Risk-Informed Prioritization for Complex Engineered Systems: Two US Army Corps of Engineers Case Studies

Many complex socio-technical systems enable the conduct of daily activities across the United States. These systems incorporate engineered systems, their human operators, processes, and the people, property, and environments the systems affect. Understanding these socio-technical systems and the interactions within them is difficult. The U.S. Army Corps of Engineers must allocate resources to operate and maintain complex socio-technical systems across multiple business lines, such as Flood Risk Management, in order to mitigate risk. This chapter presents a methodology to provide decision-makers with improved understanding of their complex socio-technical systems through the development of a risk-informed prioritization framework. Likelihood of facility and system degradation based on the condition of components is developed from subject matter expert initialized Bayesian networks. Designed simulation experiments with hydrological models provide estimates of flood consequences at the watershed level. By combining likelihood and consequence values, this methodology develops relative risk scores that are used as inputs to a mixed integer program that provides decision-makers a recommended set of investments given constrained resources. Two case study applications are provided.