Rockburst

Rockburst: Mechanisms, Monitoring, Warning and Mitigation invites the most relevant researchers and practitioners worldwide to discuss the rock mechanics phenomenon related to increased stress and energy levels in intact rock introduced by drilling, explosion, blasting and other activities. When cri [...]
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Rockburst: Mechanisms, Monitoring, Warning and Mitigation invites the most relevant researchers and practitioners worldwide to discuss the rock mechanics phenomenon related to increased stress and energy levels in intact rock introduced by drilling, explosion, blasting and other activities. When critical energy levels are reached, rockbursts can occur causing human and material losses in mining and tunneling environments. This book is the most comprehensive information source in English to cover rockbursts. Comprised of four main parts, the book covers in detail the theoretical concepts related to rockbursts, and introduces the current computational modeling techniques and laboratory tests available. The second part is devoted to case studies in mining (coal and metal) and tunneling environments worldwide. The third part covers the most recent advances in measurement and monitoring. Special focus is given to the interpretation of signals and reliability of systems. The following part addresses warning and risk mitigation through the proposition of a single risk assessment index and a comprehensive warning index to portray the stress status of the rock and a successful case study. The final part of the book discusses mitigation including best practices for distressing and efficiently supporting rock. Designed to provide the most comprehensive coverage, the book will provide practicing mining and tunneling engineers the theoretical background needed to better cope with the phenomenon, practical advice from case studies and practical mitigation actions and techniques. Academics in rock mechanics will appreciate this complete reference to rockburst, which features how to analyze stress signals and use computational modeling more efficiently.