Water Pipe Replacement Scheduling Based on Life Cycle Cost Assessment and Optimization Algorithm

Abstract

Water distribution networks (WDNs) comprise a complex network of pipes and are crucial for providing potable water to urban communities. Therefore, WDNs must be carefully managed to avoid problems such as water contamination and service failures; however, this requires a large budget. Because WDN components have different statuses depending on their installation year, location, transmission pressure, and flow rate, it is difficult to plan the rehabilitation schedule within budgetary constraints. This study, therefore, proposes a new pipe replacement scheduling approach to smooth the investment time series based on a life cycle cost (LCC) assessment for a large-scale WDN. The proposed scheduling plan simultaneously considers both the annual budget limitation and the optimum expenditure on the useful life of pipes. A multi-objective optimization problem consisting of three decision-making objectives—minimum imposed LCC on the network, minimum standard deviation of annual investment, and minimum average age of the network—is thus solved using a nondominated sorting genetic algorithm to obtain an optimal plan. Three scenarios with different pipe replacement time spans and different annual budget constraints are considered accordingly. The results indicate that the proposed scheduling framework provides an efficient water pipe replacement scheduling plan with a smooth management budget.

Asset management analytics for urban water mains: a literature review

“…• The artificial intelligence model adopts a learning approach to recognizing complicated relationships between input and output data, without calculating the covariate relationships like the deterministic and probabilistic models. Using the artificial intelligence model has the potential to significantly reduce the number of field inspections needed, provide timely warning of break risks and thus avoid a large number of breaks as well as their consequences (Fu et al 2013;Marzouk and Osama 2017;Kakoudakis et al 2017;Snider and McBean 2018;Ghobadi et al 2021).…”

“…The existing review articles have mostly focused on water main prediction models (St. Clair and Sinha 2012;Dawood et al 2020b), the effect of availability and quantity of the database on WM failure models (Snider and McBean 2020a;Chen et al 2022), the effect of the limited, uncertain dataset on WM failure models (Jenkins et al 2014), and the effect of combined datasets from different utilities on the performance of machine learning models for predicting future breaks (Chen et al 2022). Other reviews have discussed different approaches to optimizing rehabilitation and maintenance strategies for WMs and integrated infrastructures (Abusamra 2018;Ghobadi et al 2021;Ramos-Salgado et al 2022;Shahata et al 2022; Barton et al 2022). This review aims to address issues of the failure prediction models developed recently and optimal maintenance strategies conjointly.…”

Assessment of the Impacts of Climate Change on Water Supply System Pipe Failures

“…Additionally, pipes in the current water systems are continuously aging over time, which further exacerbates the failures due to limited budget and underinvestment over the past decades (Ghobadi, Jeong et al 2021). The condition of drinking water system in the United States has been rated at D by the ASCE Report Card (ASCE 2017).…”

An Optimal Maintenance and Replacement Strategy for Deteriorating Water Mains

“…Nevertheless, this is the part that has not yet received due attention in the current literature for the life cycle management of municipal water pipe networks. Existing studies, though they have made significant advances in water pipe management, have focused largely upon network effects and a simplification of methods for LCCA, e.g., Termes-Rifé et al [29], Roshani and Filion [30], Naoum-Sawaya et al [31], Lee et al [32], Ghobadi et al [33], among other excellent works. A brief review of LCCA for water pipes can be found in Ghobadi et al [33].…”