Evolution, Monitoring and Predicting Models of Rockburst: Precursor Information for Rock Failure - Softcover

Wang, Chunlai

Softcover

ISBN 10: 9811356513 ISBN 13: 9789811356513

Publisher: Springer, 2019

Synopsis

This open access book focuses on investigating predicting precursor information and key points of rockburst in mining engineering through laboratory experiment, theoretical analysis, numerical simulation and case studies. Understanding the evolution patterns for the microstructure instability of rock is a prerequisite for rockburst prediction. The book provides a guide for readers seeking to understand the evolution patterns for the microstrucure of rock failure, the predicting key point of rock failure and the rockburst predicting model. It will be an essential reference to understand mechanism of rockburst and sheds new light on dynamic disasters prediction. Chapters are carefully developed to cover (1) The evolution patterns for the microstructure instability of rock; (2) Rockburst hazard monitoring and predicting criterion and predicting models. The book addresses the issue with a holistic and systematic approach that investigates the occurrence mechanism of rockburst based on the evolution patterns for the microstructure of rock failure and establishes the predicting model of rockburst.

This book will be of interest to researchers of mining engineering, rock mechanics engineering and safety engineering.

About this title

About the Author

Dr. Chunlai Wang graduated from Heibei Polytechnic University in 2001 and he obtained his PhD of Mining Engineering from University of Science and Technology Beijing in 2011. He works as associate professor in the Faculty of Resources and Safety Engineering, China University of Mining & Technology Beijing, China, and he is now the associate director of the department of Department of Resources Engineering. In 2015-2016, he commenced his research in the University of British Columbia, as a visiting scholar. In 2012, he was awarded the National Youth Science and Technology Award from China Coal Society. He took charge of more than 10 national scientific projects including the National Natural Science Foundation of China (NSFC). His research interests focus mainly on predicting of mine dynamic hazards, predicting model and criterion, and reinforced technology for 16 years. Up to now, he has published over 50 academic papers and holds 8 patents in China, in which more than 15 English papers were published in International Journal of Rock Mechanics and Mining Sciences, etc. He has also authored a number of books and book chapters including Microseismic Monitoring Predicting and Reinforced Technology of Dynamic Hazards in Deep Mining (Beijing: Metallurgical Industry Press, 2013). He has won 6 National or Provincial Science and Technology Progress Awards.

From the Back Cover

This open access book focuses on investigating predicting precursor information and key points of rockburst in mining engineering through laboratory experiment, theoretical analysis, numerical simulation and case studies. Understanding the evolution patterns for the microstructure instability of rock is a prerequisite for rockburst prediction. The book provides a guide for readers seeking to understand the evolution patterns for the microstrucure of rock failure, the predicting key point of rock failure and the rockburst predicting model. It will be an essential reference to understand mechanism of rockburst and sheds new light on dynamic disasters prediction. Chapters are carefully developed to cover (1) The evolution patterns for the microstructure instability of rock; (2) Rockburst hazard monitoring and predicting criterion and predicting models. The book addresses the issue with a holistic and systematic approach that investigates the occurrence mechanism of rockburst based on the evolution patterns for the microstructure of rock failure and establishes the predicting model of rockburst.

This book will be of interest to researchers of mining engineering, rock mechanics engineering and safety engineering.

Edition details

• Publisher: Springer
• Publication date: 2019
• Language: English
• ISBN 10: 9811356513
• ISBN 13: 9789811356513
• Binding: Paperback
• Number of pages: 207