Dynamic dual-layer network resilience assessment as a system architecting tool
Paparistodimou, Giota and Knight, Philip and Robb, Malcolm and Hughes, Gail (2025) Dynamic dual-layer network resilience assessment as a system architecting tool. Journal of Mechanical Design. pp. 1-58. ISSN 1050-0472 (https://doi.org/10.1115/1.4068458)
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Abstract
Modern complex systems should be resiliently designed to enable recovery in a variety of expected or unexpected environments. Resilience is defined as the ability to withstand and recover from disruptive events. The objective of developing resilient systems drives the need of analysis tools to guide the system architecture process. There is a need for the creation of resilience tools that are time-based and are applicable for the system architecture process. The larger literature offers a variety of methods and quantitative metrics for assessing resilience. Still, there is a lack of system architecting tools that focus on assessing the resilience of system architecture options considering the dual nature of the system's physical and functional aspects while taking into account the design of redundancy into the system's recoverability behavior. To bridge this gap, this paper proposes a dynamic network-based resilience assessment method that models systems as a dual layer functional and physical network. The method, which has been developed into a computational tool, generates a measure of resilience that serves as a quantitative evaluation indicator during system architecting. As a case study, the method is applied to eight power and propulsion system architecture options. The findings demonstrate that, even before a system architecture has matured, the tool supports informed decision-making, for example in terms of measuring the effectiveness of redundancy introduced to improve resilience, as well as early detection of system vulnerabilities.
ORCID iDs
Paparistodimou, Giota, Knight, Philip
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Item type: Article ID code: 92741 Dates: DateEvent16 April 2025Published16 April 2025Published Online10 April 2025AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 01 May 2025 14:32 Last modified: 02 May 2025 00:39 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/92741