Novel model for risk identification during karst excavation

This study proposes a novel fuzzy model for identifying high-risk factors during excavations in urban karst geological environments. The proposed model incorporates the interval analytic hierarchy process (I-AHP) into the technique for order preference by similarity to an ideal solution (TOPSIS). The developed model considers the complex geological conditions, monitoring data, management quality, and surrounding environment. I-AHP is employed to assign the weights of the criteria, while TOPSIS is applied to identify high-risk factors. An expert confidence index is introduced to increase the reliability of the evaluated results. A case study of karst excavation at Ma'anshan Park Station on Guangzhou Metro Line 9 is analysed to validate the proposed model. The results indicate that high-risk factors can be identified in different excavation stages. The evaluated results concerning variations in risk factors can provide a guide for adopting construction measures to mitigate risk and reduce accident occurrence.

Automated summary

This study introduces a novel fuzzy model to identify high-risk factors in urban karst geological environments, utilizing I-AHP and TOPSIS techniques. The model considers various factors, including geological conditions, monitoring data, and management quality, providing guidance for risk mitigation and accident reduction through construction measures. Case study results validate the model's effectiveness in identifying high-risk factors at different excavation stages.