New Risk Management Study Results Reported from Colorado State University (Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams)

2019 MAY 13 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Researchers detail new data in Risk Management. According to news reporting out of Fort Collins, Colorado, by NewsRx editors, research stated, “Probabilistic risk assessment (PRA) is a useful tool to assess complex interconnected systems. This article leverages the capabilities of PRA tools developed for industrial and nuclear risk analysis in community resilience evaluations by modeling the food security of a community in terms of its built environment as an integrated system.”

Financial support for this research came from National Science Foundation.

Our news journalists obtained a quote from the research from Colorado State University, “To this end, we model the performance of Gilroy, CA, a moderate-size town, with regard to disruptions in its food supply caused by a severe earthquake. The food retailers of Gilroy, along with the electrical power network, water network elements, and bridges are considered as components of a system. Fault and event trees are constructed to model the requirements for continuous food supply to community residents and are analyzed efficiently using binary decision diagrams (BDDs). The study also identifies shortcomings in approximate classical system analysis methods in assessing community resilience. Importance factors are utilized to rank the importance of various factors to the overall risk of food insecurity. Finally, the study considers the impact of various sources of uncertainties in the hazard modeling and performance of infrastructure on food security measures.”

According to the news editors, the research concluded: “The methodology can be applicable for any existing critical infrastructure system and has potential extensions to other hazards.”

For more information on this research see: Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams. Risk Analysis, 2019;():. (Wiley-Blackwell - http://www.wiley.com/; Risk Analysis - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6924)

Our news journalists report that additional information may be obtained by contacting S. Nozhati, Dept. of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States. Additional authors for this research include B.R. Ellingwood and H. Mahmoud.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/risa.13321. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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