Results 151 to 160 of about 2,608,139 (189)

Comprehensive Prediction of Rockburst in High-Speed Railway Tunnel

Applied Mechanics and Materials, 2013
Dayanwan tunnel in Shanghai-Kunming high-speed railway is deeply buried and its rock lithology is brittle and hard. The typical tunnel cross section was selected to do hydraulic fracturing field geostress test. The stress in the measured depth was obtained. In order to forecast the rock burst in the whole tunnel, the finite element inversion method has
Bo Li, Li Wu, Chang Mao Xu, Zhi Gang Li, Qing Jun Zuo   +4 more
openaire   +1 more source

Short-term rockburst risk prediction using ensemble learning methods

Natural Hazards, 2020
Short-term rockburst risk prediction plays a crucial role in ensuring the safety of workers. However, it is a challenging task in deep rock engineering as it depends on many factors. More recently, machine learning approaches have started to be used to predict rockbursts.
Weizhang Liang, Asli Sari, Guoyan Zhao, Stephen D. McKinnon, Hao Wu   +4 more
openaire   +1 more source

Predicting rockburst tendency based on fuzzy matter–element model

International Journal of Rock Mechanics and Mining Sciences, 2015
Rockburst is a dynamic phenomenon caused by multiple factors associated with mining excavations and activities. It is very hard to make predictions accurately. In this study, a multi-index model, based on fuzzy matter–element theory, information entropy theory and closeness degree rules, are established to predict rockburst tendency.
Chunlai Wang, Aixiang Wu, Hui Lu, Tiancai Bao, Xiaohui Liu   +4 more
openaire   +1 more source

Studies for rockburst prediction in the Carrara Marble (Italy)

2010
The exploitation of Carrara Marble dates back to Roman times. Throughout these twenty centuries, quarrying activity was mostly developed in the Carrara district in open pit quarries. In the last decades many quarries have been moved into underground. In some areas the mining stopes are subjected to rock burst. In order to overcome this hazard, detailed
COLI, MASSIMO, E. Livi, P. Berry, A. Bandini, J. Xuena   +4 more
openaire   +4 more sources

Short-term rockburst prediction in underground project: insights from an explainable and interpretable ensemble learning model

Acta Geotechnica, 2023
Y. Qiu, Jian Zhou
semanticscholar   +1 more source

Rockburst Intensity Prediction based on Kernel Extreme Learning Machine (KELM)

Acta Geologica Sinica - English Edition
As one of the most serious geological disasters in deep underground engineering, rockburst has caused a large number of casualties. However, because of the complex relationship between the inducing factors and rockburst intensity, the problem of ...
Yidong Xiao, Shengwen Qi, Song-feng Guo, Shishu Zhang, Zan Wang, Fengqiang Gong   +5 more
semanticscholar   +1 more source

Prediction method for rockburst risk using unsupervised clustering in small sample scenarios

Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
As underground engineering operations delve deeper, rockbursts are becoming more frequent and severe, raising safety and operational concerns. Predicting rockburst risks in deep environments is critical but challenging due to limited sample data.
Haohan Xiao, Ruilang Cao, Zhi Zheng, Qiang Zhang, Hongtao Yu   +4 more
semanticscholar   +1 more source

Prediction of rockbursts by analysis of induced seismicity data

International Journal of Rock Mechanics and Mining Sciences, 2001
Abstract This paper describes a technique for predicting the occurrence of strong rockbursts in mines. Both the kinetic theory of solid strength and the “rigid inclusion” model form the basis of this technique. The proposed precursor characteristics of the strong rockburst preparation process, when applied in retrospect to the North Ural Bauxite ...
openaire   +1 more source

Performance Evaluation of Rockburst Prediction Based on PSO-SVM, HHO-SVM, and MFO-SVM Hybrid Models

Mining Metallurgy & Exploration, 2023
Jian Zhou, Peixi Yang, Pingan Peng, M. Khandelwal, Y. Qiu   +4 more
semanticscholar   +1 more source

Application of KM-SMOTE for rockburst intelligent prediction

Tunnelling and Underground Space Technology, 2023
Qiushi Liu, Yiguo Xue, Guangkun Li, Daohong Qiu, Weimeng Zhang, Zhuangzhuang Guo, Zhiqiang Li   +6 more
openaire   +1 more source