s suggested activation energies for self diffusion and the equilibrium volume percent of ferrite and austenite calculated with the lever law in the intercritical region, a plot of the variation in the Zener-Holloman parameter for constant strain rate against temperature was created for the carbon content of the iron bar (Figure 9.1). In addition to the constant strain rate plot, a surface plot showing the change in Z with both temperature and strain rate was created. This plot is shown in Figure 9.2. First, the value for e(Q/RT) was calculated for each phase. Next, the volume percent of ferrite and austenite was calculated for the carbon composition of the iron bar over a temperature range from just below the equilibrium A1 temperature to just above the equilibrium A3 temperature. By multiplying the volume percent of each phase by the calculated e(Q/RT) value for that phase and summing the products, an average e(Q/RT) was calculated. The equation looked like this:
%ferrite · e(294400/RT) + % austenite · e(291300/RT) 177 at temperatures below the Curie temperature and like this:
%ferrite · e(240900/RT) + % austenite · e(291300/RT) at temperatures above the Curie temperature. Examination of the formula and values for the activation energy reveal that the Curie temperature should have a significant effect on the flow stress. Also, the sudden increase in volume percent austenite as the A3 temperature is approached should cause an increase in the flow stress, due to the higher activation energy for deformation of austenite compared to that for paramagnetic ferrite.
Calculated Combined Zener-Holloman Parameter (constant strain rate of 1)
1E+13
9E+12
8E+12
7E+12
6E+12
5E+12
4E+12 Zener-Holloman Parameter Zener-Holloman 3E+12
2E+12
1E+12 750 800 850 900 950 1000 Temperature (°C)
Figure 9.1 Change in volume percent phase averaged Zener-Holloman parameter for iron with 0.029 wt% C at a constant strain rate
178 Intercritical Zener-Holloman Parameter
9E+13-1E+14 8E+13-9E+13 7E+13-8E+13 6E+13-7E+13 5E+13-6E+13 4E+13-5E+13 1E+14 3E+13-4E+13 2E+13-3E+13 9E+13 1E+13-2E+13 8E+13 0-1E+13 7E+13 6E+13 9 5E+13 7 4E+13 3E+13 Strain Rate (1/s) 5 2E+13
3 1E+13 Zener-Holloman Parameter 0 1 760 770 780 790 800 810 820 830 840 850 860 870 880 890 Temperature (°C)
Figure 9.2 Change in the volume percent phase averaged Zener-Holloman parameter for varying strain and temperature
179 The minima of the volume fraction phase averaged Zener-Holloman parameter occurs at 863ºC, which corresponds to the temperature at the initiation of torsion where the most strain occurred in standard hot torsion samples (See Chapter 6).
9.1.2 Localized Strain in Iron Hot Torsion Samples The hot torsion tests using standard samples, which showed strain localization in the iron, were chosen for examination by the method of volume fraction phase averaged Zener-Holloman parameter. In particular, the samples labeled run 5 and run 6, which had strain localized in the center and on either side of the center respectively were chosen. Because strain rate varied across the samples gage section, the value for only e(Q/RT) was calculated. Figure 9.3 shows a plot of the average values of e(Q/RT) against the distance from the left shoulder of the gage section for run 5 and run 6 of the standard iron torsion sample strain tests. Comparison of the plots for the average e(Q/RT) profile in the iron hot torsion samples showed excellent correlation to the distribution of strain. In both samples, the deformed region which showed preferred grain orientation was located where the value of e(Q/RT) was less than 4·E12, which corresponds to a temperature range from 814ºC to 892ºC at the initiation of torsion.
180 e(Q/RT) Profile in Iron Hot Torsion Samples
1E+13
9E+12 Run 5 Run 6 8E+12
7E+12
6E+12
5E+12
Zener-Holloman Parameter Zener-Holloman 4E+12
3E+12
2E+12 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Distance from Left Shoulder (in)
Figure 9.3 Plot of the average e(Q/RT) value across the gage section of standard hot torsion samples (Run 5 – 875ºC at center, Run 6 - 900ºC at center)
9.1.3 Conceptual Model of Strain Localization The fact that the region of localized strain in the iron samples extends to either side of the region where the averaged value of e(Q/RT) is a minimum may be explained by two things: a change in phase stability and heating due to internal friction. At temperatures above 863ºC, an increase in the thermodynamic stability of ferrite, brought about by strain could effectively lower the local flow stress by changing the volume fraction of ferrite. At temperatures below 863ºC the strain would also induce an increase in the volume percent of ferrite. However, the temperature profiles of iron torsion samples also showed significant heating in the intercritical temperature region. Higher heating rates were associated with lower initial temperatures. At positions in the torsion samples where the equilibrium temperature just before the initiation of torsion was below 863ºC, the heating caused by deformation would lower the flow stress. Since strain in a torsion sample is highest at the outer surface, heating would begin where the
181 strain was greatest and flow stress was a minimum. Figure 9.5 illustrates this concept by showing the temperature and volume percent ferrite profiles for a torsion sample before and during torsion.
182 Temperature Profile Volume % Ferrite
A
B
C
Figure 9.4 Conceptual representation of changes caused by torsion of non-uniform temperature sample. (Isotherms represented by lines in left column, ferrite represented by white in right column)
183 The explanation of the strain localization concept shown in Figure 9.4 is as follows. At A, prior to initiation of torque, a parabolic temperature profile exists and the volume % of ferrite decreases from a maximum at the edges of the gage section until there is no ferrite in the center. At B the application of torque is initiated. With the application of torque, strain is localized where the flow stress is a minimum. Strain is greater at the outer surface and the sample begins to cool in the interior relative to the outer surface. The ferrite phase increases in volume due to strain induced transformation and heating occurs from adiabatic shearing. As torsion continues (stage C), the volume heated by adiabatic shearing grows with the region of strain induced ferrite transformation . Heating occurs at the outer surface where the strain is greatest. The LCRSM experiments in both iron and HSLA-65 showed that the rate of heating achieved during torsion was strongly dependent upon the strain (rate of revolution) and the test temperature of the run. Low temperatures and high strain rates produced the highest heating rates. Thermocouple data acquired during the LCRSM experiment in iron showed that heating occurred preferentially in the intercritical region and the rate of heating in this region decreased as the temperature approached the Ac3 temperature.
9.2 Heat Generation in Friction Stir Welding
The localized straining and heating detected in the hot torsion experiments have implications for the friction stir welding process in iron alloys. The application of strain can affect the thermodynamic stability of a phase and the relative volume of each phase in existence can affect the flow stress at a given temperature. By correlating this information with what was learned from the hot torsion experiments, a conceptual model for the generation of heat and development of regions within the weld may be developed.
9.2.1 Heat Generated by the Shoulder The friction of the tool shoulder on the top surface of the plate generates heat at the interface. The tool heats up as a result of the friction and apparently reaches a steady state temperature of 1260ºC when welding HSLA-65. Heat from the shoulder is conducted into
184 the plate at the interface between the shoulder and plate. Marker experiments showed material beneath the shoulder is sheared and moves from the advancing side of the tool around the retreating side and is left at the trailing edge of the tool. The pressure of the shoulder on the surface of the plate and the straining of the material under the shoulder is capable of creating a forge weld below the shoulder to a depth of 0.125” in the absence of a pin.
9.2.2 Heat Generated in the Shear Zone The friction stir welds made with embedded markers showed that material deeper below the surface of the plate is also rotated around the tool from the advancing side to the retreating side before being deposited behind the tool. The radius around which the material rotates decreases as distance from the shoulder (depth in plate) increases. This material is heated by adiabatic heat from shear as the tool advances. The thermocouple data from the HSLA-65 friction stir weld instrumented with Inconel sheathed thermocouples showed very high heating rates at low temperatures which decreased as the Ac3 temperature was approached. This is very similar to the data which was acquired in the hot torsion experiments in the region where strain and heating was localized. After a plateau in temperature, the heating rate increased again before the peak temperature was reached and cooling began. The instantaneous heating rate at a given temperature as the tool approached the position of the embedded thermocouples can be calculated from the acquired data by taking the slope of the temperature versus time at that point. The heating rate can then be plotted against temperature, or the calculated position of some part of the tool geometry. Plots of this type are shown in Figures 9.5 and 9.6 for data acquired by one of the Inconel sheathed thermocouples in weld HSLA-65-6.
