Year
Month
(Peer-Reviewed) Risk assessment of fault water inrush during deep mining
Zhaodan Cao ¹ ², Qixiong Gu 古启雄 ³, Zhen Huang 黄震 ³, Jiaju Fu ⁴
¹ College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
中国 杭州 浙江大学建筑工程学院
² ZJU-UIUC Institute, Zhejiang University, Haining 314400, China
中国 海宁 浙江大学伊利诺伊大学厄巴纳香槟校区联合学院
³ School of Resources and Environment Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
中国 赣州 江西理工大学资源与环境工程学院
⁴ Guiyang Architectural Design and Surveying Prospecting CO. LTD, Guiyang 550082, China
中国 贵阳 贵阳建筑勘察设计有限公司
Abstract

With the gradual depletion of shallow coal resources, the Yanzhou mine in China will enter the lower coal seam mining phase. However, as mining depth increases, lower coal seam mining in Yanzhou is threatened by water inrush in the Benxi Formation limestone and Ordovician limestone.

The existing prediction models for the water burst at the bottom of the coal seam are less accurate than expected owing to various controlling factors and their intrinsic links. By analyzing the hydrogeological exploration data of the Baodian lower seam and combining the results of the water inrush coefficient method and the Yanzhou mine pressure seepage test, an evaluation model of the seepage barrier capacity of the fault was established.

The evaluation results show the water of the underlying limestone aquifer in the Baodian mine area mainly threatens the lower coal mining through the fault fracture zone. The security of mining above confined aquifer in the Baodian mine area gradually decreases from southwest to northeast.

By comparing the water inrush coefficient method and the evaluation model of fault impermeability, the results show the evaluation model based on seepage barrier conditions is closer to the actual situation when analyzing the water breakout situation at the working face.
Risk assessment of fault water inrush during deep mining_1
Risk assessment of fault water inrush during deep mining_2
Risk assessment of fault water inrush during deep mining_3
Risk assessment of fault water inrush during deep mining_4
  • Advanced biological imaging techniques based on metasurfaces
  • Yongjae Jo, Hyemi Park, Hyeyoung Yoon, Inki Kim
  • Opto-Electronic Advances
  • 2024-10-31
  • Orthogonal matrix of polarization combinations: concept and application to multichannel holographic recording
  • Shujun Zheng, Jiaren Tan, Hongjie Liu, Xiao Lin, Yusuke Saita, Takanori Nomura, Xiaodi Tan
  • Opto-Electronic Advances
  • 2024-10-23
  • Streamlined photonic reservoir computer with augmented memory capabilities
  • Changdi Zhou, Yu Huang, Yigong Yang, Deyu Cai, Pei Zhou, Kuenyao Lau, Nianqiang Li, Xiaofeng Li
  • Opto-Electronic Advances
  • 2024-10-22
  • High-precision multi-focus laser sculpting of microstructured glass
  • Kang Xu, Peilin Huang, Lingyu Huang, Li Yao, Zongyao Li, Jiantao Chen, Li Zhang, Shaolin Xu
  • Opto-Electronic Advances
  • 2024-10-09
  • Multi-physical field null medium: new solutions for the simultaneous control of EM waves and heat flow
  • Sailing He, Ruili Zhang, Junbo Liang
  • Opto-Electronic Advances
  • 2024-09-30
  • Adaptive decentralized AI scheme for signal recognition of distributed sensor systems
  • Shixiong Zhang, Hao Li, Cunzheng Fan, Zhichao Zeng, Chao Xiong, Jie Wu, Zhijun Yan, Deming Liu, Qizhen Sun
  • Opto-Electronic Advances
  • 2024-09-29
  • Data-driven polarimetric approaches fuel computational imaging expansion
  • Sylvain Gigan
  • Opto-Electronic Advances
  • 2024-09-28
  • An externally perceivable smart leaky-wave antenna based on spoof surface plasmon polaritons
  • Weihan Li, Jia Chen, Shizhao Gao, Lingyun Niu, Jiaxuan Wei, Ruosong Sun, Yaqi Wei, Wenxuan Tang, Tie Jun Cui
  • Opto-Electronic Advances
  • 2024-09-25
  • The possibilities of using a mixture of PDMS and phosphor in a wide range of industry applications
  • Rodrigo Rendeiro, Jan Jargus, Jan Nedoma, Radek Martinek, Carlos Marques
  • Opto-Electronic Advances
  • 2024-09-20
  • Agile cavity ringdown spectroscopy enabled by moderate optical feedback to a quantum cascade laser
  • Qinxue Nie, Yibo Peng, Qiheng Chen, Ningwu Liu, Zhen Wang, Cheng Wang, Wei Ren
  • Opto-Electronic Advances
  • 2024-09-20
  • Genetic algorithm assisted meta-atom design for high-performance metasurface optics
  • Zhenjie Yu, Moxin Li, Zhenyu Xing, Hao Gao, Zeyang Liu, Shiliang Pu, Hui Mao, Hong Cai, Qiang Ma, Wenqi Ren, Jiang Zhu, Cheng Zhang
  • Opto-Electronic Science
  • 2024-09-20
  • Finely regulated luminescent Ag-In-Ga-S quantum dots with green-red dual emission toward white light-emitting diodes
  • Zhi Wu, Leimeng Xu, Jindi Wang, Jizhong Song
  • Opto-Electronic Advances
  • 2024-09-18



  • Artificial intelligence CT helps evaluate the severity of COVID-19 patients: A retrospective study                                Genetic-algorithm-based artificial intelligence control of a turbulent boundary layer
    About
    |
    Contact
    |
    Copyright © PubCard