Subway construction accident causation network modeling and analysis

doi:10.16265/j.cnki.issn1003-3033.2020.01.024

Abstract

Abstract: In order to reveal evolution law between accidents and their causation factors, a double-layer SCACN model combining causation layer and accident layer were built based on real cases of subway construction, and network topological structure and internal mechanism were analyzed. According to calculation, cumulative degree distribution of its sub-networks all followed a power law with smaller shortest path length and higher clustering coefficient, and they presented features of scale-free and small-world networks. Also, SCACN showed robustness to random attacks but vulnerability to specific attacks. The results show that inadequate safety management, lack of safety awareness, and mechanical failure are initial causation factors that lead to a large number of accidents. Eliminating key nodes with large degree will reduce subsequent accidents to the maximum extent and improve safety management of subway engineering construction.

Key words: subway construction accident causation network (SCACN), causation factors, topological analysis, node failure, robustness

CLC Number:

X928.02

GUO Wenya, ZHOU Zhipeng. Subway construction accident causation network modeling and analysis[J]. China Safety Science Journal, 2020, 30(1): 155-161.

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