Abstract:

To accurately identify deep foundation pit collapse risk levels and improve construction safety, a risk assessment model was developed using variable fuzzy set theory. Sixteen influencing factors were screened from four categories: hydrogeology, support conditions, construction operations, and management monitoring. A risk index system was constructed based on these factors with clearly defined grade standards for risk classification. The multiplicative synthesis method was applied to optimally combine subjective weights derived from Stepwise Weight Assessment Ratio Analysis (SWARA) and objective weights calculated via the entropy weight method, forming comprehensive weights that integrate expert judgment and data objectivity. Variable fuzzy set theory was then utilized to process sample data, generating comprehensive grade characteristic values to determine collapse risk levels. Engineering case results show that the evaluation outcomes of method align with actual construction conditions, confirming its scientific validity and effectiveness. Compared to existing approaches, it more accurately reflects risk status by addressing the fuzzy nature of risk boundaries in deep foundation pit projects. This study provides a scientific and practical framework for risk assessment, enhancing safety management in deep foundation pit construction and offering practical value for ensuring project safety and informed risk management decisions.

Key words: subway, deep foundation pit, collapse, variable fuzzy set, risk assessment