China Geological Environment Monitoring Institute, China Geological Disaster Prevention Engineering Industry AssociationHost
2023 Vol. 34, No. 3
Article Contents

FU Junyi, CHEN Fada, SHEN Zhiping, YIN Linli, WANG Xiang. Risk analysis of the geological hazards during urban tunnel construction in mountainous karst areas[J]. The Chinese Journal of Geological Hazard and Control, 2023, 34(3): 100-108. doi: 10.16031/j.cnki.issn.1003-8035.202205013
Citation: FU Junyi, CHEN Fada, SHEN Zhiping, YIN Linli, WANG Xiang. Risk analysis of the geological hazards during urban tunnel construction in mountainous karst areas[J]. The Chinese Journal of Geological Hazard and Control, 2023, 34(3): 100-108. doi: 10.16031/j.cnki.issn.1003-8035.202205013

Risk analysis of the geological hazards during urban tunnel construction in mountainous karst areas

More Information
  • Construction of urban tunnel engineering in mountainous karst regions involves a plethora of uncertain geological risk factors. Due to cost and schedule constraints, hydrogeological and engineering geological risk sources cannot be identified in detail, leading to frequent disasters. Expert scoring, which is influenced by human subjectivity, is a common method for disaster evaluation in tunnel engineering, and some evaluation indicators are difficult to quantify. In order to address these issues, Guiyang rail transit line 2 Phase I project was selected as a case study to establish a risk disaster evaluation system for urban tunnel engineering in mountainous karst regions. The location and type of the disasters during construction were recorded for 26 running tunnels, and geological risk factors that were significantly correlated were selected as evaluation factors. The coupling relationship between the frequency of disaster occurrence and the geological risk factors was inverted, leading to the establishment of the risk disaster evaluation system of urban tunnel engineering in mountainous karst region. The evaluation results demonstrate that the degree of consistency between the frequency of disaster occurrence and the segmentation results of the evaluation system is more than 69%, indicating that the evaluation system is capable of predicting the frequency of disaster occurrence effectively.

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