Efficient Approach to Compute Generalized Interdependent Effects between Infrastructure Systems

Abstract

Most studies on infrastructure interdependencies only explore a subset of the possible damage states in which they operate. Typically, interdependence effects (IE) are measured in terms of common failure fractions (f) of components across systems. In this paper, an expanded damage space is explored where infrastructure systems can simultaneously experience different failure fractions f. This augmented space is then mapped onto a functionality space where IEs are evaluated as a function of the efficiencies of constitutive systems: a desirable feature because efficiency is typically measured and recorded in practice whereas f is not. These new IEs conditioned on efficiency levels are termed generalized interdependent effects (GIE), which can be predicted or detected in a computationally efficient fashion. Prediction is a function of initial efficiencies before damage propagation and can be used in prefailure analyses, whereas detection is a function of final joint efficiencies for postfailure analyses. To illustrate the quantification of the nonnegative GIE metric, this study uses artificial power (p) and gas (g) networks with flow traversal capabilities. Results show that the maximum predicted or detected GIE of power on gas and gas on power among all efficiencies are GIEp→gmax⁡=1.54 and GIEg→pmax⁡=0.19, respectively, highlighting the relative inadequacy of the gas system to function independently (high GIE) and vice versa. The proposed practical metric is expected to provide useful information to infrastructure decision makers on strategies to design interdependent topology and handle interdependencies when operating at different regimes.