Results 71 to 80 of about 2,851 (220)

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Experimental investigation of the precursor characteristics and early warning of coal burst based on quantitative analysis of acoustic emission signals

Geomechanics and Geophysics for Geo-Energy and Geo-Resources
Coal burst is one of the most frequent and destructive dynamic disasters encountered during underground mining engineering. However, the understanding of quantitative precursor characteristics of coal burst is still in its infancy, rendering it difficult
Xiaoling Zhao, Zhiyi Liao, Xiufeng Zhang, Cong Shen, Jianbo Zhu   +4 more
doaj   +1 more source

Dynamic cracking properties and generating conditions of coal under rapid gas release

Deep Underground Science and Engineering, EarlyView.
Gas release tests revealed that crack initiation and propagation are jointly controlled by initial crack length, residual strength, and gas release velocity. A new outburst risk coefficient was thus developed from a fracture mechanics perspective, offering a novel predictive approach.
Bing Zhang, Hanpeng Wang, Liang Yuan, Guofeng Yu, Wei Wang, Benliang Chen, Bo Ren   +6 more
wiley   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Study on Monitoring Rock Burst through Drill Pipe Torque

Shock and Vibration, 2015
This paper presents a new method to identify the danger of rock burst from the response of drill pipe torque during drilling process to overcome many defects of the conventional volume of drilled coal rubble method.
Zhonghua Li, Liyuan Zhu, Wanlei Yin, Yanfang Song   +3 more
doaj   +1 more source

FDNet: Knowledge and Data Fusion-Driven Deep Neural Network for Coal Burst Prediction. [PDF]

Sensors (Basel), 2022
Cao A, Liu Y, Yang X, Li S, Liu Y.
europepmc   +1 more source

Multi‐factor coupling effects in hydraulic fracturing of laminated shale: Experimental insights and physics‐informed neural network‐driven optimization

Deep Underground Science and Engineering, EarlyView.
This study establishes a multi‐factor coupling framework for predicting breakdown pressure in laminated shale by integrating experimental hydraulic fracturing tests, physics‐informed neural networks (PINNs), and Sobol sensitivity analysis. It reveals how differential stress, the bedding dip angle, and the injection rate interact to influence fracture ...
Tao Wang, Guoyao Xu, Liyuan Liu, Yao Zhang, Sitao Zhu, Hongyang Chu, Kaikai Zhao   +6 more
wiley   +1 more source

Mechanism of “seesaw‐type” rock burst in coal seam mining beneath mountainous areas

Deep Underground Science and Engineering, EarlyView.
This study reveals the mechanism of “seesaw‐type” rock bursts during coal mining beneath mountainous areas. The advancing working face induces nonuniform fracturing of the overburden. The detached mountain mass then undergoes a seesaw‐type rotational movement around a shifting pivot, driving the primary fracture through a characteristic “open‐close ...
Chao Zhou, Xueqiu He, Zhenlei Li, Ping Wang, Dazhao Song, Fuxing Jiang, Shan Yin, Anliang Lü, Menghan Wei, Taoping Zhong   +9 more
wiley   +1 more source

Occurrence law and classification prevention of rock burst in coal mines of Shaanxi Province

Meitan kexue jishu
With coal resource extraction areas are constantly shifting towards the west and deeper regions, and the number of rock burst mines in the western region is increasing rapidly.
Junfeng PAN, Shaohong LIU, Wentao MA, Yongxue XIA, Shuwen WANG, Meihua FENG   +5 more
doaj   +1 more source

Research on Optimal Width of Coal Pillars in Both Sides of Abandoned Mining Areas and Tunnel Control Technology

Energy Science &Engineering, EarlyView.
This study primarily investigates the optimal width for coal pillar retention in both sides of the worked‐out face section. Taking the 42201 haulage roadway of the 42201 working face at Shengxin Coal Mine as the primary research target, it analyses the optimum width for coal pillar retention through theoretical calculations, numerical simulations, and ...
Shuaifeng Yin, Kanglei Han, En Wang, Yitao Yan, Xubo Zhao   +4 more
wiley   +1 more source