QUANTITATIVE RESILIENCE ASSESSMENT OF CHEMICAL PROCESS SYSTEMS USING FUNCTIONAL RESONANCE ANALYSIS METHOD AND DYNAMIC BAYESIAN NETWORK

dc.contributor.authorZinetullina, Altyngul
dc.contributor.authorYang, Ming
dc.contributor.authorKhakzad, Nima
dc.contributor.authorGolman, Boris
dc.contributor.authorLi, Xinhong
dc.date.accessioned2021-07-14T08:26:41Z
dc.date.available2021-07-14T08:26:41Z
dc.date.issued2021
dc.description.abstractThe emergent hazards of chemical process systems cannot be wholly identified and are highly uncertain due to the complicated technical-human-organizational interactions. Under uncertain and unpredictable circumstances, resilience becomes an essential property of a chemical process system that helps it better adapt to disruptions and restore from surprising damages. The resilience assessment needs to be enhanced to identify the accident's root causes on the level of technical-human-organizational interactions, and development of the specific resilience attributes to withstand or recover from the disruptions. The outcomes of resilience assessment are valuable to identify potential design or operational improvements to ensure complex process system functionality and safety...en_US
dc.identifier.citationZinetullina, A., Yang, M., Khakzad, N., Golman, B., & Li, X. (2021). Quantitative resilience assessment of chemical process systems using functional resonance analysis method and Dynamic Bayesian network. Reliability Engineering and System Safety, 205, [107232]. https://doi.org/10.1016/j.ress.2020.107232en_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/5571
dc.language.isoenen_US
dc.publisherReliability Engineering and System Safetyen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectresilience assessmenten_US
dc.subjectchemical process systemsen_US
dc.subjectdynamic Bayesian networken_US
dc.titleQUANTITATIVE RESILIENCE ASSESSMENT OF CHEMICAL PROCESS SYSTEMS USING FUNCTIONAL RESONANCE ANALYSIS METHOD AND DYNAMIC BAYESIAN NETWORKen_US
dc.typeArticleen_US
workflow.import.sourcescience

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