Pipe Break Rate Assessment While Considering Physical and Operational Factors: A Methodology Based on Global Positioning System and Data Driven Techniques

Deterioration of urban Water Distribution Networks (WDNs) is one of the primary cases of water supply losses, leading to the huge expenditures on the replacement and rehabilitation of elements WDNs. An accurate prediction of pipes failure rate play a substantial role in the management of WDNs. In this study, a field study was conducted to register pipes break and relevant causes in the WDN of Yazd City, Iran. In this way, 851 water pipes were incepted and localized by the Global Positioning System (GPS) apparatus. Then, 1033 failure cases were reported in the eight zones of under study WDN during March-December 2014. Pipes break rate (BRP) was calculated using the depth of pipe installation (hP), number of failure (NP), pressure of water pipes in operation (P), and age of pipe (AP). After completing a pipe break database, robust Artificial Intelligence models, namely Multivariate Adaptive Regression Spline (MARS), Gene-Expression Programming (GEP), and M5 Model Tree were employed to extract precise formulation for the pipes break rate estimation. Results of the proposed relationships demonstrated that MARS model with Coefficient of Correlation (R) of 0.981 and Root Mean Square Error (RMSE) of 0.544 provided more satisfying efficiency than M5 model (R = 0.888 and RMSE = 1.096). Furthermore, statistical results indicated that MARS and GEP models had comparatively at the same accuracy level. Explicit equations by AI models were satisfactorily comparable with those obtained by literature review in terms of various conditions: physical, operational, and environmental factors and complexity of AI models. Through a probabilistic framework for the pipes break rate, the results of first-order reliability analysis that MARS technique had highly satisfying performance when MARS-extracted-equation was assigned as a limit state function.

State of Watermain Infrastructure: A Canadian Case Study using Historic Pipe Break Datasets

Over the last two decades, a variety of reports have suggested that watermains in Canada are deteriorating, and break rates are increasing. However, these reports are often limited as the years of break records being utilized are brief; this paper revisits those assessments using over forty-five years of break records and shows that three of the five utilities investigated are experiencing significant decreases in break rates over the past 10 years while the two other utilities are maintaining consistent break rates. These results indicate that these utilities are effectively managing their watermain infrastructure, and suggest watermain infrastructure throughout Canada may be performing better than suggested by cross-sectional survey results. Analyses indicate that on average, 22% of the watermains analysed have exceeded the 0.125 brk/km/yr break rate threshold and may be considered for pipe replacement / rehabilitation. In particular 50% of cast iron pipes installed post-WWII have exceeded a break rate threshold of 0.125 brks/km/yr, suggesting large pipe replacement/rehabilitation of this pipe cohort is required.

Water Distribution System Pipe Break Failure Modeling and Analysis: Case Study of Kuwait

The Ministry of Electricity and Water (MEW), as well as other water authorities all over the world, is facing a difficult challenge in assessing the physical condition of its distribution systems. Since the majority of the mains are buried, the MEW must rely upon indirect methods, including analysis of repair records. A case study on Kuwait’s water distribution system using the techniques of survival analysis is analyzed and investigated for modeling the pipe break failures. The proportional hazard model has the advantage of being able to separate the effects of component deterioration on failure due to aging from the effects of site-specific causes. Another desirable feature is its ability to analyze censored data. The sensitivity of the model parameters to sample size and percent censoring is examined through random sampling of the database. In addition, the proportional hazard model is suitable for describing failure rates of components.