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Full Description
This book presents the latest advancements in predicting Tunnel Boring Machine (TBM) performance in hard rock, a critical aspect of mechanized tunneling. Featuring contributions from renowned international experts, the book systematically covers key topics across ten chapters. Four pivotal chapters (2 to 5) are authored by the original developers of the world's leading performance prediction models—CSM, NTNU, QTBM, and UT—providing unique insights into their latest versions, formulations, and applications. The remaining chapters address crucial related areas, including TBM performance in seismic zones, cutterhead modeling, disc cutter wear, feature optimization, and the application of artificial intelligence (XAI/ML) for enhanced, interpretable predictions. Serving as both a reference and a practical guide, this book is essential for researchers, engineers, and professionals involved in TBM project planning, design, and execution.
Contents
Introduction.- Cutterhead Modeling of Hard Rock TBM.- The NTNU prediction model for hard rock tunnel boring: Performance predictions and cutter life assessments.- AR, Time, Tunnel Length and Geology Using QTBM.- University of Tehran Model, A Geological-based Model for Rock Mass Boreabil-ity Classification and TBM Performance Prediction.- The Performance of Three Hard Rock TBMs in Earthquake Zones and the Behavior of the Bored Tunnels Thereafter Feature Optimization: Identifying Critical Parameters for TBM Performance As-sessment.- Other TBM Performance Prediction Methods.- Application of Machine Learning (ML)-Based Algorithms in Hard Rock TBM Performance Analysis Using Explainable Artificial Intelligence (XAI).- Disc Cutter Wear.
