4.6 Article

Integrated Framework of Modified Accident Energy Release Model and Network Theory to Explore the Full Complexity of the Hangzhou Subway Construction Collapse

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ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)ME.1943-5479.0000431

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Hangzhou subway construction collapse (HZSCC); Modified accident energy release model (MAERM); Network theory; Accident network; Safety management

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The Hangzhou subway construction collapse (HZSCC) is a serious accident that caused the most casualties in China's subway construction history. This disaster took place on November 15, 2008, causing 21 fatalities and 24 injuries. Past analyses of the HZSCC were incomplete, and using traditional linear causation models made it difficult to grasp the nature of the HZSCC within its complex context of subway construction. This study aims to capture the full complexity of the HZSCC, on the basis of an integrated framework of a modified accident energy release model (MAERM) and network theory. Given that the energy release model has the advantage of revealing the nature of accident occurrence from an ontological perspective, it was adopted and was modified by employing the hierarchy of the causal influences model. The HZSCC causation analysis was conducted by identifying energy sources and analyzing invalidation of energy restraints. This accident is not isolated but rather a combination of 11 subaccidents. The multiple relationships among these subaccidents constitute an accident network within the process of the HZSCC. Commercially available software was employed to build the accident network and calculate corresponding topological parameters of average degree, average path length, diameter, clustering coefficient, and betweenness centrality. The concise and precise calculation of the topological parameters can benefit subaccidents propagation analysis in a broad sense and comprehension of the dynamic features of the HZSCC. The proposed framework has the potential for accident prediction, as the original accident can be regarded as a precursor event that could predict and prevent secondary and derivative accidents in an accident network.

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