Understanding the Effect of Interdependency and Vulnerability on the Performance of Civil Infrastructure

Vulnerability is a measure of the extent to which a community, structure, services or geographic area is likely to be damaged or disrupted by the impact of particular hazard. Current asset management practices focuses on studying factors that affect performance of isolated infrastructure networks and model a set of actions to control the expected performance of these networks. This approach ignores the underlying spatial and functional interdependencies among these infrastructure networks and their vulnerability. The purpose of this paper is to introduce a new method that recognizes the effect of spatial and functional interdependencies on vulnerability rating of water, sewer and road networks. The proposed method consists of: 1) risk assessment model, 2) interdependency assessment model and 3) vulnerability assessment model. The risk model is composed of two modules: 1) water and sewer risk module and 2) road infrastructure module. The water and sewer risk module will cluster these assets into three risk categories based on environmental, social, operational and economical factors. The road infrastructure module will cluster road assets into three risk categories by using rational factorial technique based on road type, serviceability index, traffic load, and freeze and thaw index. The interdependency model will deploy the risk ranking to perform geospatial analysis in ArcGIS which results in determining the interdependent layers of waters, sewers and roads. The vulnerability model will deploy fuzzy neural networks technique to determine the vulnerability rating based on spatial and functional interdependencies. The fuzzy neural networks are utilized to overcome the lack of historical data and incorporate experts’ preferences for establishing the knowledge base for vulnerability assessment. The expected contribution of this framework is to aid decision makers in understanding the interdependencies between civil infrastructure assets and to which extent such interdependencies can compromise assets performance.