Assessment of port resilience using Bayesian network: A study of strategies to enhance readiness and response capacities

端口(电路理论) 弹性(材料科学) 计算机科学 贝叶斯网络 风险分析(工程) 自然灾害 运筹学 环境资源管理 工程类 运输工程 业务 环境科学 地理 人工智能 气象学 电气工程 热力学 物理
作者
Nanxi Wang,Min Wu,Kum Fai Yuen
出处
期刊:Reliability Engineering & System Safety [Elsevier]
卷期号:237: 109394-109394 被引量:100
标识
DOI:10.1016/j.ress.2023.109394
摘要

Ports, as critical infrastructure, are a crucial part of the maritime transportation system (MTS) and are increasingly vulnerable to disturbances and disasters in the post-pandemic era. Resilience plays a crucial role in building sustainable infrastructure, and developing a resilient port system is a priority in planning and developing MTS. This paper aims to develop measures to enhance port resilience that can cope with risks and uncertainties. A circular four-stage method is proposed to study port resilience. The major disturbances that are currently affecting ports are summarized and classified. Then, a port resilience assessment model using the Bayesian network is proposed, in which various resilience strategies are categorized into different metrics to assess resilience capabilities (i.e. readiness and response capacities). The model is constructed based on expert judgment and statistical analysis. The Shanghai Yangshan Deepwater Port in China is used as a case study. The results show that natural disasters are major disruptors plaguing ports. The overall resilience of automated terminals is higher than that of non-automated terminals. Strategies to enhance visibility, such as building real-time data management systems and data analysis programs, have the most significant impact on improving ports’ readiness. Strategies to enhance recovery such as facility restoration and technology restoration are the most important when improving ports’ response capability.
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