Name
Abstract | ||
|---|---|---|
Increasing system complexity and threat uncertainty require the consideration of resilience in the design and analysis of engineered systems. While the resilience engineering community has begun to converge on a definition and set of characteristics for resilience, methods for quantifying the concept are still limited in their applicability to system designers. This paper proposes a framework for assessing resilience that focuses on the ability of a system to absorb disruptions, recover from them, and adapt over time. The framework extends current approaches by explicitly considering temporal aspects of system responses to disruptions, volatility in system performance data, and the possibility of multiple disruption events. Notional system performance data is generated using the logistic function, providing an experimental platform for a parametric comparison of the proposed resilience metric with an integration-based metric. An information exchange network model is used to demonstrate the applicability of the framework towards system design tradeoff studies using stochastic simulations. The presented framework is domain-agnostic and flexible, such that it can be applied to a variety of systems and adjusted to focus on specific aspects of resilience. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.ress.2016.10.014 | Reliability Engineering & System Safety |
Keywords | Field | DocType |
System resilience,Resilience metrics,Adaptive networks | Psychological resilience,Computer science,Information exchange,Systems design,Parametric statistics,Logistic function,Notional amount,Reliability engineering,Network model,Socio-ecological system | Journal |
Volume | ISSN | Citations |
158 | 0951-8320 | 5 |
PageRank | References | Authors |
0.52 | 23 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huy Tran | 1 | 286 | 31.59 |
| Michael Balchanos | 2 | 6 | 3.17 |
| Jean Charles Domercant | 3 | 9 | 2.12 |
| Dimitri N. Mavris | 4 | 34 | 9.50 |