Research on risk assessment for building construction sites under heavy rain disasters based on BBWM-Cloud Model

• 1、School of Management, Wuhan University of Science and Technology

Abstract：In order to prevent safety accidents caused by sudden heavy rainfalls on construction sites, this study used the Bayesian Best Worst Method (BBWM) and cloud model method to propose a risk assessment model for construction sites during heavy rainfall disasters, in order to determine the risk level of construction sites in the face of heavy rainfalls. The model utilized the Pressure-State-Response (PSR) model and disaster system theory, and based on considering the danger of the causative factors, the stability of the disaster-prone environment, the vulnerability of the disaster-stricken body, and the resilience of disaster reduction capabilities, constructed an evaluation indicator system consisting of 18 risk factors for construction site risk assessment. The model was verified using a construction site in Wuhan during a heavy rainfall disaster. The results showed that the disaster reduction capabilities of the construction site were the most important, and that effective disaster reduction measures were crucial for responding to disasters. The evaluation result of the case project was in the normal risk state, which was consistent with the actual situation on site. The results of this study provide a tool for construction projects to respond to heavy rainfall disasters and have practical value for their application.

Keywords： heavy rain disasters building construction sites risk assessment Cloud model Bayesian best worst method(BBWM)