弹性(材料科学)
过程(计算)
社区复原力
民用基础设施
多智能体系统
风险分析(工程)
地震灾害
计算机科学
土木工程
工程类
系统工程
业务
可靠性工程
人工智能
操作系统
物理
冗余(工程)
热力学
作者
Li Sun,Božidar Stojadinović,Giovanni Sansavini
出处
期刊:Journal of Infrastructure Systems
[American Society of Civil Engineers]
日期:2019-04-01
卷期号:25 (2)
被引量:42
标识
DOI:10.1061/(asce)is.1943-555x.0000492
摘要
In this paper, an agent-based modeling framework to evaluate the seismic resilience of an integrated system comprising the community and its civil infrastructure systems is proposed. Specifically, an agent-based model of the recovery process of civil infrastructure systems is incorporated into a previously developed compositional supply/demand seismic resilience quantification framework. The proposed model represents the behavior of the operators of civil infrastructure systems as they strive to recover their functionality in the aftermath of an earthquake as well as their mutual interactions and the interactions with the community they provide services to. A case study of the seismic resilience of a virtual system comprising the electric power supply system, the transportation system and the community (EPSS-TS-Community system) is conducted using the proposed framework. A parametric investigation is carried out to examine the effect of different earthquake magnitude scenarios as well as different behaviors of the involved agents and their interaction on the seismic resilience of the virtual system. It was demonstrated that the proposed agent-based modeling approach is effective in representing the interactions among different participants in the recovery process. It was also revealed that timely and well-planned intervention in the recovery process can be effective in alleviating the post-earthquake lack of resilience resulting from the insufficient supply of civil infrastructure service to meet the community demands. Therefore, the proposed framework could be employed to formulate the recovery trajectory of the intertwined socio-technical system subjected to different earthquake scenarios. The interplay among different agents, as well as the interdependence between civil infrastructure systems is found to profoundly shape the recovery path for this integrated EPSS-TS-Community system.
科研通智能强力驱动
Strongly Powered by AbleSci AI