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The Westerville water distribution system consists of 205 miles of predominantly ductile iron and cast-iron pipe installed beginning in the 1950s. With a break rate that began a steady acceleration in 2006, the city knew it must act proactively identify and replace poor performing pipe to maintain reliability. The city chose not to rely on industry standard values for predicting pipe life because those values vary widely and lead to inaccurate pipe break predictions. Instead, the city leveraged its pipe attribute data, empirical watermain break data, and information on pipe criticality to identify its riskiest pipes. Pipe and break data were imported into the infraSOFT on-line software platform, specifically designed to predict pipe failures. The software guides users through quality control steps to verify and improve data quality. Using the Linear-Extended Yule Process with Weibull survival curves and Markov Chain modeling of the progression of pipe deterioration, infraSOFT predicts the year-by-year probability of a pipe break for every pipe. Predicted break data was coupled with consequence of failure data, which was generated for each pipe based on its size, proximity to roads, water, structures, and service to critical customers. This resulted in a quantitative understanding of risk. With a listing of pipes prioritized by risk, the city evaluated replacement investment levels and chose an affordable annual expenditure that will stabilize the break rate. Replacements projects were coordinated with other upcoming city street and utility projects to minimize disruption and costs. Implementation of proactive watermain replacement is already underway with the expectations of reduced breaks and associated impacts, providing customers with a more reliable drinking water supply. The number of breaks in the system, which were expected to more than double over the next 15 years, will remain at or near current levels for at least that long.

Our industry has become too familiar with numerous reports from a variety of reputable agencies that collectively conclude with an important message: our assets are aging and the funding gap between what is needed and what is available is growing. In the State of Michigan alone, for example, the 21st Century Infrastructure Report concludes that many of the state’s more than 1,300 community systems were built nearly a half or a full century ago. Compounding the problem is the fact that a large percentage of our municipalities are not the big, metropolitan cities that we hear in the news. Another example, North Carolina, being the 9th most populated state in the country, is home to nearly 550 water systems and nearly half of those have less than 2,000 service connections. This presentation aims to find an answer to the following question: can advanced technology help small and medium sized communities address their infrastructure challenges in a cost effective and timely manner? Several key findings from advanced statistical data mining analyses of sanitary sewer condition data will be discussed, which lends itself to a unique and simple condition evaluation procedure. The concept of artificial intelligence will be introduced, and the “face recognition” functionality be adopted to asset condition evaluation. The presentation concludes with how this approach, coupled with intelligent dashboard tools, enabled the effective condition assessment of a community’s collection system.

Transportation is one of the industries hardest hit by the COVID-19 crisis. Yet, as an essential business, transportation asset management has continued evolving during the pandemic in innovative ways. The speaker will explore how public works agencies can seize opportunities to improve emergency management, workforce agility, strategic planning, and maintenance operations in the pandemic’s aftermath.