当前位置:
X-MOL 学术
›
arXiv.cs.CE
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Multi-agent Modeling of Hazard-Household-Infrastructure Nexus for Equitable Resilience Assessment
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2021-06-06 , DOI: arxiv-2106.03160 Amir Esmalian, Wanqiu Wang, Ali Mostafavi
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2021-06-06 , DOI: arxiv-2106.03160 Amir Esmalian, Wanqiu Wang, Ali Mostafavi
To enable integrating social equity considerations in infrastructure
resilience assessments, this study created a new computational multi-agent
simulation model which enables integrated assessment of hazard, infrastructure
system, and household elements and their interactions. With a focus on
hurricane-induced power outages, the model consists of three elements: 1) the
hazard component simulates exposure of the community to a hurricane with
varying intensity levels; 2) the physical infrastructure component simulates
the power network and its probabilistic failures and restoration under
different hazard scenarios; and 3) the households component captures the
dynamic processes related to preparation, information seeking, and response
actions of households facing hurricane-induced power outages. We used empirical
data from household surveys in conjunction with theoretical decision-making
models to abstract and simulate the underlying mechanisms affecting experienced
hardship of households. The multi-agent simulation model was then tested in the
context of Harris County, Texas, and verified and validated using empirical
results from Hurricane Harvey in 2017. Then, the model was used to examine
effects of different factors such as forewarning durations, social network
types, and restoration and resource allocation strategies on reducing the
societal impacts of service disruptions in an equitable manner. The results
show that improving the restoration prioritization strategy to focus on
vulnerable populations is an effective approach, especially during
high-intensity events. The results show the capability of the proposed
computational model for capturing the dynamic and complex interactions in the
nexus of humans, hazards, and infrastructure systems to better integrate
human-centric aspects in resilience planning and into assessment of
infrastructure systems in disasters.
中文翻译:
用于公平复原力评估的灾害-家庭-基础设施联系的多代理建模
为了在基础设施恢复力评估中整合社会公平因素,本研究创建了一个新的计算多代理模拟模型,可以对灾害、基础设施系统和家庭要素及其相互作用进行综合评估。该模型侧重于飓风引起的停电,由三个要素组成:1) 灾害分量模拟社区暴露于不同强度级别的飓风;2) 物理基础设施组件模拟电力网络及其在不同灾害场景下的概率故障和恢复;3) 家庭部分捕捉与面临飓风引起的停电的家庭的准备、信息搜索和响应行动相关的动态过程。我们利用住户调查的经验数据结合理论决策模型来抽象和模拟影响住户经历困难的潜在机制。多智能体模拟模型随后在德克萨斯州哈里斯县进行了测试,并使用 2017 年飓风哈维的实证结果进行验证和验证。 然后,该模型用于检查不同因素的影响,如预警持续时间、社交网络类型、恢复和资源分配策略,以公平的方式减少服务中断的社会影响。结果表明,改进以脆弱人群为重点的恢复优先级策略是一种有效的方法,尤其是在高强度事件期间。
更新日期:2021-06-08
中文翻译:
用于公平复原力评估的灾害-家庭-基础设施联系的多代理建模
为了在基础设施恢复力评估中整合社会公平因素,本研究创建了一个新的计算多代理模拟模型,可以对灾害、基础设施系统和家庭要素及其相互作用进行综合评估。该模型侧重于飓风引起的停电,由三个要素组成:1) 灾害分量模拟社区暴露于不同强度级别的飓风;2) 物理基础设施组件模拟电力网络及其在不同灾害场景下的概率故障和恢复;3) 家庭部分捕捉与面临飓风引起的停电的家庭的准备、信息搜索和响应行动相关的动态过程。我们利用住户调查的经验数据结合理论决策模型来抽象和模拟影响住户经历困难的潜在机制。多智能体模拟模型随后在德克萨斯州哈里斯县进行了测试,并使用 2017 年飓风哈维的实证结果进行验证和验证。 然后,该模型用于检查不同因素的影响,如预警持续时间、社交网络类型、恢复和资源分配策略,以公平的方式减少服务中断的社会影响。结果表明,改进以脆弱人群为重点的恢复优先级策略是一种有效的方法,尤其是在高强度事件期间。