185 Instantaneous Heating Rate at Thermocouple Channel 2 (bottom of plate)
1000
900
800
700
600
500
400 Temperature (°C) Temperature 300
200
100
0 0 100 200 300 400 500 600 Heating Rate (°C/s)
Figure 9.5 Temperature versus heating rate measured at the bottom of the plate during weld HSLA-65-6
186 Heating Rate Relative to Distance to Leading Edge of Tool Pin
600
500
400
300
Heating Rate (°C/s) 200
100
0 -0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 Distance (in)
Figure 9.6 Heating rate plotted as a function of distance from the leading edge of the advancing tool pin on the bottom of the plate in weld HSLA-65-6
Initially, the plate is heated by conduction of heat through the plate. There appears to be a decrease in heating rate from 340ºC to 390ºC. The heating rate increases rapidly after this point until reaching a peak of 504ºC/s at 478ºC. After this the heating rate decreases with oscillating peaks for approximately every 0.02” of tool travel. At 881ºC the heating rate begins to increase again until reaching 945ºC and decreases until the peak temperature is reached and cooling begins. Conceptually, the region from 390ºC to 478ºC heats rapidly as the shear stresses caused by the approaching tool begin to cause deformation and dislocations within the grains multiply and move through the crystal lattice in individual grains. It may be that, at this point, the temperature has increased to the point that the flow stress has decreased enough for the stresses caused by the tool to begin causing deformation. Above 478ºC, the rate of heating is decreasing. If the model for heating rate from the torsion experiments holds true, the decrease in heating rate means the Zener-Holloman
187 parameter is decreasing. A decrease in this parameter could be caused by several things: an increase in temperature, a decrease in strain rate, a decrease in activation energy for deformation due to a change in the relative amount of phases present in the structure, or by a combination of these. As the tool gets closer to the point at which the temperature is being measured, the radius of rotation (from the axis of the tool to the point of measurement) is decreasing. Since shear strain is proportional to radius, the strain rate will decrease as the tool approaches. It is also possible that some phases formed by the complex metallurgy of the alloy are dissolving into the matrix at this temperature. ThermoCalc analysis of the composition of the ¼” HSLA-65 plate suggests that M3P particles and M7C3 carbides will dissolve at approximately 395ºC and 490ºC respectively. If this is the case, the change in volume percent of these phases could affect the flow stress in this temperature region. The increase in heating rate at elevated temperature is most likely due to the formation of a critical volume percent of austenite. As was shown in the first section of this chapter, once enough austenite is formed, the Zener-Holloman parameter will increase until all the ferrite has transformed to austenite. Once a completely austenitic structure has been formed, the flow stress will continue decreasing as temperature increases. With this understanding, the A3 temperature for the conditions at the position of the thermocouple is determined to be 945ºC. This transformation is at a higher temperature than that observed in samples of the same material heated at 600ºC/s in the Gleeble. The oscillations in heating rate observed between the peak heating rate at 478ºC and the formation of a completely austenitic structure at 945ºC is not completely understood, but could be explained by an oscillation within the mechanical system of the welding machine itself. The regular frequency of the oscillation suggests the machine is the cause. Plots of the heating rate at the top of the plate were also created. These are shown in Figures 9.7 and 9.8.
188 Instantaneous Heating Rate at Thermocouple Channel 5 (top of plate)
1200
1000
800
600 Temperature (°C) Temperature 400
200
0 0 200 400 600 800 1000 1200 Heating Rate (°C/s)
Figure 9.7 Temperature versus heating rate measured at the top of the plate during weld HSLA-65-6
As can be seen in this plot, the heating rate on the top surface increased rapidly and began to decrease after the temperature reached 503ºC. This was followed by oscillations in the heating rate during a general decrease in the heating rate until the peak temperature was reached and cooling began.
189 Heating Rate Relative to Distance to Leading Edge of Tool Pin
1200
1000
800
600
Heating Rate (°C/s) Rate Heating 400
200
0 -0.16 -0.14 -0.12 -0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 Distance (in)
Figure 9.8 Heating rate plotted as a function of distance from the leading edge of the advancing tool shoulder on the top of the plate in weld HSLA-65
The steeper heating rate at the top of the plate makes the distance from the advancing tool to the edge of the shear zone smaller than was observed on the bottom of the plate (0.12” on top versus 0.15” on bottom). The recurring oscillation at 0.2” intervals makes the friction stir welding machine the most likely candidate as the cause of the noise. The oscillations make determination of the A3 temperature in this sample impossible as the oscillations in heating rate continue throughout the region where the phase change is anticipated to take place. Examination of the surface of the weld revealed that the ridges left by the tool were actually composed of one large and one small ridge. Figure 9.9 shows an image of the ridges on the weld surface. A measurement of the distance from the beginning of one ridge to the same feature three ridges away along the centerline of the weld revealed that 190 this distance was 1.55 mm. Dividing this distance by three and converting to inches gives a distance of 0.02”, exactly the distance the tool traveled between major peaks in the oscillating heating rate.
Figure 9.9 Magnified view of the surface of weld HSLA-65-6 showing repeating pattern of ridges
The oscillation observed in the heating rate and the alternating ridges and valleys of the weld surface must be caused by the mechanical systems of the welding machine. Either the feed mechanism is oscillating, or the tool is not rotating at a constant rate. To test this theory, the ridges on one of the iron welds, made with a feed rate of 6 ipm and tool rotation speed of 350 rpm were examined. If the feed rate was the determining factor, the spacing between ridges should be the same. If however, the rotational velocity of the tool was oscillating the distance between ridge features should be about 0.017”. This is the distance the tool travels in one rotation. The measurement of the distance between 13 ridges was 5.75 mm. This converts to approximately 0.017”, which means the repeating features on the surface of the weld are directly related to the rotational 191 velocity of the tool. The fact that the oscillations in heating and the spacing of the ridges created by the tool on the surface of the weld occur at the same frequency suggests that the cause of the ridges and heating fluctuations is the same. The difference in the heating rate at the shear zone on the surface ( > 1000ºC/s) and the heating rate observed at the bottom of the plate ( ~ 500ºC/s) can be explained by the radius of the shear zone. The model created in the hot torsion experiments for the heating rate was largely a function of the temperature and the rate of strain. The marker experiments showed that the area around which the markers were stirred was larger near the shoulder than it was near the bottom of the plate. Since the shear strain developed by a rotating part in contact with another is dependent upon the radius, the larger radius of the shoulder, relative to the pin, should create a higher heating rate.
9.2.3 Observed Decrease in Cooling Rate The same method used to examine the heating ahead of the tool as it advances through the material is capable of providing useful information about the cooling of the material after the tool has passed. The instantaneous cooling data for the thermocouple on the bottom which was used to create the instantaneous heating data for the plots in Figures 9.5 and 9.6 was plotted in a similar manner. Plots of the instantaneous cooling rate for measured temperatures and cooling rate versus tool position are shown in Figures 9.10 and 9.11. Rather than using the position of the leading edge of the tool pin as a reference, the trailing edge of the tool pin was used. It can be seen in the plots that a decrease in cooling rate occurred between 953ºC and 909ºC. This is evidence of the creation of heat in that temperature range.
192 Instantaneous Cooling Rate at Thermocouple Channel 2 (bottom of plate)
1000
900
800
700
600
500
400 Temperature (°C) 300
200
100
0 -60-50-40-30-20-100 Cooling Rate (°C/s)
Figure 9.10 Temperature versus cooling rate measured at the bottom of the plate during weld HSLA-65-6
193
Cooling Rate Relative to Distance to Trailing Edge of Tool Pin
0
-10
-20
-30
Cooling Rate (°C/s) Cooling -40
-50
-60 -0.5 0 0.5 1 1.5 2 Distance (in)
Figure 9.11 Cooling rate plotted as a function of distance from the trailing edge of the advancing tool pin on the bottom of the plate in weld HSLA-65-6
The decrease in cooling rate nearly mirrors the increase in heating rate observed in front of the tool. In the discussion of heating, the cause for this change was suggested to be the change in flow stress associated with the transformation from ferrite to austenite. The same argument holds true here. As was shown in the analysis of activation energy effects on flow stress in the hot torsion samples, a peak in the flow stress occurs at the A3 temperature due to the higher activation energy for deformation associated with austenite relative to ferrite. As the material in the weld cools from its peak temperature above the A3, the Zener-Holloman parameter increases, which the ANOVA model created from hot torsion testing predicts will result in an increase in heating rate (or decrease in cooling). The Zener-Holloman
194 parameter decreases as ferrite begins to form, resulting in easier deformation and less heat generation. The temperatures over which this change in heating rate occurs would not normally be associated with the Ar3 and Ar1 temperatures. However, in the presence of strain caused by the rotating tool, the thermodynamic stability of ferrite may be favored. In an attempt to illustrate this concept, the e(Q/RT) value for each temperature measured was calculated. A standard iron-carbon phase diagram was used to calculate the volume percent ferrite and austenite which would be present for the carbon content of the 0.25” plate (0.085 wt%) at equilibrium. The activation energies for the ferrite and austenite in the HSLA-65 plate are unknown, but in the interest of illustrating the concept the values for activation energy used previously for the iron were used. As can be seen in the plot of e(Q/RT) in Figure 9.12, there are two peaks which correspond to the transformation to austenite. By plotting the heating rate data against the same x-axis, it is apparent that the heating rate follows a similar relationship, with decreases in the heating approximately following the decreases in the value of e(Q/RT). That the two plots do not have maxima and minima at the same positions is due to several things. The actual activation energies are unknown for the HSLA-65, which could cause some deviation. Also, the calculation of e(Q/RT) is based on equilibrium conditions, which are not the conditions for material being heated in a weld. Superheating could delay the transformation. Additionally, the stabilizing of the ferrite phase by the strain induced by the tool could also cause a delay in the transformation to austenite.
