4.5 Article

Development of a civil infrastructure resilience assessment framework and its application to a nuclear power plant

期刊

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/15732479.2020.1832538

关键词

Bayesian network; decision making; fragility; functionality; losses; natural hazards; networked infrastructure; nuclear power plant; recovery; reliability; Resilience; software

资金

  1. Natural Sciences and Engineering Research Council of Canada (NSERC) [CRDPJ 480802-15]

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This study proposes a Civil Infrastructure Resilience Assessment Framework to evaluate seismic fragility and resilience, quantifying functionality loss, recovery time, repair cost, and overall resilience using a Bayesian Network approach. An engineering tool is developed to simplify stakeholders' decision-making process.
Recent disruptive events, such as earthquakes or floods, have caused severe damage to civil infrastructure systems. Thus, there is a need to extend the focus of traditional design practices to include resilience-based design approaches which can help in defining preventive actions and measures to mitigate the consequences caused by such disruptive events. This paper presents a Civil Infrastructure Resilience Assessment Framework (CIRAF) to assess the seismic fragility and resilience of a single or multiple interconnected civil infrastructure systems following a disruptive event. Once the information regarding the infrastructure system, hazards, fragility functions, component's damage state correlation, recovery models, and upgrade models are identified, then the framework can be used to quantify the loss of functionality, recovery time, repair cost, and overall resilience using a Bayesian Network approach. A state-of-the-art engineering tool is also developed using the framework that would enable the stakeholders to compare different upgrade strategies through an easy to use web interface and thus easing the decision-making process. A case study of a hypothetical nuclear power generation system is used to assess the seismic fragility and resilience using the proposed framework.

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