Modeling Interdependent Infrastructure System Vulnerability with Imprecise Information Using Two Fuzzy Inference Systems

Abstract

Infrastructure systems play important roles in economic development and the social quality of life. Interdependencies exist between infrastructure systems: a functional disruption in one system can affect dependent systems, thereby escalating the impacts. It is vital to properly model interdependencies to understand the full impacts of disruptive events on infrastructure systems. Quantitative data on infrastructure interdependency is often difficult to obtain or unavailable for a variety of reasons. To overcome quantitative data scarcity issues, qualitative subject expert knowledge has been used in interdependency analysis, primarily in the form of linguistic responses. Linguistic data is susceptible to uncertainties arising from variations in intended meanings, which may yield inaccurate results. This paper proposes a framework to address this problem using two fuzzy inference systems to model event-specific, network-wide infrastructure failures. The first fuzzy inference system models the damage induced by interdependencies using verbal descriptions. The second fuzzy inference system accounts for synergistic, compounding effects of multiple incidences of indirect damage caused by interdependencies. A case study is conducted to demonstrate the applicability of the proposed methodology using electric and gas distribution networks in the United Kingdom. Sensitivity analyses are performed to show the flexibility of the fuzzy inference systems. The results show that the proposed method can model the interdependency and vulnerability of infrastructure systems using fuzzy inference systems to handle imprecise input. The proposed framework may assist practitioners in better understanding the interdependency and vulnerability of infrastructure systems, and in making more informed decisions to reduce losses resulting from disruptive events.