195 Equilibrium Flow Stress and Actual Heating Rate
4E+13 300
3.5E+13 250 e(Q/RT) Heating Rate 3E+13 200
2.5E+13 150
2E+13 100 e(Q/RT)
1.5E+13 50
1E+13 0 (°C/s) Rate Heating/Cooling
5E+12 -50
0 -100 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 Distance from Leading Edged of Tool Pin (in)
Figure 9.12 Overlaying plots of heating relative to tool position and calculated e(Q/RT) for equilibrium conditions
It should be noted that the minimum in both the heating rate occurs at a point approximately 0.1875” after the passage of the leading edge of the pin. Since the pin has a radius of 0.375”, this minimum corresponds with the center of the pin being directly over the thermocouple. If the material rotating around the pin is considered to be a torsion sample, where the shear strain is a function of the radius, then the shear strain should be at a minimum when the radius is zero, the center of rotation. The second peak in heating rate, which occurs when the leading edge of the tool has moved beyond the thermocouple by about 0.27” would then be associated with decreasing temperature in the austenite. The decrease in heating rate which follows this peak would then be associated with the formation of ferrite and a decrease in flow stress. The most likely cause of this transformation, as was mentioned earlier, is the presence of strain. 196 9.3 Estimation of Strain in HSLA-65 Friction Stir Weld
The thermal data from the friction stir welds allowed plots of measured temperature against instantaneous heating rate to be made. The hot torsion tests in HSLA-65 allowed mathematical models which predicted the heating rate at the center of the hot torsion sample for the range over which testing was conducted (see Figure 7.13). The model showed that heating rate measured in the torsion samples was strongly dependent upon the test temperature and the rate of rotation, which is equivalent to strain rate. It seems probable that by using the hot torsion model, a given temperature and heating rate recorded in a friction stir weld might be used to estimate the strain required to cause the measured heating rate at that temperature. Unfortunately, there is little overlap of heating rates and temperatures for the hot torsion experiments and friction stir welds. Additionally, the oscillating heating rate makes use of the heating rate data difficult. It is hoped that friction stir welds made on a different machine will not produce the oscillations observed in heating rate and allow a comparison between hot torsion sample and friction stir weld heating.
9.4 Grain Size Significance
Tests for significance of the hot torsion control variables on the resulting grain size were inconclusive. However, this does not mean that the control variables do not affect the grain size. It is possible that all the tests were conducted at total strains above the critical strain required for dynamic recrystallization. If this is the case, then refined austenite grains would be expected in the hot zone of the hot torsion samples. Unfortunately, the control of cooling rates below 730ºC was not possible, so all the samples had essentially the same Δt8-5 times with the application of the helium quench. In the future, tests which utilize thermocouples at the sample center and less than half of one full revolution of torsion may provide the cooling rate control needed to obtain a variety of structures and grain sizes. It would also be advisable to test a material which does not change phases, such as an austenitic stainless steel, in an attempt to better understand the effect of strains on the microstructure at high temperatures. 197 9.5 Conceptual Model for Ferrous Friction Stir Welds
The combination of the thermal data from the welds, weld marker experiments, the microstructures created in the hot torsion experiments, EBSD orientation deviation maps, and models developed from ANOVA gives a general overview of the heating and deformation which occurs in a ferrous friction stir weld. With this knowledge, a conceptual model for the development of the weld regions can be developed. As the tool rotates, it generates heat at the interface between the tool and the weld material. When the tool advances into the metal, a shear load is applied at the leading edge of the pin and a void opens behind the pin. Heat generated at the interface of the tool and material (both the shoulder and pin) conducts into the plate, creating a temperature gradient. The flow stress of the material is reduced as its temperature increases. The combination of the shear load and the reduced flow stress causes material close to the pin to rotate around it, where it fills the void left by the advancing pin. At some distance from the pin, the flow stress of the material is high enough that dislocations are formed, but the material does not flow. Strain induced ferrite formation at elevated temperature and superheating delay the formation of austenite, allowing ferrite to exist at higher temperatures than equilibrium conditions would allow. When austenite finally does form, the increase in the activation energy for deformation relative to ferrite causes an increase in the heating rate. Material in the center of the weld is heated above the Ac3 temperature and transforms to fine grained ferrite upon cooling. The material which remains in the intercritical temperature region during deformation appears to have undergone recrystallization. The grains in this region appeared to have little grain orientation deviation and few subgrain boundaries. Whether the recrystallization which caused this structure was dynamic or metadynamic is not certain. In hot torsion samples the region associated with this temperature range appeared to have larger grains than the surrounding material. This may be due to abnormal grain growth by strain-induced grain boundary migration, classical static recrystallization, or metadynamic recrystallization. Further study will be required to determine the actual process responsible for the formation of this region. 198 Finally, the region which was heated to temperatures below the Ac1 temperature appears to undergo deformation, as evidenced by the high heating at temperatures below the Ac1 and the subgrain boundary networks visible with EBSD. Since ferrite recovers easily, this region does not undergo recrystallization, but recovers by polygonization. The result is high grain orientation deviation and subgrain boundaries within individual grains.
weld centerline
FGZ γ
Ac3 ICZ Ac1 RZ Increasing temperature temperature Increasing
wt% carbon
Base metal
Figure 9.13 Suggestions for nomenclature of zones in ferrous friction stir welds
Based on the above discussion, different nomenclature for the microstructural zones produced by the friction stir welding process in ferrous materials is proposed. The center of the weld, which is commonly referred to as the stir zone might more appropriately be termed the fine grained zone (FGZ). The FGZ is that portion of the thermomechanically affected material which has been heated into the austenitic region and upon cooling transforms into fine grains. Whether this region has undergone dynamic recrystallization 199 or not is debatable as the transformation to ferrite on cooling erases the evidence. The region which has been heated into the intercritical region is more likely to deform due to the higher temperatures and decrease in ferrite flow stress associated with the temperature increase. The proposed name for this region is the intercritical zone, or ICZ. In the hot torsion tests this region was textured, with a preferred orientation of the <111> direction tangent to the edge of the rotating tool. As was discussed above, the formation of the structure in this zone may be due to dynamic or metadynamic recrystallization. Finally the region which was deformed below the Ac1 temperature, but heated sufficiently to recover might be called the recovered zone (RZ). If the recovery is found to be dynamic in nature, it might be called the dynamic recovery zone (DRZ). These terms seem more appropriate for the observed temperatures and microstructures in this study.
