ABSTRACT
Statistical models that predict the deterioration of sewer pipes are useful for planning financial resources required for sewer renewal. Usually, data that are available to calibrate these models solely concern pipes that are still in place, leading to underestimated deterioration rates. A new method is proposed to consider possible past replacement of pipes in the statistical modeling of their deterioration. The proposed method considers the aging of pipes, simulated with a Cox model, and their probability to be replaced separately. Application to a synthetic sewer network, for which it was assumed that information regarding all pipe replacements over the lifetime of the network was available, showed that the proposed method allows for improved predictions of the sewer deterioration model, when compared to predictions of a model calibrated without considering the information about replaced pipes.
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