Safety Resilience Evaluation of Deep Foundation Pit Construction Based on Extension Cloud Model

Deep foundation pit construction faces significant safety challenges—including frequent accidents and severe disaster consequences—due to inherent complexity and uncertainty. Conventional risk assessment methods cannot adequately evaluate these complex engineering systems. This study introduces the concept of resilience to analyze safety issues during the deep foundation pits construction process and develops a safety resilience evaluation model based on the extension cloud model theory. First, based on the characteristics of the deep foundation pit construction process and the four stages of safety resilience, a safety resilience curve for deep foundation pit construction is plotted. Then, using multi-text analysis, an evaluation indicator list for deep foundation pit construction safety resilience is constructed, comprising 4 primary indicators and 24 secondary indicators. Next, based on the extension cloud model theory, the IF-AHP and entropy weight methods are combined to calculate the cloud membership degrees, systematically constructing a safety resilience evaluation model for deep foundation pit construction. Taking the Nanchang HH Center deep foundation pit project as an example, the model’s effectiveness and accuracy are validated. The results indicate that the safety resilience level of this deep foundation pit project is Grade IV, consistent with the actual engineering conditions, thereby validating the scientific validity of this method. This study innovatively applies the concepts of safety resilience and the extension cloud model to deep foundation pit construction assessment, providing a suitable method for evaluating safety risks in deep foundation pit construction projects. The model assists decision-makers in appropriate risk classification and scientific risk prevention strategies, enhances the safety management system for deep foundation pit construction, and even promotes the sustainable development of the construction industry.