Developing Sustainable Urban Water Infrastructure via Smart Decision Support Systems and Trenchless Technology-based Mitigation Strategies

It is estimated that about 20% of treated drinking water is lost through distribution pipeline leakages in the United States. Pipeline leakage detection is a top priority for water utilities across the globe as leaks increase operational energy consumption and could also develop into potentially catastrophic water main breaks, if left unaddressed. Leakage detection is a laborious task often limited by the financial and human resources that utilities can afford. Many conventional leak detection techniques also only offer a snapshot indication of leakage presence. Furthermore, the reliability of many leakage detection techniques on plastic pipelines that are increasingly preferred for drinking water applications is questionable. As part of a smart water utility framework, this paper proposes and validates a hydraulic model-based technique for detecting and assessing the severity of leakages in buried water pipelines through monitoring of pressure from across the water distribution system (WDS). The envisioned smart water utility framework entails the capabilities to collect water consumption data from a limited number of WDS nodes and pressure data from a limited number of pressure monitoring stations placed across the WDS. A popular benchmark WDS is initially modified by inducing leakages through addition of orifice nodes. The leakage severity is controlled using emitter coefficients of the orifice nodes. WDS pressure data for various sets of demands is subsequently gathered from locations where pressure monitoring stations are to be placed in that modified distribution network. An evolutionary optimization algorithm is subsequently used to predict the emitter coefficients so as to determine the leakage severities based on the hydraulic dependency of the monitored pressure data on various sets of nodal demands. Artificial neural networks (ANNs) are employed to mimic the popular hydraulic solver EPANET 2.2 for high computational efficiency. The goals of this study are to: (1) validate the proof of concept of the proposed modeling approach for detecting and assessing the severity of leakages and (2) evaluate the sensitivity of the prediction accuracy to number of pressure monitoring stations and number of demand nodes at which consumption data is gathered and used. This study offers new value to prioritize pipes for rehabilitation by predicting leakages through a hydraulic model-based approach.

Gravity flow wastewater collection systems are comprised of sewer pipes and manholes. Failure of a manhole may have catastrophic consequences such as developing a sinkhole in the street and roadway, and at a minimum, wastewater flow will be blocked, and stream of the manhole will backup causing a sanitary sewer overflow (SSO). Improving structural conditions of a manhole is critical to minimize these types of failures. This paper considers the impact of several lining materials including cement mortar, epoxy, polyurethane, cured-in-place composites, and a multi-layer structure material on increasing the structural capabilities of deteriorated manholes. The tasks included in this research consist literature search and, preliminary laboratory and main testing of select manhole rehabilitation materials. A finite element analysis is included to complement the experiments. Several preliminary tests according to ASTM C-39 on coated concrete cylinders, and ASTM C-293 on lined concrete beams, were performed at UT Arlington's Center for Underground Infrastructure Research and Education (CUIRE) Laboratory. The test results showed significant increase in the performance of concrete samples under compression and flexure. A second round of testing was performed on 4-ft long, 24-in. diameter concrete pipe sections with 3-in. wall thickness manufactured according to ASTM C-76. These pipe sections were lined internally with the same materials as the preliminary tests, and tested according to ASTM C-497 under Three-Edge-Bearing testing. Using computer data acquisition system, strain gages and displacement extensometers, stress/strain data were measured. The results showed that tested No-Dig manhole rehabilitation materials can significantly improve structural performance of deteriorated manholes.

Most of urban water infrastructure around the world were built several decades ago and nowadays they are deteriorated. So, the assets that constitute these infrastructures need to be rehabilitated. Since most of the assets are buried, water utilities face the challenge of deciding how, where and when to rehabilitate. Condition assessment is a vital component on plan rehabilitation actions and is mostly based on the data collected from the managed networks. This collected data need to be put together in order to be transformed into useful information. Nonetheless, the large amount of assets and data involved makes data and information management a challenging task for water utilities, especially in those with as lower digital maturity level. This paper highlights the importance of data and information systems' management for urban water infrastructure condition assessment based on the authors' experience.