CONTACT US: Contact info
|
Citation |
Guo Z, Haimes YY. Risk Anal. 2016; 36(8): 1630-1643. |
|
Affiliation |
University of Virginia, Charlottesville, VA, USA. |
|
Copyright |
(Copyright © 2016, Society for Risk Analysis, Publisher John Wiley and Sons) |
|
DOI |
|
PMID |
27575259 |
|
Abstract |
Physical infrastructure systems are commonly composed of interconnected and interdependent subsystems, which in their essence constitute system of systems (S-o-S). System owners and policy researchers need tools to foresee potential emergent forced changes and to understand their impact so that effective risk management strategies can be developed. We develop a systemic framework for precursor analysis to support the design of an effective and efficient precursor monitoring and decision support system with the ability to (i) identify and prioritize indicators of evolving risks of system failure; and (ii) evaluate uncertainties in precursor analysis to support informed and rational decision making. This integrated precursor analysis framework is comprised of three processes: precursor identification, prioritization, and evaluation. We use an example of a highway bridge S-o-S to demonstrate the theories and methodologies of the framework. Bridge maintenance processes involve many interconnected and interdependent functional subsystems and decision-making entities and bridge failure can have broad social and economic consequences. The precursor analysis framework, which constitutes an essential part of risk analysis, examines the impact of various bridge inspection and maintenance scenarios. It enables policy researchers and analysts who are seeking a risk perspective on bridge infrastructure in a policy setting to develop more risk informed policies and create guidelines to efficiently allocate limited risk management resources and mitigate severe consequences resulting from bridge failures. Language: en |