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Browsing by Author "Matthews, John C."
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Item Empirical Analysis of Water-Main Failure Consequences(Elsevier, 2015) Piratla, Kalyan R.; Yerri, Sreeganesh R.; Yazdekhasti, Sepideh; Cho, Jinsung; Koo, Dan; Matthews, John C.; Department of Engineering Technology, School of Engineering and TechnologyModern urban societies depend greatly on critical lifeline systems such as drinking water supply. Water supply systems in the United States comprise about one million mile length of interconnected pipelines that transport water from sources to consumption points with the support of treatment plants, pumping stations, storage tanks and valves. While depleting freshwater sources in some regions is an alarming concern, supply infrastructure woes exacerbate the problem of meeting supply reliability targets. Evidenced by the “D” or lower grade it has been receiving over the past few ASCE infrastructure report cards, the quality of water supply infrastructure has degraded to an extent where 240,000 water mains fail annually in the U.S. A majority of these failures result in significant economic, environmental and societal consequences. Pro-active rehabilitation of deteriorated infrastructure will avoid these unwarranted failure consequences. This paper employs empirical analysis of the economic, environmental and societal consequences of large-diameter water main failures to estimate their overall impact cost. Data on the impacts of 11 large-diameter water main failures has been gathered and synthesized. The results of this paper will aid in predicting the future water main failure consequences to enable risk-based, long-term capital improvement planning of water supply systems.Item Sustainability evaluation of pipe asset management strategies(Elsevier, 2016) Matthews, John C.; Piratla, Kalyan; Koo, Dan D.; Department of Engineering Technology, School of Engineering and TechnologyThe consequences associated with pipe failures can be widespread impacting service, while potentially causing damage, affecting traffic, and contaminating water. Recently the visibility of pipe failures has increased with social media and 24-hour news coverage. In response, many utilities have adapted pipe asset management strategies to reduce failures. Also, many technologies have emerged that allow for a more proactive pipe asset management. As sustainability has become a focus for many organizations including utilities, the question becomes which pipe asset management strategy is most sustainable. The purpose of this paper is to evaluate three pipe asset management strategies for sustainability using Envision®. The strategies include: a reactive run-to-failure and then replace; a preemptive replacement prior to failure based on assumed condition; and a balanced approach of active condition assessment and action based on the known condition. Envision® will be used to evaluate each approach to determine its sustainability rating.Item Towards Sustainable Water Supply: Schematic Development of Big Data Collection Using Internet of Things (IoT)(Elsevier, 2015) Koo, Dan; Piratla, Kalyan; Matthews, John C.; Department of Engineering Technology, School of Engineering and TechnologyWater supply systems in the United States connect raw water sources to hundreds of millions of water consumers through humongous infrastructure that include approximately one million miles of buried water mains and service connections and thousands of treatment facilities and appurtenances. This enormous set-up is currently operated by more than 170,000 public water systems. Sustainability of the water supply system faces several imminent challenges such as: 1) increasing water main breaks, 2) decreasing fresh water resources, 3) untraceable non-revenue water use, and 4) increasing water demands. However, current water supply management practices are not capable of providing fundamental solutions to the issues identified above. Big Data is a new technical concept to collect massive amounts of relevant data from sensors installed to monitor structural condition, usage, and system performance. This Big Data concept can be realized by deploying Internet of Things (IoT) technology throughout the water supply infrastructure and consumers’ usage. This paper presents a schematic development of IoT application for Big Data collection through a myriad of water clients. The scheme consists of downstream and upstream data collection using Wireless Sensor Network (WSN) technologies connecting to IoT. Downstream data shall provide water usage and performance data to clients and upstream data is similar to traditional SCADA and Automated Meter Reading (AMR) systems. Ultimately, all data will be converged to build a Big Data collection system where data mining identifies 1) local and system performances including pressure and flow, 2) non-revenue and illegitimate water consumption, and 3) locations and quantity of water breaks and water losses. The goal of this development is to enable both utilities and consumers to proactively manage their water usage and achieve higher levels of sustainability in water supply.