Transient simulations in water networks

Course Leaders

Lu Xing, Data Scientist, Xylem Inc . Send e-mail.

Lina Sela, Assistant Professor, Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin . Send e-mail.

Course instructors

Lu Xing

Data Scientist, Xylem Inc

Lu Xing is currently a data scientist in the Decision Intelligence Solutions Group at Xylem Inc. Before Xylem, she was a postdoctoral researcher in the Department of Civil, Architectural, and Environmental Engineering at the University of Texas at Austin. She holds a Ph.D. in Civil Engineering (2021), an M.S. in Statistics (2020), an M.S. in Ocean Engineering (2018) from the University of Texas at Austin, and a B.S. in Ocean Engineering (2016) from Tianjin University, China. Lu is passionate about integrating hydraulic modeling, machine learning, and data analysis to enable more informed decision making in water sector. Her work focuses on leveraging numerical modeling, algorithm development, remote sensing, and artificial intelligence to promote the advancement of intelligent and resilient water infrastructure systems. Major areas of interest include the modeling and control of water distribution systems, Internet of Things (IoT) for water system management, and digital twins. She is the developer of an open-source package – Transient Simulation in water Networks (TSNet).

Lina Sela

Assistant Professor, Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin

Lina Sela is an Assistant Professor in Environmental Water Resources Engineering, in the Civil, Architectural and Environment Engineering department at the University of Texas at Austin. Dr. Sela’s research focuses on improving the efficiency of water distribution systems facing challenges related to finite water sources, aging infrastructure, and population growth. Her work relies on integrating the increasingly available digital information from distributed sensing devices with physical-based models to improve operations and management of urban water systems, including hydraulic modeling, state estimation, leak detection, and pipe failure prediction. Her research focuses on developing advanced models for managing water networks that are driven towards practical implementation to improve decision capabilities for attaining equitable and accountable water management and promote engineering practice through collaboration between academic research and public utilities. She is a recipient of the NSF CAREER award and is an Associate Editor in the Journal of Water Resources Planning and Management.

Short Description

Modeling transient flow conditions in water distribution networks has shown increasing usability for various applications, including burst and leak detection, sensor placement, model calibration, and risk assessment.  However, working with transients can be challenging, as it requires extensive interaction with simulation software. Transient Simulations in water Networks (TSNet, an open source Python package, was developed by the University of Texas at Austin to facilitate the integration of transient modeling in these simulation-based applications. TSNet adopts the Method of Characteristics (MOC) for solving the system of partial differential equations governing the unsteady hydraulics. It allows users to simulate various conditions including operational changes in valves and pumps, as well as background leaks and pipe bursts.

In this workshop, we will cover the TSNet modeling framework, and use  a case study to demonstrate how to use TSnet to: (1) create transient models based on EPANET INP files, (2) simulate transients generated by operating valves and pumps, (3) add disruptive events including pipe bursts and leaks, (4) include simple surge protection devices, (5) choose between steady, quasi-steady, and unsteady friction models, (6) perform transient simulation using the MOC technique, (7) and visualize results.

Current limitations and future directions will be discussed.

At the end of the workshops, participants are expected to be able to set up simple transient models, execute transient simulation, vary system parameters to explore system response, and extract and analyze results.

All the material, including codes, networks, and documentation, will be available electronically to the participants.

Target Audience

Graduate students, early career researchers, and practitioners that are familiar with hydraulic modeling, including software for steady state and extended period hydraulic modeling, such as EPANET. Beginners level of programming experience with Python and familiarity with WNTR is preferred but not necessary.