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Open Thesis-Rev3.Pdf The Pennsylvania State University The Graduate School Department of Energy and Mineral Engineering STUDY OF UTILIZATION FACTOR AND ADVANCE RATE OF HARD ROCK TBMS A Dissertation in Energy and Mineral Engineering by Ebrahim Farrokh 2012 Ebrahim Farrokh Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy May 2013 The dissertation of Ebrahim Farrokh was reviewed and approved* by the following: Jamal Rostami Assistant Professor of Energy and Mineral Engineering Mark S. Klima Department Head, Associate Professor of Mineral Processing and Geo-Environmental Engineering R. Larry Grayson Professor of Energy and Mineral Engineering Antonio Nieto Associate Professor of Energy and Mineral Engineering Prasenjit Basu Assistant Professor of Civil and Environmental Engineering *Signatures are on file in the Graduate School iii ABSTRACT Estimating the penetration rate (PR), utilization (U), and advance rate (AR) is a critical factor in successful selection and application of tunnel boring machines (TBM), but it has remained a challenge to most engineers and contractors. While there have been many studies on accurate prediction of penetration rate with some progress in accounting for various geological parameters, the amount of research performed on TBM utilization and advance rate is still very limited. The primary objective of this research was to develop a comprehensive database of TBM utilization and advance rate from different hard-rock tunneling projects using a TBM to develop a new model for estimation of machine utilization and advance rate through statistical analysis of available machine field performance information and a new rock mass characterization system. For this purpose, information for 300 tunnel projects, including rock properties, TBM specification, TBM operational parameters, and achieved performance were compiled in a database to seek significant correlations between these parameters. As the results of statistical analyses show, Unconfined Compressive Strength (UCS), Cerchar Abrasion Index (CAI), and Rock Quality Designation (RQD) are the most influential parameters in estimation of PR. For utilization factor, PR, UCS, groundwater condition, and tunnel diameter are the most influential parameters. The results of the analyses also indicate that tunnel diameter and UCS are among the primary parameters for prediction of advance rate. Good correlations between the actual and predicted values with R-sq of more than 60% have been obtained in different statistical analyses. In this thesis, two methods for prediction of AR are offered. One comes from multiplication of the predicted PR and U (indirect methodology) and the other method comes from direct estimation of AR from input parameters. Even though these two ARs are not exactly the same (since the methodologies and the input parameters are different), the results are iv reasonably close to each other. Although the indirect methodology has more flexibility in changing the related conditions for different down time components, it might produce more errors due to the combination of many parameters. On the other hand, the direct methodology benefits from more tunnel records compared to the indirect methodology and has more reliability. Hence, the direct method is proposed as the primary method for AR prediction and the indirect method is proposed as the supporting methodology to be used for more in-depth estimation using the analysis of different down time components. The results of analyses for the learning phase period show that, on average, it takes one week per each meter of tunnel diameter. This should be reflected as an adjustment on the results of the analyses for the first sections of the tunnel after completing the AR prediction for the entire length of a tunnel. In order to account for parallel activities and the probability of the parameters values, four different models were developed and calibrated for the real data. The results of simulation modeling show a very good agreement with the actual values of TBM advance rate values. The outcome of this study is establishing a framework to assist in the prediction of the main components of TBM performance parameters. This will provide an extremely useful tool for developing reliable estimates of the machine advance rate used in estimating project time and costs for a specific site, ground condition, and machine type when all input variables are properly assigned. v TABLE OF CONTENTS List of Figures...........................................................................................................................ix List of Tables............................................................................................................................xvi Acknowledgements...................................................................................................................xx Chapter 1 Introduction ............................................................................................................. 1 Introduction and Problem Statement ................................................................................ 1 Scientific Objectives and Intellectual Merit ..................................................................... 4 Background of Studies on TBM Performance Prediction ................................................ 5 Scope of Work and Methodology in Performing the Research........................................ 6 Structure of the Thesis ..................................................................................................... 10 Chapter 2 Literature Review on Hard Rock TBMs ................................................................. 12 Introduction ...................................................................................................................... 12 Tunnel Boring Machine (TBM) ....................................................................................... 14 Open TBM System Description ............................................................................... 17 Single Shield TBM ................................................................................................... 18 Double Shield TBM ................................................................................................. 20 TBM Performance Parameters ......................................................................................... 22 Penetration Rate ....................................................................................................... 23 Utilization Factor and Advance Rate ....................................................................... 23 Chapter 3 TBM Performance Databases .................................................................................. 25 Introduction ...................................................................................................................... 25 General TBM Field Performance Database ..................................................................... 26 Detailed Database ............................................................................................................ 29 Data Screening ................................................................................................................. 34 Review of TBM Performance Parameters in the Database .............................................. 37 TBM Operational Parameters ................................................................................... 37 Tunnel Location and Application ............................................................................. 39 Tunnel Diameter ....................................................................................................... 40 Length of the Tunnel ................................................................................................ 43 Unconfined Compressive Strength ........................................................................... 44 Core Fracture Frequency (CFF) ............................................................................... 46 Groundwater Condition ............................................................................................ 46 Rock Type ................................................................................................................ 47 Major Mining Problems ........................................................................................... 48 Geological Variability .............................................................................................. 49 Quartz Content ......................................................................................................... 50 Cutter Diameter ........................................................................................................ 51 Ground Support ........................................................................................................ 51 Tunnel Transport and Muck Haulage System .......................................................... 53 Tunnel Access .......................................................................................................... 54 Year of Completion .................................................................................................. 55 vi TBM Condition ........................................................................................................ 56 TBM Type ................................................................................................................ 57 Tunnel Slope ...........................................................................................................
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