Collaborative research: enabling safe and efficient restoration of drinking water systems through multiphase flow modeling and control

The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded The University of Texas at San Antonio $225,569 on October 1, 2026, under the Engineering program (CFDA 47.041) to develop computational methods for safe and efficient restoration of drinking water systems following repairs and construction.

The project will create physics-informed models that simulate multiphase air-water flow during transmission main and distribution network refilling, capturing water motion, air compression, air release, and pressure dynamics without computationally intensive multiphase simulations. The work includes calibrating models using physics-informed neural differential equations that combine conservation-law models with sensor data, developing uncertainty-aware state estimation methods to infer unmeasured pressures, flows, air volumes, and filling states from limited sensor measurements, and formulating control strategies to guide safe restoration of service. The research addresses hazards created when trapped air is compressed and displaced during main refilling, producing pressure surges that damage pipes, increase water loss, and prolong service interruption. Slower filling reduces these risks but delays service restoration to homes, businesses, hospitals, and essential facilities. The project integrates research into university courses, trains students in water infrastructure and data-enabled engineering, and transfers technology through collaborations with municipal utilities and laboratory testbeds.

Performance occurs at San Antonio, Texas 78249 with a period of performance from October 1, 2026, through September 30, 2029.

Abstract

Drinking water service is expected to be restored quickly after water mains are repaired, new lines are installed, or communities expand. Yet refilling an empty water main can create hidden hazards. As water enters the pipe, trapped air is compressed and displaced, producing damaging pressure surges that can cause additional pipe damage, water loss, longer service interruptions, and increased repair costs. Filling the system more slowly reduces these risks but delays the restoration of water service to homes, businesses, hospitals, and other essential facilities. The research funded by this award will develop new scientific understanding and practical engineering tools to help water utilities restore service more safely, reliably, and efficiently following repairs and construction. The project will also support education and workforce development by integrating research into university courses, training students in water infrastructure and data-enabled engineering, while promoting technology transfer through collaborations with municipal utilities and laboratory testbeds. The project will develop computational methods for modeling, monitoring, and controlling multiphase air-water flow during the refilling of transmission mains and water distribution networks. The research will formulate computationally efficient models that capture the dominant physical mechanisms governing water motion, air compression, air release, and pressure dynamics without requiring computationally intensive multiphase flow simulations. These models will be calibrated using physics-informed neural differential equations that combine conservation-law models with sensor data. The project will further develop uncertainty-aware state estimation methods to infer unmeasured pressures, flows, air volumes, and filling states from limited sensor measurements, and will integrate these estimates into optimization-based control algorithms for pumps, valves, hydrants, and air-release devices. The methods will be validated through laboratory experiments, realistic network testbeds, and field-informed case studies conducted in collaboration with water utilities in texas and alabama. The expected outcome is a general computational framework for modeling, monitoring, and regulating multiphase flow during water system priming. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.