Cascading Failure Analysis of Causal Factors for Construction Collapse Accidents Based on Network Theory
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 2
Abstract
Construction collapse accidents are one of the most serious accidents. A variety of causal factors interact with each other, leading to the occurrence of accidents. Some causal factors may cause other causal factors to happen one after another, eventually leading to the occurrence of accidents. The propagation process of causal factors that can lead to construction collapse accident must be clarified. Therefore, this study aims to analyze the propagation path of construction collapse causal factors based on network theory and cascading failure model. First, this study collected and screened the cases of construction collapse accidents, and conducted a statistical analysis of their basic information. Second, a construction collapse accident causation (CCAC) framework was established to identify causal factors in accident cases. Then, a CCAC network model was established. Based on multiple measurement criteria in complex network theory, the causal factors were ranked. After that, through the cascading failure analysis of the causal factors, the critical causal factor-accident propagation path was obtained. It is found that construction scheme and organization is at the beginning and is the source of other causal factors. Finally, five cases were analyzed to verify the rationality of the results. This paper provides a solution to study the propagation path of causal factors and find out the characteristics of the CCAC mechanism through a large number of accident cases, which has theoretical and practical significance for the prevention of construction collapse accidents.
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Data Availability Statement
All data and models generated and used to support the findings of this study are available from the corresponding author upon reasonable request. All 782 incident reports are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Science Foundation of China (Grant No. 71702136).
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Journal of Construction Engineering and Management
Volume 150 • Issue 2 • February 2024
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© 2023 American Society of Civil Engineers.
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Received: Nov 25, 2022
Accepted: Oct 6, 2023
Published online: Dec 15, 2023
Published in print: Feb 1, 2024
Discussion open until: May 15, 2024
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