9.6 Implications of Modified Hot Torsion Testing
The modified Gleeble® hot torsion test which was developed in this work has many implications to the research and development of friction stir welding. The ability to rapidly heat, strain, and cool are all necessary for the simulation of friction stir welding. This new test provides each of these capabilities. The production of microstructures which are similar to those observed in friction stir welds is promising. The measurable strain distribution, temperature profile, and acquisition of adiabatic heating due to shear strain during torsion testing should enable better modeling of friction stir welding by providing quantitative data with which to compare computer models. As was mentioned in section 9.3, it is believed that estimates of the strain may be made in the future by use of models developed from hot torsion tests. With continued work, it is believed a direct relationship between the hot torsion test and the friction stir welding test can be developed. There are several items which prevented the development of this relationship in the course of the current study that must be considered in the future. Ideally, a designed experiment, in which the control parameters for the friction stir welding machine are varied, would have been carried out. ANOVA of the quantified
200 results could provide a model which optimizes the welding parameters for the desired outcome. The excellent fit of the hot torsion ANOVA models to the experimental data suggests models of friction stir parameter effects on measured output could have excellent fit as well. As an example, an experiment in which the angle of the weld tool, the travel speed, and the rotational velocity were controlled variables could be conducted. Utilizing the LCRSM experimental design would require 9 welds to be made. If the welds were made on a fully instrumented machine, and each plate utilized embedded thermocouples, models for the effect of the input parameters on peak temperature, peak instantaneous heating rate, distance from leading edge of the tool to the peak heating rate, cooling rate, size of the weld, torque, tool loading in each orthogonal direction, difference in peak temperature at the top and bottom of the plate, and a variety of other outputs could be created. In the current work, enough material was provided for only 6 welds in HSLA-65, which was not enough for even a simple screening experiment. It took three welds just to determine parameters which provided acceptable welds. Adequate material for determining operating parameters and performing a designed experiment must be obtained if this type of experiment is to be conducted. Welds made on a different machine, which is capable of making precise measurements of the torque on the tool during welding would be of great benefit for additional testing. The Gleeble® torsion system is capable of controlling the torsional loading of a sample by torque rather than rotation and rate of rotation. It would be possible to apply the same constant torque to a hot torsion sample that was measured by the friction stir welding machine. Using the scribed line technique, it would be possible to measure the strain induced across the gage section as a result of loading at a constant torque. Measuring the number of revolutions would allow calculation of shear strain and rate of strain for the constant torque. The variety of input and output variables possible makes the hot torsion test invaluable for developing quantified data for friction stir weld models.
201
CHAPTER 10
CONCLUSIONS
Friction Stir Tracer Experiments
1. The 0.0625” 308 stainless steel markers performed satisfactorily as a tracer in both ingot iron and HSLA-65 friction stir welds. The 0.0625” markers did not produce measurable loading of the tool in the friction stir welds made in both materials.
2. The 0.0625” embedded markers were moved around the retreating side of the pin and deposited behind the tool.
3. Material near the upper surface of the plate is acted upon by the tool shoulder, which has a larger radius than the tool pin. The result is that material near the surface, which is in contact with the shoulder, is deposited a greater distance behind the initial position of the marker, relative to the direction of tool travel, than material which is deeper in the plate.
202 HSLA-65 Thermocouple Instrumented Weld
4. 0.0625” Inconel 600 sheathed thermocouples pressed into a plate provide excellent temperature data for the end of the probe in friction stir welds. When positioned on the bottom of the plate, the thermocuoples were deformed very little and recorded data throughout the welding procedure.
5. The peak temperature at the top surface of a weld made in HSLA-65 exceeded 1200°C.
6. At the bottom of the plate the peak measured temperature reached 1000°C.
7. The temperature gradient at the leading edge of the advancing tool is composed of a conduction heated region and a shear heated region.
8. The peak temperature measured on the centerline of the tool at the top surface of the plate was greater than that measured at the bottom of the plate.
9. The instantaneous heating rate in the shear heated region at the top of the plate approached 1100ºC/s.
10. The instantaneous heating rate in the shear heated region at the bottom of the plate just exceeded 500ºC/s.
11. The peak heating rate in the shear zone occurred at temperatures between 350ºC
and 500ºC, well below the Ac1 temperature for HSLA-65.
12. The instantaneous heating rate at the bottom of the plate increased at temperatures between 876ºC and 942ºC on heating.
203 13. The instantaneous cooling rate measured on the bottom of the plate decreased at temperatures between 953°C and 909°C after the tool had passed.
14. The regions of a ferrous weld do not include a true HAZ, as the deformation
caused by the tool extends well below the Ac1 temperature. Rather, a fine grained heat and deformation affected zone, an intercritical heat and deformation affected zone, and a below critical heat and deformation affected zone are observed.
Hot Torsion Testing
15. Gleeble® hot torsion samples which have been modified to allow internal gas quenching are capable of producing microstructures similar to those produced in friction stir welds made in the same material.
16. Strain and heating are localized in the intercritical temperature region due to differences in activation energy for deformation in ferrite and austenite. As a result, iron hot torsion samples having temperature gradients across the gage
section with peak temperatures within 25ºC of the A3 temperature deform preferentially in the intercritical region.
17. Analysis of Variance (ANOVA) for data acquired from designed experiments can provide models with excellent fit for the effect of control variables (temperature, revolutions, and rate of revolution) in Gleeble hot torsion tests.
18. ANOVA of heating rates in hot torsion samples showed a proportional relationship to the Zener-Holloman parameter.
204 Modeling Ferrous Friction Stir Welds with Hot Torsion Data
19. Modeling of heating rates for a given test temperature caused by known strain rates in torsion testing can provide a basis for estimating the strain rate necessary to produce the heating rates measured by thermocouples embedded in friction stir welded plates.
20. Continued work with larger ranges for test temperature and strain rate are necessary for overlap of hot torsion models with the observed temperatures and heating rates observed in friction stir welding.
205
CHAPTER 11
SUGGESTIONS FOR FUTURE WORK
While this investigation has lead to a conceptual model for the thermomechanical effects of the FSW process on steel, there is additional work which would enhance the understanding of friction stir welding. The following are a few suggestions for future work which would build upon the present study. The effect of the change in phase on the shear heating characteristics is evident from the present study. A better understanding of the effects of the phase transformation on heating rate and strain localization in steels might be achieved by a series of hot torsion experiments in the intercritical temperature region on plain carbon steels with varying carbon contents. The varying carbon content would change the flow stress and the temperature range over which the transformation from ferrite to austenite occurs. The phase transformation in the stir zone, which occurs in iron alloys, obscures the understanding of the effect of the process on grain size at elevated temperature. The localization of strain in the intercritical region during some hot torsion tests also complicates testing. For future work it is suggested that 304 stainless steel be used for studying friction stir weld process parameter affects on microstructure. 304 stainless steel is austenitic and does not undergo a phase transformation and it does not recover easily. 304 also melts at high temperatures, which would allow torsion testing in the Gleeble without modification of the pyrometer control system. These qualities make 304 stainless steel an ideal candidate for studying the effects of friction stir welding parameters on microstructure development.
206 Titanium is another alloy which merits study by the techniques discussed in this document. Like iron, titanium undergoes an allotropic phase transformation upon heating, from a hexagonal close packed structure at lower temperatures to a body centered cubic structure at elevated temperature. Titanium has proven to be joinable by the friction stir welding process. Work by Nix and Ilschner [98] showed that the activation energy for self diffusion in α-Ti (stable at room temperature) is lower than the activation energy for self diffusion in β-Ti (high temperature phase). It would be interesting to see if the same type of strain and heat localization observed in iron during this study occurs in titanium at temperatures below the beta transus temperature. The use of metal sheathed thermocouples has proven to be a simple and useful method for gathering temperature data from the stir zone of a friction stir weld. Additional experiments, in which data collected from thermocouples placed at a variety of distances from the weld centerline on both the advancing and retreating side of a weld would allow isotherm mapping and could be beneficial to improving the understanding of heat generation in friction stir welds. The use of single sensor differential thermal analysis on this data would also be helpful in better understanding phase transformation behavior. Welds in this study were all made on the same machine. It would be interesting to see if other friction stir welding machines exhibit the same ridge width to rotation speed characteristic observed in this study. In this study, a weld was made to half the thickness of a plate when the tool pin sheared off, leaving only the tool shoulder rotating and pressing on the surface of the plate. Researchers attempting to model the heat input from a tool could benefit from collecting data from welds made with only a shoulder and welds made with a shoulder and pin. Comparison of temperature to tool position for the two different tools could aid in improving modeling heat generation in the friction stir welding process. The mechanical differences between bcc and fcc iron clearly have an effect on the heating rate and strain in iron alloys. Future computer models for the friction stir welding process in iron alloys should take into consideration the differences in activation energy for deformation between bcc and fcc iron. The location of the heat generation may be 207 found with a scanning infrared camera. If properly calibrated, the camera could determine where the temperature is increasing most as torque is applied to the sample. The method used in this work to create plots of shear strain versus temperature has great potential for determining hot deformation properties with very few samples. With some development of the technique, it is believed that activation energies for deformation could be calculated from carefully conducted tests. The problem that arose in the current test was localized heating. Local heating during deformation changes the temperature profile and prevents an accurate plot of ln ε˙ versus 1/T, where the slope of the line is equal to the activation energy. The Gleeble is capable of passing current through a sample while the hydraulic motor turns the sample, as long as the rate of rotation does not exceed 2 rpm. Straining at this low rate would most likely prevent significant heating from torsion and would allow the resistive heating to maintain a parabolic temperature profile in the sample. Using this technique, it may be possible to determine the activation energy for deformation with only one sample. The thermal analysis techniques used in this study proved to be very sensitive to very small changes in thermal gradients. Additional experiments into the detection of particle dissolution, precipitation of secondary phases, and recrystallization should be conducted. Finally, the hot torsion tests used to develop the relationship between temperature and strain in this study had high strain rates with very short duration; normally just fractions of a second. It is unknown whether the strain occurred uniformly across the sample, or whether some areas were strain hardened before straining transferred to other regions. A suggestion for studying this is the use of high speed video during torsion testing to ascertain the progression of deformation during torsion.
