弹性(材料科学)
风险分析(工程)
计算机科学
建筑工程
工程类
业务
热力学
物理
作者
Xiaogang Song,Zhengxuan Li,Yaohua Liu
标识
DOI:10.1038/s41598-025-18161-0
摘要
With the construction industry's deepening development towards digitalization, intelligentization, greening, and industrialization, prefabricated building is poised for significant promotion due to its characteristics of energy efficiency, environmental friendliness, rapid progress, and high quality. Current safety management models for prefabricated construction primarily focus on preventing safety accidents, lacking a holistic, systematic analysis of the system's comprehensive capability when subjected to risk disturbances. This study adopts a resilience perspective, focusing on the safety resilience of prefabricated construction engineering systems. Utilizing accident case studies and academic literature as sources, it preliminarily identifies 24 influencing factors of safety resilience based on the four types of resilience. The rationality of the indicator system is validated through confirmatory factor analysis, including structural validity, convergent validity, and discriminant validity. Based on the screened and validated safety resilience indicator system, a Bayesian Network model for the safety resilience of prefabricated construction engineering is established. Through forward causal inference, backward diagnostic inference, and sensitivity analysis within the Bayesian Network model, critical influencing pathways and sensitive nodes are identified. Targeted countermeasures and suggestions to enhance the safety resilience of prefabricated construction engineering systems are proposed. This approach can effectively improve the system's risk resistance capability and post-disaster rapid recovery capacity, thereby strengthening its overall safety resilience.
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