Results 51 to 60 of about 1,540,028 (185)
Intelligent Monitoring and Warning for Road‐Network Tunnels Via Feature Matching
Applied Research, Volume 5, Issue 5, October 2026.To address the safety issues in mountain tunnel construction, an early warning model integrating association rules and text vectorization feature matching was developed. The validation on two tunnels demonstrated that this model can accurately predict accident types and actively identify risks, providing support for dynamic safety management and the ...
Yinghui Zhang, Xianghui Liu
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Deep Underground Science and Engineering, Volume 5, Issue 3, Page 829-842, September 2026.Based on experimental results and theoretical analysis, an established rock damage accumulation model that comprehensively considers the preapplied static load, impact peak value, impact frequency, and impact times. Abstract To study the rock damage mechanism under high static loading and superimposed medium strain rate cyclic impact loading, a series ...
Wei Wang +6 more
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Energy Science &Engineering, Volume 14, Issue 8, Page 3726-3740, August 2026.This study determines the impact critical stress early‐warning indicators for deep soft coal seams: 18 MPa (shallow holes), 20 MPa (deep holes), and 3 MPa/d daily stress change rate, via theoretical, experimental and simulation methods. ABSTRACT The accurate determination of early‐warning indicators for critical impact stress in deep soft coal seams is
Haichen Yin +8 more
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Study on the Mechanism of Rockburst Induced by Tidal Force
Taiyuan Ligong Daxue xuebao, 2021 According to the statistical analysis of the time and region of rockburst, it is found that the time and region of rockburst have a certain correlation with the change of tidal force.
Gaochuan GUO, Yongkang YANG
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Energy Science &Engineering, Volume 14, Issue 8, Page 3935-3947, August 2026.Mining disturbance tends to trigger fault stick‐slip instability and induce disasters. This paper establishes a mechanical model to propose a critical criterion, which is verified to be reliable via FLAC3D, providing a theoretical basis for early warning of fault slip disasters.
Bowen Wu, Yanhui Li
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Prediction of rockburst classification using Random Forest
Transactions of Nonferrous Metals Society of China, 2013 Abstract The method of Random Forest (RF) was used to classify whether rockburst will happen and the intensity of rockburst in the underground rock projects. Some main control factors of rockburst, such as the values of in-situ stresses, uniaxial compressive strength and tensile strength of rock, and the elastic energy index of rock, were selected in
Long-jun DONG, Xi-bing LI, Kang PENG
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Seismic Insights Into the Role of Rockfall in Rockslide Destruction Processes
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.Abstract The dynamic link between rockslide failure and rockfall activity remains elusive, primarily due to the challenge of detecting weak signals amidst high noise. We propose a seismic attribute guided deep learning framework that formulates rockfall detection as a time‐series segmentation task, facilitating the precise extraction of rockfall events
Yaojun Wang +4 more
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Mechanism and Predicting Theory-Based of Rockburst Evolution [PDF]
, 2017 Mechanism and predicting of rockburst is complicated, and there is no mechanism and prediction model to explain the occurrence of rockburst satisfactorily. In this chapter, the mechanism of rockburst stress-energy evolution is obtained by analyzing the pre-peak stage of rock compressive deformation.
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Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN
Deep Underground Science and Engineering, Volume 5, Issue 2, Page 446-464, June 2026.A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan +4 more
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A scientometric review of structure rockburst research: current trends and future directions
Frontiers in Earth Science, 2023 Based on practical construction experience, it is observed that a significant number of rockburst-prone regions exhibit structural surfaces of varying scales that exert a controlling influence on rockburst. Therefore, it is crucial to review the progress
Yuanhang Zhang, Yuanyou Xia, Jian Huang
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