Risk assessment of large-scale winter sports sites in the context of a natural disaster

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Jiansong Wu , Yuxuan Xing , Yiping Bai , Xiaofeng Hu , Shuaiqi Yuan
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引用次数: 2

Abstract

Accidents induced by natural disasters at sports sites may cause catastrophic loss of great concern. However, previous studies on risk assessments of sports sites have only focused on operational risk and equipment failure. With the frequent occurrence of extreme disasters, the risk of domino chains caused by natural disasters at large-scale events, such as large-scale winter sports sites, cannot be ignored. In this study, a natural disaster-induced accident-chain evolution analysis model (NAEA model) is proposed. Based on the results of the NAEA model, a fuzzy Bayesian network for domino accidents triggered by an earthquake at large-scale winter sports sites was established. Through sensitivity analysis and scenario analysis, it was found that fire and explosion accidents and crowded stampede accidents are the main causes of serious loss in domino disaster chains in large-scale sports sites. Simultaneously, improving the early warning capability, reliability of electrical equipment, and automatic sprinkler systems are the most effective ways to prevent and control major accidents. In addition, an optimal safety strategy improvement analysis was performed to facilitate the decision-making of safety managers to prevent serious accidents and reduce accident loss.

自然灾害背景下大型冬季运动场地风险评估
自然灾害引起的体育场地事故可能会造成重大的灾难性损失。然而,以往关于体育场地风险评估的研究只关注于操作风险和设备故障。随着极端灾害的频繁发生,在大型冬季运动场地等大型赛事中,自然灾害引发的多米诺骨牌连锁风险不容忽视。本文提出了自然灾害事故链演化分析模型(NAEA模型)。在NAEA模型的基础上,建立了大型冬季运动场地地震引发多米诺骨牌事故的模糊贝叶斯网络。通过敏感性分析和情景分析发现,火灾爆炸事故和人群踩踏事故是大型体育场馆多米诺骨牌灾害链中造成严重损失的主要原因。同时,提高预警能力、电气设备可靠性和自动喷水灭火系统是预防和控制重大事故的最有效途径。并进行了最优安全策略改进分析,为安全管理者提供决策依据,防止重大事故发生,减少事故损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
安全科学与韧性(英文)
安全科学与韧性(英文) Management Science and Operations Research, Safety, Risk, Reliability and Quality, Safety Research
CiteScore
8.70
自引率
0.00%
发文量
0
审稿时长
72 days
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