• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
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  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
ZHU Qing, ZHENG Weipeng, WU Haoyu, DING Yulin, GUO Yongxin, WANG Qiang, LIU Li, ZHANG Junxiao. Analysis Method for Water-Rich and Fractured Risks in Tunnel Surrounding Rock Based on Fuzzy Bayesian Network[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230397
Citation: ZHU Qing, ZHENG Weipeng, WU Haoyu, DING Yulin, GUO Yongxin, WANG Qiang, LIU Li, ZHANG Junxiao. Analysis Method for Water-Rich and Fractured Risks in Tunnel Surrounding Rock Based on Fuzzy Bayesian Network[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230397

Analysis Method for Water-Rich and Fractured Risks in Tunnel Surrounding Rock Based on Fuzzy Bayesian Network

doi: 10.3969/j.issn.0258-2724.20230397
  • Received Date: 15 Aug 2023
  • Rev Recd Date: 06 Nov 2023
  • Available Online: 21 Apr 2025
  • Unfavorable water-rich and fractured geological zones easily bring about water inrush disasters during tunnel construction. To accurately analyze water-rich and fractured risks in tunnel surrounding rock and address the need for automated and quantitative risk analysis, a fuzzy Bayesian network model for risk assessment was constructed by using tunnel excavation data. Geological parameter uncertainty was quantified via membership functions, and Bayesian probabilistic inference was employed to integrate data from tunnel seismic prediction and transient electromagnetic methods, yielding the probability of water-rich and fractured risks. A three-dimensional voxel model was used to map the risk probability to spatial coordinates, visualizing the spatial distribution of risks. A typical deep-buried long tunnel was selected for analysis. The results demonstrate that the assessment model achieves classification accuracies of 80.91% for groundwater conditions and 82.81% for rock mass integrity. Not affected by incomplete data, the model can conduct quantitative analysis under both single-source and multi-source data conditions. The constructed three-dimensional voxel model provides an effective reference for risk prevention and control. Analysis results of multi-source data fusion show higher spatial consistency with field-exposed water-rich and fractured zones than those of single-source data.

     

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