208
REFERENCES List of References 1. Czyryca, E.J., Kihl, D.P. and DeNale, R., Meeting the Challenge of Higher Strength, Lighter Warships. AMPTIAC, Vol. 7, No. 3, p. 63-70.
2. Konkol, P.J., Warren, J.L. and Hebert, P.A., Weldability of HSLA-65 [high- strength low alloy] steel for ship structures. Welding Journal, Vol. 77, No. 9, p. 361s-371s.
3. Thomas, W.M., Murch, M.G., Nicholas, E.D., Temple-Smith, P., Needham, J.C. and Dawes, C.J., Improvements relating to friction welding, U.S. patent: 5,460,317, issued to The Welding Institute (UK) (vert bar) t T
4. Posada, M., Nguyen, J.P., Forrest, D.R., DeLoach, J.J. and DeNale, R., Friction Stir Welding Advances Joining Technology. AMPTIAC, Vol. 7, No. 3, p. 13-20.
5. Konkol, P.J., Mathers, J.A., Johnson, R. and Pickens, J.R. Friction stir welding of HSLA-65 [high strength low alloy] steel for shipbuilding. in Friction Stir Welding. Proceedings, 3rd International Symposium. 2001. Kobe, Japan TWI Ltd.
6. Nelson, T.W., Su, J.-Q. and Steel, R.J. Friction Stir Welding of Ferritic Steels. in The Fourteenth (2004) International Offshore and Polar Engineering Conference. 2004. Toulon, France May 23-28, 2004: The International Society of Offshore and Polar Engineers.
7. Posada, M., Deloach, J., Reynolds, A.P., Fonda, R. and Halpin, J. Evaluation of friction stir welded HSLA-65 [high strength low alloy]. in Friction Stir Welding. Proceedings, 4th International Symposium. 2003. Park City, UT, USA 14-16 May 2003: Abington, Cambridge CB1 6AL, UK; TWI Ltd.
8. Arbegast, W.J. Modeling friction stir joining as a metalworking process. in Third Symposium on Hot Deformation of Aluminum Alloys III as held at the 2003 TMS Annual Meeting. 2003. San Diego, CA; USA 2-6 Mar. 2003.
9. Forrest, D.R., Nguyen, J.P., Posada, M., DeLoach, J.J., Boyce, D., Cho, J. and Dawson, P. Simulation of HSLA-65 Friction Stir Welding. in 7th International Conference on Trends in Welding Research. 2005. Pine Mountain, GA, USA May 16-20: ASM International. 209 10. Metallography, Structures and Phase Diagrams. 8 ed. Metals Handbook, ed. T. Lyman. Vol. 8. 1973, American Society for Metals: Metals Park, OH. 466.
11. Reed-Hill, R.E. and Abbaschian, R., Physical Metallurgy Principles. 3rd ed. The PWS Series in Engineering. 1994, Boston: PWS Publishing Company. 926.
12. Russell, K.C., in Encyclopedia of Materials Science and Engineering. 1986, Pergamon Press: Oxford. p. 3263-3267.
13. Davis, J.R., ed. ASM Materials Engineering Dictionary. 1992, ASM International. 555.
14. Sinha, A.K., Ferrous Physical Metallurgy. 1989, Boston, MA: Butterworth Publishers. 818.
15. Decker, B.F. and Harker, D., Recrystallization in Rolled Copper. Transactions of the AIME, Vol. 188, p. 887-890.
16. Vender Voort, G.F., Committee E-4 and Grain Size Measurements: 75 Years of Progress. ASTM Standardization News, Vol. 19, No. 5, May 1991, p. 42-47.
17. Linnert, G.E., Welding Metallurgy: Carbon and Alloy Steels. 4 ed. Vol. 1. 1994, Miami, Fl, USA: American Welding Society.
18. Samuels, L.E., Optical Microscopy of Carbon Steels. 1980, Metals Park, OH: American Society for Metals.
19. Bhadeshia, H.K.D.H., Bainite in Steels. 2nd ed. 2001, London: Institute of Materials. 460.
20. Aaronson, H.I., ed. The Decomposition of Austenite by Diffusional Processes. 1962, Interscience: New York. 387-546.
21. Dubé, A., Aaronson, H.I. and Mehl, R.F., La formation de la ferrite proeutectoïde dans les aciers au carbone. Revue de Métallurgie, Vol. 55, p. 201-210.
22. Aaron, H.B. and Aaronson, H.I., Altering the Time Cycle of Heat Treatment by Controlling Grain Boundary and Subboundary Structure. Metallurgical Transactions A, Vol. 2A, No. 1, January 1971, p. 23-37.
23. Kral, M.V. and Spanos, G., Three-Dimensional Analysis and Classification of Grain-Boundary Nucleated Proeutectoid Ferrite Precipitates. Metallurgical and Materials Transactions A, Vol. 36A, No. 5, May 2005, p. 1199-1207.
24. Massalski, T.B., Massive Transformation Revisited. Metallurgical and Materials Transactions A, Vol. 33A, No. 8, August 2002, p. 2277-2283.
210 25. Hillert, M., Thermodynamics of the Massive Transformation. Metallurgical Transactions A, Vol. 15A, No. 3, March 1984, p. 411-419.
26. Jonas, J.J., Sellars, C.M. and Tegart, W.J.M., Strength And Structure Under Hot- Working Conditions. Metallurgical Reviews, Vol. 14, No. 130, p. 1-24.
27. McQueen, H.J., Development of dynamic recrystallization theory. Materials Science and Engineering A, Vol. 387-389, 15 Dec. 2004, p. 203-208.
28. Luton, M.J. and Sellars, C.M., Dynamic Recrystallization in Nickel and Nickel- Iron Alloys During High Temperature Deformation. Acta Metallurgica, Vol. 17, No. 8, August 1969, p. 1033-1043.
29. Sakai, T. and Jonas, J.J., Dynamic Recrystallization: Mechanical and Microstructural Considerations, in Acta Metall. Vol. 32, no. 2, pp. 189-209. Feb. 1984. 1984.
30. McQueen, H.J., The Role of Dynamically Recovered Substructure in Dynamic Recrystallization, in Deformation, Processing, and Structure, G. Krauss, Editor. 1982, American Society for Metals: Metals Park, OH. p. 231-238.
31. Ryan, N.D. and McQueen, H.J., Dynamic Softening Mechanisms in 304 Austenitic Stainless Steel. Canadian Metallurgy Quarterly, Vol. 29, No. 2, Apr.-Jun. 1990, p. 147-162.
32. Elwazri, A.M., Wanjaraz, P. and Yue, S., Effect Of Carbon Content On Dynamic Recrystallization Behaviour Of Plain Carbon Steels. Canadian Metallurgical Quarterly. Vol. 43, no. 4, pp. 507-512. Oct. 2004.
33. Poliak, E.I. and Jonas, J.J., A One-Parameter Approach to Determining the Critical Conditions for the Initiation of Dynamic Recrystallization. Acta Materialia, Vol. 44, No. 1, p. 127-136.
34. Sakai, T., Ohashi, M., Chiba, K. and Jonas, J.J., Recovery and Recrystallization of Polycrystalline Nickel After Hot Working. Acta Metallurgica, Vol. 36, No. 7, July 1988, p. 1781-1790.
35. Uranga, P., Fernández, A.I., López, B. and Rodriguez-Ibabe, J.M., Transition between static and metadynamic recrystallization kinetics in coarse Nb microalloyed austenite. Materials Science and Engineering A, Vol. 345, No. 1-2, March 2003, p. 319-327.
