| description 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 for analysis tools to guide the system architecture process. There is a need for the creation of resilience tools that are time-based and applicable to 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 the 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 article 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. | |
