A Quantitative Framework for Resilience Assessment of Complex Engineered Systems under Uncertainty

Sunyue Geng, Ming Yang*, Sifeng Liu

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

39 Downloads (Pure)

Abstract

Complex engineered systems with various components and dynamic behaviors are connerstones to develop resilient cities and societies. These systems are robust but also vulnerable to adverse events and inevitably suffer performance degradation. An immediate question would be, “how can we manage and improve the resilience of a complex engineered system?”. This study proposes a quantitative framework to assess the resilience of complex engineered systems. The proposed framework focuses on figuring out the impact of functionality implementation on the capability of complex engineered systems to anticipate, absorb, adapt to, and restore from disruptive events. It is composed of three parts, including functionality analysis, performance evaluation, and resilience measure. Firstly, various functions are analyzed at the system level, where a functional tree is employed to investigate the relationship between functions. Then the actual performance of the system is evaluated while uncertain implementation of system functionality is considered. Finally, system resilience is measured from the perspectives of anticipation, absorption, adaptation, and restoration. Anticipation, absorption, adaptation, and restoration are critical capacities of complex engineered systems to ensure normal operation in the event of disruptions. The proposed framework provides a general approach for resilience assessment of complex engineered systems, which figures out functionality implementation and system performance under uncertainty.
Original languageEnglish
Pages (from-to)31-36
Number of pages6
JournalChemical Engineering Transactions
Volume91
DOIs
Publication statusPublished - 2022

Fingerprint

Dive into the research topics of 'A Quantitative Framework for Resilience Assessment of Complex Engineered Systems under Uncertainty'. Together they form a unique fingerprint.

Cite this