36. Xu, Z. and Sakai, T., Kinetics of recovery and recrystallization in dynamically recrystallized austenite. Mater. Trans, JIM (Japan). Vol. 32, no. 2, pp. 174-180. Feb. 1991.
211 37. Perry, A.C., Lusk, M.T. and Speer, J.G., An Analytical Model and Experimental Investigation of the Recrystallization Behavior of Hot-Deformed Ferrite. Steel Grips: Journal of Steel and Related Material, Vol. 3, No. 2, May/June 2004, p. 203-208.
38. Glover, G. and Sellars, C.M., Recovery and Recrystallization During High Temperature Deformation of Alpha-Fe. Metallurgical Transactions, Vol. 4, No. 3, Mar. 1973, p. 765-775.
39. Desrayaud, C., Girard, S., Le Coze, J. and Montheillet, F., Influence of Carbon Additions on the Dynamic Recrystallization of High Purity α-Iron. Materials Transactions JIM (Japan), Vol. 43, No. 2, Feb. 2002, p. 135-140.
40. Serajzadeh, S. and Taheri, A.K., An investigation into the effect of carbon on the kinetics of dynamic restoration and flow behavior of carbon steels. Mechanics of Materials (Netherlands). Vol. 35, no. 7, pp. 653-660. July 2003.
41. Hurley, P.J. and Hodgson, P.D., Formation of ultra-fine ferrite in hot rolled strip: potential mechanisms for grain refinement. Materials Science and Engineering A (Switzerland). Vol. 302, no. 2, pp. 206-214. 30 Apr. 2001.
42. Hong, S.C., Lim, S.H., Lee, K.J., Shin, D.H. and Lee, K.S., Effect of Undercooling of Austenite on Strain Induced Ferrite Transformation Behavior. ISIJ International, Vol. 43, No. 3, March 2003, p. 394-399.
43. Lewis, J., Jonas, J.J. and Mintz, B., The Formation of Deformation Induced Ferrite during Mechanical Testing. ISIJ International, Vol. 38, No. 3, March 1998, p. 300-309.
44. Rauf, I.A. and Boyd, J.D., Microstructural Evolution during Thermomechanical Processing of a Ti-Nb Interstitial-Free Steel Just below the Ar3 Temperature. Metallurgical and Materials Transactions A, Vol. 28, No. 7, July 1997, p. 1437- 1443.
45. Yada, H., Matsumura, Y. and Senuma, T. Massive Type Transformation Induced by Hot Deformation in Low Carbon Steels. in The International Conference on Martensitic Transformations (ICOMAT-86). 1986. Nara, Japan August 26-30, 1986: The Japan Institute of Metals.
46. Yada, H., Li, C.-M. and Yamagata, H., Dynamic γ - α Transformation during Hot Deformation in Iron–Nickel–Carbon Alloys. ISIJ International, Vol. 40, No. 2, Feb. 2000, p. 200-206.
47. Berry, B., Ritt, A. and Greissel, M., A Retrospective of Twentieth-Century Steel, in New Steel. 1999. p. 38-51.
212 48. Immarigeon, J.P.A. and Jonas, J.J., Deformation of Armco Fe and Si Steel in the Vicinity of the Curie Temperature. Acta Metallurgica, Vol. 22, No. 10, Oct. 1974, p. 1235-1247.
49. Bailon, J.P., Loyer, A. and Dorlot, J.M., Relationships Between Stress, Strain, Grain Size, And Dislocation Density In Armco Iron At Room Temperature. Materials Science and Engineering, Vol. 8, No. 5, Nov. 1971, p. 288-298.
50. Immarigeon, J.P.A. and Jonas, J.J., Flow Stress And Substructural Change During The Transient Deformation Of Armco Fe And Si Steel. Acta Metallurgica, Vol. 19, No. 10, Oct. 1971, p. 1053-1061.
51. Bailon, J.P. and Dorlot, J.M., Thermal-Treatment Effects On The Hall-Petch Relation For Armco-Iron. Acta Metallurgica, Vol. 19, No. 2, Feb. 1971, p. 71-84.
52. Valiev, R.Z., Ivanisenko, Y.U.V., Rauch, E.F. and Baudelet, B., Structure and deformation behaviour of Armco iron subjected to severe plastic deformation. Acta Materialia, Vol. 44, No. 12, Dec. 1996, p. 4705-4712.
53. Ivanisenko, Y., Valiev, R.Z. and Fecht, H.J., Grain boundary statistics in nano- structured iron produced by high pressure torsion. Materials Science and Engineering A, Vol. 390, No. 1-2, 15 January 2005, p. 159-165.
54. Walasek, T.A., Experimental verification of Monte Carlo recrystallization model. Journal of Materials Processing Technology, Vol. 157-158, 20 Dec. 2004, p. 262- 267.
55. Wetscher, F., Vorhauer, A., Stock, R. and Pippan, R., Structural refinement of low alloyed steels during severe plastic deformation. Materials Science and Engineering A, Vol. 387-389, 15 Dec. 2004, p. 809-816.
56. Nelson, T.W., Lippold, J.C. and Mills, M.J., Nature and evolution of the fusion boundary in ferritic-austenitic dissimilar weld metals. Part 2: On-cooling transformations. Welding Journal, Vol. 79, No. 10, Oct. 2000, p. 267s-277s.
57. Kallee, S. and Mistry, A. Friction Stir Welding in the Automotive Body in White Production. in Proceedings of 1st International Symposium on Friction Stir Welding. 1999. Thousand Oaks, CA, USA 14-16 June 1999: TWI.
58. Midling, O.T., Kvåle, J.S. and Dhal, O. Industrialisation of the Friction Stir Welding Technology in Panels Production in the Maritime Sector. in Proceedings of 1st International Symposium on Friction Stir Welding. 1999. Thousand Oaks, CA, USA 14-16 June 1999: TWI.
213 59. Thomas, W.M., Threadgill, P.L. and Nicholas, E.D., Feasibility of Friction Stir Welding Steel. Science and Technology of Welding and Joining, Vol. 4, No. 6, June 1999, p. 365-372.
60. Sorensen, C.D., Nelson, T.W. and Packer, S.M. Tool Material Testing for FSW of High-Temperature Alloys. in 3rd International Symposium on Friction Stir Welding. 2001. Kobe, Japan Sept. 2001.
61. Posada, M., DeLoach, J., Reynolds, A.P. and Halpin, J.P. Mechanical property and microstructural evaluation of friction stir welded AL-6XN. in 6th International Conference: Trends in Welding Research; Pine Mountain, GA; USA; 15-19 Apr. 2002. 2003 ASM International, Materials Park, OH, 44073- 0002, USA.
62. Juhas, M.C., Viswanathan, G.B. and Fraser, H.L. Microstructural Evolution in Ti Alloy Friction Stir Welds. in Proceedings of 2nd International Symposium on Friction Stir Welding. 2000. Gothenburg, Sweden TWI.
63. Lienert, T.J., Stellwag, W.L., Jr., Grimmett, B.B. and Warke, R.W., Friction Stir Welding Studies on Mild Steel. Welding Journal, Vol. 82, No. 1, Jan. 2003, p. 1s- 9s.
64. Lippold, J.C. and Ditzel, P.J., Microstructure and Properties of Aluminum Friction Stir Welds. Materials Science Forum, Vol. 426-432, No. Part 5, July 2003, p. 4597-4602.
65. Seidel, T.U. and Reynolds, A.P., Visualisation of the material flow in AA2195 friction-stir welds using a marker insert technique. Metallurgical and Materials Transactions A, Vol. 32A, No. 11, p. 2879-2884.
66. Fenn, R. and Thomas, W.M., The friction stir welding process. Light Metal Age, Vol. 59, p. 9-10.
67. Leonard, A.J. Microstructure and ageing behaviour of FSW's [friction stir welds] in aluminium alloys 2014A-T651 and 7075-T651. in Friction Stir Welding, Proceedings, 2nd International Symposium. 2000. Gothenburg, Sweden 26-28 June 2000: Abington Publishing.
68. Colligan, K., Material flow behaviour during friction stir welding of aluminium. Welding Journal, Vol. 78, No. 7, July 1999, p. 229s-237s.
69. Reynolds, A.P., Seidel, T.U. and Simonsen, M. Visualisation of material flow in an autogenous friction stir weld. in 1st International Symposium on Friction Stir Welding. 1999. Thousand Oaks, CA, USA June 1999: TWI.
