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
  • Emerging optical techniques for sorting and detection of chiral particles
  • Yuzhi Shi, Chengfeng Li, Xiaolei Lin, Wenwen Xue, Chengxing Lai, Tao He, Qinghua Song, Zhanshan Wang, Yulan Wang, Din Ping Tsai, Xinbin Cheng, Haidong Zou
  • Opto-Electronic Advances
  • 2026-06-08
  • Phonon-assisted absorption photoconductive switch
  • Zhao Wang, Lixin Zhang, Lu Cheng, Danwen Zhang, Yu Lu, Naiji Zhang, Xin Zhang, Duanyang Chen, Zhan Sui, Hongji Qi, Wei Zheng
  • Opto-Electronic Science
  • 2026-05-25
  • Photonic spiking reinforcement learning for intelligent routing
  • Shuiying Xiang, Yonghang Chen, Ling Zheng, Zhicong Tu, Xintao Zeng, Mengting Yu, Shuai Wang, Yahui Zhang, Xingxing Guo, Weitao Pan, Yue Hao
  • Opto-Electronic Science
  • 2026-05-25
  • Multistable soliton dynamics in an optical microresonator
  • Zichun Liao, Yuchong Cai, Lun Li, Weiqiang Wang, Shuai Li, Chi Zhang, Wenfu Zhang, Xinliang Zhang
  • Opto-Electronic Advances
  • 2026-05-15
  • AI-powered nonlinear optical imaging reveals protein spatial homogenization as an indicator of impaired bone quality in type 2 diabetes
  • Bowen Zhang, Jiangbo Pu, Tao Hu, Junjie Zeng, Han Zhang, Zemeng Chen, Xiang Ji, Shuhua Yue, Lin Z. Li, Ting Li
  • Opto-Electronic Advances
  • 2026-05-15
  • Highly sensitive SWCNT-based pyroelectric phototransistors for broadband room temperature infrared detection
  • Svetlana I. Serebrennikova, Daria S. Kopylova, Yuriy G. Gladush, Sakellaris Mailis, Nikita E. Gordeev, Aliya R. Vildanova, Aleksandr V. Averchenko, Sergey S. Zhukov, Dmitry V. Krasnikov, Albert G. Nasibulin
  • Opto-Electronic Advances
  • 2026-05-15
  • Active retinal projection augmented reality display via pixel-to-pixel collimation
  • Xiang Zhang, Yuanlong Huang, Weiyao Fan, Enguo Chen, Jiajun Luo
  • Opto-Electronic Advances
  • 2026-05-15
  • Massively parallel and programmable photonic differential equation solver
  • Jiahao Wang, Wen Chen, Zhou Zhou, Dongyu Hu, Zile Li, Peng Chen, Yan-qing Lu, Shuang Zhang, Cheng-Wei Qiu, Shaohua Yu, Guoxing Zheng
  • Opto-Electronic Advances
  • 2026-05-15
  • Femtosecond laser rapid customization of high-performance anti-reflection windows
  • Yulong Ding, Xiang Jiang, Cong Wang, Xianshi Jia, Linpeng Liu, Weina Han, Zheng Gao, Shiyu Wang, Nai Lin, Dejin Yan, Ji'an Duan
  • Opto-Electronic Science
  • 2026-04-23
  • Ppt-level volatile organic compounds detection via microsecond-pulse-enhanced mid-infrared photoacoustic
  • Senyu Wang, Liang Zhao, Hongyu Luo, Xiangyu Zhao, Jianfeng Li, Wei Wang, Hao Lei, Mingrui Jiang, Jinlong Wan, Binxing Zhao, Bincheng Li, Yong Liu
  • Opto-Electronic Science
  • 2026-04-23
  • Polarization-guided diffusion prior for eyeglass reflection removal
  • Yating Chen, Liangcai Cao
  • Opto-Electronic Advances
  • 2026-04-17



  • 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