Modeling Blockage Failures in Sewer Systems to Support Maintenance Decision Making

Abstract

The objective of this research is to develop and implement a stochastic method that can be applied to characterize random failures in critical infrastructure systems. We particularly focus on blockage failures in sewer systems that are nonmechanistic and result from combination of external factors, including deterioration in condition. The method was implemented using a data set consisting of sewer blockage failure records from a small municipality. Statistical tests were conducted to: (1) ensure that available data set is representative and (2) estimate parameters of distributions that appropriately characterize failure event arrival pattern. Failure trends were also analyzed to identify the influence of local factors and justify the choice of the distributions used to characterize interarrival times. Based on the analysis, we explored the challenges in developing a reliability model across the life cycle of a sewer system. In addition, specific examples were also presented to illustrate how the method can be applied to support system maintenance decisions. The results of this study illustrate how the memoryless property can be assumed in analyzing failure events, while explicitly considering context specific influences. Finally, the methods described in this paper are extensible and can be applied generally to analyzing random failures in other infrastructure systems as well.