214 70. London, B., Mahoney, M., Bingel, W., Calabrese, M. and Waldron, D. Experimental Methods for Determining Material Flow in Friction Stir Welds. in Third International Symposium on Friction Stir Welding. 2001. Kobe, Japan 27- 28 Sept. 2001.
71. Frigaard, O., Grong, O., Bjorneklett, B. and Midling, O.T. Modelling of the thermal and microstructure fields during friction stir welding of aluminium alloys. in Paper presented at 1st International Symposium on Friction Stir Welding, Thousand Oaks, CA, USA; 14-16 June 1999. 1999 Abington, Cambridge CB1 6AH, UK; Abington Publishing.
72. Russell, M.J. and Shercliff, H.R. Analytical modelling of microstructure development in friction stir welding. in Paper presented at 1st International Symposium on Friction Stir Welding, Thousand Oaks, CA, USA; 14-16 June 1999. 1999 Abington, Cambridge CB1 6AH, UK; Abington Publishing.
73. Yuh, B., Chao, Y.J. and Qi, X.H. Heat transfer and thermo-mechanical analysis of friction stir joining of AA6061-T6 [aluminium alloy] plates. in Paper presented at 1st International Symposium on Friction Stir Welding, Thousand Oaks, CA, USA; 14-16 June 1999. 1999 Abington, Cambridge CB1 6AH, UK; Abington Publishing.
74. Reynolds, A.P., Lindner, K., Tang, W. and Seidel, T.U. Weld efficiency and defect formation: correlation between experiment and simple models. in 6th International Conference: Trends in Welding Research; Pine Mountain, GA; USA; 15-19 Apr. 2002. 2003 ASM International, Member/Customer Service Center, Materials Park, OH, 44073-0002, USA.
75. Bendzsak, G.J., North, T.H. and Smith, C.B. An experimentally validated 3D model for friction stir welding. in Friction Stir Welding, Proceedings, 2nd International Symposium, Gothenburg, Sweden, Session 4, Paper 1; 26-28 June 2000. 2000 Abington, Cambridge CB1 6AL; TWI Ltd.
76. Colegrove, P., Painter, M., Graham, D. and Miller, T. 3-dimensional flow and thermal modelling of the friction stir welding process. in Friction Stir Welding, Proceedings, 2nd International Symposium, Gothenburg, Sweden, Session 4, Paper 2. 10 fig, 1 tab, 11 ref; 26-28 June 2000. 2000 Abington, Cambridge CB1 6AL; TWI Ltd; 2000, 11pp.
77. Dong, P., Lu, F., Hong, J.K. and Cao, Z. Analysis of weld formation process in friction stir welding. in Paper presented at 1st International Symposium on Friction Stir Welding, Thousand Oaks, CA, USA; 14-16 June 1999. 1999 Abington, Cambridge CB1 6AH, UK; Abington Publishing.
78. Hassan, K.A.A., Wynne, B.P. and Prangnell, P.B. The simulation of nugget zone grain structures in high strength Al-alloy friction stir welds by high strain torsion 215 testing. in Friction Stir Welding. Proceedings, 4th International Symposium. 2003. Park City, UT, USA 14-16 May 2003: Publ: Abington, Cambridge CB1 6AL, UK; TWI Ltd.
79. Colegrove, P.A. and Shercliff, H.R., Experimental and numerical analysis of aluminium alloy 7075-T7351 friction stir welds. Science and Technology of Welding and Joining, Vol. 8, No. 5, Oct. 2003, p. 360-368.
80. Lambrakos, S.G., Fonda, R.W., Milewski, J.O. and Mitchell, J.E., Analysis of friction stir welds using thermocouple measurements. Science and Technology of Welding and Joining. Vol. 8, no. 5, pp. 385-390. Oct. 2003.
81. Jata, K.V. and Semiatin, S.L., Continuous dynamic recrystallisation during friction stir welding of high strength aluminium alloys. Scripta Materialia, Vol. 43, No. 8, 29 Sept. 2000, p. 743-749.
82. Nippes, E.F. and Savage, W.F., Development of Specimen Simulating Weld Heat- Affected Zones. Welding Journal, Vol. 28, No. 11, p. 534s-545s.
83. Gleeble 3500/3800 Operations Manual. 2001: DSI.
84. Gleeble 3500/3800 Options Reference Manual. 2001: DSI.
85. Alexandrov, B.T. and Lippold, J.C., Single Sensor Differential Thermal Analysis - A Novel Technique for Studying Phase Transformations In Metals and Alloys, in 3rd Annual Euroweld Seminar. 2005: Columbus, Ohio.
86. Alexandrov, B.T. and Lippold, J.C., Relationship Between the Solidification Temperature Range and Weld Solidification Cracking Susceptibility of Stainless Steels and Ni-base Alloys, IIW Doc. IX-2163-05, in 58th Annual Assembly of IIW. 2005, IIW-ISS: Prague.
87. Alexandrov, B.T. and Lippold, J.C., A New Methodology for Studying Phase Transformations in High Strength Steel Weld Metal, in 7th International Trends in Welding Research Conference. 2005, ASM: Pine Mountain, Georgia.
88. Alexandrov, B.T. and Lippold, J.C., Methodology for In Situ Investigation of Phase Transformations in Welded Joints, IIW. Doc. IX-2114-04, in 57th Annual Assembly of IIW. 2004, IIW-ISS: Osaka, Japan.
89. Alexandrov, B.T. and Lippold, J.C., In-Situ Weld Metal Continuous Cooling Transformation Diagrams, IIW Doc. IX-2162-05, in 58th Annual Assembly of IIW. 2005, IIW-ISS: Prague.
90. Lippold, J.C. and Alexandrov, B.T. Phase Transformations during Welding and Post Weld Heat Treatment of Supermartensitic Stainless Steel, IIW Doc. 1556-05. 216 in 3rd Stainless Steel World America Conference. 2004. Houston, USA October 2004: IIW-ISS.
91. Myers, R.H. and Montgomery, D.C., Response Surface Methodology: Process and Product Optimization Using Designed Experiments. Wiley Series in Probability and Statistics. 1995, New York: John Wiley & Sons, Inc.
92. Box, G.E.P. and Wilson, K.B., On the Experimental Attainment of Optimum Conditions. Journal of the Royal Statistical Society, Series B, Vol. 13, No. 1, p. 1-45.
93. Allen, T.T. and Yu, L., Low-Cost Response Surface Methods From Simulation Optimization. Quality and Reliability Engineering International, Vol. 18, p. 5-17.
94. Dynamic Systems Inc. Product Guide, CD-ROM. 2005.
95. www.paxit.com.
96. Hirano, S., Okamoto, K., Aota, K. and Masahisa, I. Metallurgical and Mechanical Properties of Friction Stir Welded Ultra Fine Grained Steel. in 5th International Symposium on Friction Stir Welding. 2004. Metz, France September 14-16, 2004: TWI.
97. Oikawa, H., Lattice Self-Diffusion in Solid Iron: a Critical Review. Technological Reports of Tohoku University, Vol. 47, No. 1, 1982, p. 67-77.
98. Nix, W.D. and Ilschner, B. Mechanisms Controlling Creep of Single-Phase Metals and Alloys. in Strength of Metals and Alloys, Vol. 3. Fifth International Conference. 1980. Aachen; W. Germany 27-31 Aug. 1979.
217
APPENDIX A
SCHEMATICS OF PARTS AND SAMPLES
218 219
220 221
222
223 224
APPENDIX B
LIST OF EQUIPMENT AND SUPPLIES
Polishing Equipment
Manual
Leco Spectrum System™ 1000 Allied High Tech Products, Inc. Silicon Carbide paper (240, 320, 400, 600, 800, 1200 grits)
Buehler Metaserv 2000 Buehler Mastertex cloth Leco 9 μm and 3 μm diamond paste
Leco Spectrum System™ 1000 Mager Scientific Magercloth Allied High Tech Products, Inc. 1.0 micron standard alumina powder
Automated
Buehler Vibromet 2 with Buehler Mastermet 2 colloidal silica
Struers Lectropol-5 with Struer A2 solution
A2 compositon: 90 ml distilled water 730 ml ethanol 100 ml ethylene glycol monobutyl ether 78 ml perchloric acid
Polishing Procedure: Volts 37 V Flow Rate 14 Time 10 sec
225 Microscopy
Optical
Nikon Epiphot with attached Pax-cam 7000 Zoom Navitar TV Zoom lens attached to Hitachi HV-C20 3CCD camera PaxIt! Software (versions 4, 5, and 6 used as system was upgraded)
Electron
Philips XL-30 ESEM with EDAX TSL OIM™ System
Gleeble
Gleeble 3800 (serial# 3800-354) Omega Engineering, Inc. Teflon coated Chromel 0.010” dia. Omega Engineering, Inc. Teflon coated Alumel 0.010” dia.
