Abstract
Resilience, the ability to withstand disruptions and recover quickly, must be considered during system design because any disruption of the system may cause considerable loss, including economic and societal. This work develops analytic maximum flow-based resilience models for series and parallel systems using Zobel’s resilience measure. The two analytic models can be used to evaluate quantitatively and compare the resilience of the systems with the corresponding performance structures. For systems with identical components, the resilience of the parallel system increases with increasing number of components, while the resilience remains constant in the series system. A Monte Carlo-based simulation method is also provided to verify the correctness of our analytic resilience models and to analyze the resilience of networked systems based on that of components. A road network example is used to illustrate the analysis process, and the resilience comparison among networks with different topologies but the same components indicates that a system with redundant performance is usually more resilient than one without redundant performance. However, not all redundant capacities of components can improve the system resilience, the effectiveness of the capacity redundancy depends on where the redundant capacity is located.
Highlights
Modern society is built on adaptive and intelligent infrastructure systems that deliver energy and information to support productivity, water to meet basic needs, and transportation to connect communities
This paper focuses on modeling maximum flow-based system resilience according to the resilience of components, which was always neglected in previous engineering research
This paper proposes two new component-based system resilience models for series and parallel systems, in which the maximum flow is used as the key performance index (KPI)
Summary
Modern society is built on adaptive and intelligent infrastructure systems that deliver energy and information to support productivity, water to meet basic needs, and transportation to connect communities. The infrastructure systems are vulnerable to many natural disasters and man-made attacks that threaten the services they provide, and the performance degradation may cause considerable financial loss. The 2009 L’Aquila earthquake in Italy and the 2011 Tohoku earthquake in Japan exemplified the vulnerability of our modern, highly complex infrastructure systems. To face so many surprising combinations of events and more extreme stressors, building resilience becomes the best decision for large, complex infrastructure systems [4]. Park et al [5] described resilience analysis as complementary to risk analysis with important implications for the adaptive management of complex systems
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