A quantitative approach for risk assessment of a ship stuck in ice in Arctic waters
A quantitative approach for risk assessment of a ship stuck in ice in Arctic waters
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北极水域困冰船舶风险评估的定量方法
DOI：
10.1016/j.ssci.2017.07.001
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发表时间：
2018-08-01
期刊：
影响因子：
6.1
通讯作者：
Yan, Xinping
中科院分区：
文献类型：
--
作者：
Fu, Shanshan;Zhang, Di;Yan, Xinping
北极沃茨历来被视为恶劣的环境，因为其极端的气候条件和远离陆地。最近，由于海路较短和碳氢化合物能源开发的优势，在这种恶劣环境中的海洋活动有所增加。为了确保区域内的安全运营，需要系统地分析、评估和管理船舶事故的潜在风险沿着相关的不确定性。还应考虑处理由于缺乏知识和信息而导致的不良事件可能性的认识不确定性。本文提出了一种基于Frank Copula的模糊事件树分析方法，用于北极沃茨重大船舶事故的风险评估，考虑到不确定性。该定量方法包括四个步骤，即事故情景的事件树模型建模，相关中间事件的概率和相关性分析，后果事件的风险评估。以北极沃茨的一次重大船舶事故--船舶陷入冰中为例，说明了该方法的建模过程。船员和船东可以使用这种方法来定义风险控制选项，以实现最佳的风险缓解。海洋管理也可受益于更好的风险评估。(C)2017爱思唯尔有限公司版权所有
Arctic waters have historically been regarded as harsh environments owing to their extreme weather conditions and remoteness from land. The advantages of shorter sea routes and hydrocarbon energy exploitation have recently led to increased marine activities in such harsh environments. To ensure safe operation within the area, the potential risks of ship accidents, need to be systematically analyzed, assessed and managed along with the associated uncertainties. The treatment of epistemic uncertainty in the likelihoods of adverse events due to lack of knowledge and information should also be considered. This paper presents a Frank copula-based fuzzy event tree analysis approach to assess the risks of major ship accidents in Arctic waters, taking uncertainty into consideration. The quantitative approach includes four steps, namely, accident scenario modeling by an event tree model, probability and dependence analysis of the associated intermediate events, risk assessment with respect to the consequent outcome events. A major ship accident in Arctic waters - ships stuck in ice, is chosen as a case to interpret the modeling process of the approach proposed. Crews and ships owners can use such approach to defining risk control options that enable optimal risk mitigation. Maritime management may also benefit from better risk assessment. (C) 2017 Elsevier Ltd. All rights reserved.