Friction Stir Welder
EWI FSW#2 prior to January 2006 overhaul and retrofitting Temprel, Inc. 0.0625” Inconel 600 sheathed K-type thermocouple (T21-MG-12K-AS)
Data Acquisition System
Instrunet 100 Analog/Digital Input/Output System
226
APPENDIX C
EXPERIMENTAL DESIGNS
227 Std. Order Run Order Revolutions Speed (rpm) Temp. (°C) 15 1 20 1000 1200 5 2 12 703 1300 11 3 20 500 1200 16 4 20 1000 1200 9 5 6.5 1000 1200 1 6 12 703 1100 7 7 12 1297 1300 13 8 20 1000 1032 8 9 28 1297 1300 14 10 20 1000 1368 6 11 28 703 1300 20 12 20 1000 1200 3 13 12 1297 1100 12 14 20 1500 1200 18 15 20 1000 1200 2 16 28 703 1100 4 17 28 1297 1100 10 18 33.5 1000 1200 17 19 20 1000 1200 19 20 20 1000 1200 Initial Central Composite Design Experiment used in testing 14mm Iron Rod (center point runs highlighted in yellow)
Std. Order Run Order Revolutions Speed (rpm) Temp. (°C) 15 1 7 700 1200 5 2 4 400 1260 11 3 7 195.463 1200 16 4 7 700 1200 9 5 1.95463 700 1200 1 6 4 400 1140 7 7 4 1000 1260 13 8 7 700 1099 8 9 10 1000 1260 14 10 7 700 1301 6 11 10 400 1260 20 12 7 700 1200 3 13 4 1000 1140 12 14 7 1204.537 1200 2 15 10 400 1140 4 16 10 1000 1140 10 17 12.04537 700 1200 Central Composite Design Experiment used in testing modified torsion samples (center point runs highlighted in yellow)
228 Standard order Run Order Temp # Revs RPM delta t 8-5 1 5 875 1 325 35 2 14 950 3 100 35 3 9 850 3 1000 35 4 4 950 1 325 20 5 11 900 2 100 25 6 12 900 3 550 25 7 6 875 1 1000 20 8 8 850 2 550 25 9 2 950 3 1000 15 10 13 850 3 100 15 11 7 900 2 550 15 12 3 925 1.5 775 30 13 10 925 1.5 775 30 14 1 925 1.5 775 30
LCRSM designed experiment used in testing modified iron samples
Standard Order Run Temp Rev RPM Δt 8-5 1 12 835 1 325 35 2 3 910 7 100 35 3 10 810 7 1000 35 4 9 910 1 325 20 5 5 860 4 100 25 6 1 860 7 550 25 7 13 835 1 1000 20 8 11 810 4 550 25 9 8 910 7 1000 15 10 14 810 7 100 15 11 7 860 4 550 15 12 2 885 2.5 775 30 13 4 885 2.5 775 30 14 6 885 2.5 775 30
H-LCRSM 1 designed experiment (Samples which did not fail in torsion are highlighted yellow)
229 Standard Order Run Temp Rev RPM Δt 8-5 1 5 1150 1 325 35 2 12 1300 7 100 35 3 6 1100 7 1000 35 4 11 1300 1 325 20 5 2 1200 4 100 25 6 7 1200 4 550 25 7 4 1150 1 1000 20 8 13 1100 4 550 25 9 1 1300 7 1000 15 10 14 1100 7 100 15 11 8 1200 4 550 15 12 10 1250 5.5 775 30 13 3 1250 5.5 775 30 14 9 1250 5.5 775 30 15 final3.do1 1250 2.5 775 30 16 final3.do2 1250 2.5 775 30 17 final3.do3 1250 2.5 775 30
H-LCRSM 2 designed experiment
Standard Order Run Temp Rev RPM Δt 8-5 1 10 925 0.25 600 35 2 5 1300 1.25 300 35 3 1 800 1.25 1500 35 4 9 1300 0.25 600 20 5 4 1050 0.75 300 25 6 6 1050 0.75 900 25 7 12 925 0.25 1500 20 8 2 800 0.75 900 25 9 13 1300 1.25 1500 15 10 3 800 1.25 300 15 11 7 1050 0.75 900 15 12 11 1175 0.5 1200 30 13 14 1175 0.5 1200 30 14 8 1175 0.5 1200 30 15 6a 1050 1.25 900 25 16 validate 1225 0.9 675 15
H-LCRSM 3 designed experiment (highlighted runs not used to create models with ANOVA)
230
APPENDIX D
PSUEDO BINARY PHASE DIAGRAMS
231 THERMO-CALC (2006.01.19:14.22) : DATABASE:TCFE2 N=1., P=100000, W(MN)=3E-3, W(SI)=5E-4, W(S)=1.8E-4, W(P)=7E-5; 1000 1:*BCC_A2 2:*GRAPHITE 950 3:*FCC_A1
1 900
850
800 1
750 2 2 32 3 700 TEMPERATURE_CELSIUS
650
600 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2006-01-19 14:22:41.42 output by user rubal.7 from WE140 from rubal.7 user by output 14:22:41.42 2006-01-19 WEIGHT_PERCENT C
14mm Iron rod pseudo binary phase diagram
232 THERMO-CALC (2006.01.19:14.09) : DATABASE:TCFE2 N=1., P=100000,W(MN)=3E-3, W(P)=1.1E-4, W(S)=1.4E-4, W(SI)=1.3E-4, W(CU)=2.9E-4, W(NI)=2.8E-4, W(CR)=3.5E-4, W(MO)=5E-5, W(AL)=7.3E-4, W(V)=1E-5, W(NB)=2E-5, W 1000 1:*BCC_A2 4:*GRAPHITE 3:*FCC_A1#1 950 6:*FCC_A1#2
1 900 6 6 1 850 1 800 1
3 750 4 1 3 3 700 4 TEMPERATURE_CELSIUS
650
600 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2006-01-19 14:09:43.53 output by user rubal.7 from WE140 from rubal.7 user by output 14:09:43.53 2006-01-19 WEIGHT_PERCENT C
Ingot Iron bar pseudo binary phase diagram
233 THERMO-CALC (2006.01.19:13.56) : DATABASE:TCFE2 N=1., P=100000, W(MN)=1.33E-2, W(P)=1.7E-4, W(S)=7E-5, W(SI)=2.18E-2, W(CU)=4.6E-4, W(NI)=5.6E-4, W(CR)=5.8E-4, W(MO)=1E-4, W(AL)=3.5E-4, W(V)=4E-4, W(NB)=3.4E-4, 1200 7 6:*GRAPHITE 3:*FCC_A1#2 7 7:*FCC_A1#1 1:*BCC_A2 1100
1000 7 73 1 900 1 1
6 800 61 6
TEMPERATURE_CELSIUS 3 3 700
6 600 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2006-01-19 13:56:36.80 output by user rubal.7 from WE140 from rubal.7 user by output 13:56:36.80 2006-01-19 WEIGHT_PERCENT C
¼” HSLA-65 plate pseudo binary phase diagram
234 THERMO-CALC (2006.01.19:13.45) : DATABASE:TCFE2 P=100000, N=1., W(MN)=1.44E-2, W(P)=8E-5, W(S)=7E-5, W(SI)=2.86E-3, W(CU)=2.1E-4, W(NI)=9E-5, W(CR)=2.3E-4, W(MO)=1E-4, W(AL)=3.5E-4, W(V)=7.1E-4, W(NB)=3.4E-4, 1000 7:*GRAPHITE 6 3:*FCC_A1#1 6 8:*CEMENTITE 950 6:*FCC_A1#2 1:*BCC_A2 900 11
850 63 800 1 1
750 7
7 78 700 3 3 TEMPERATURE_CELSIUS 83 7 650
600 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2006-01-19 13:45:03.11 output by user rubal.7 from WE140 rubal.7 from output by user 13:45:03.11 2006-01-19 WEIGHT_PERCENT C
½” HSLA-65 plate pseudo binary phase diagram
235