Municipal wastewater operations are often the largest energy expense in a community, equating to about $2 billion in annual electric costs. Inaccurate system design and configuration can contribute to excessive energy consumption and lead to inefficient contaminant removal, and the need for costly retrofit.
Finding a potential solution to the issue to help provide significant environmental, economic, and social benefits to communities has been a driving force for Assistant Professor Haochen Li.
Li’s work was recently acknowledged by the American Society of Civil Engineers (ASCE) Environmental and Water Resources Institute. He was awarded the 2023 Rudolph Hering Medal, which recognizes outstanding research that contribute to the advancement of the environmental branch of the engineering profession.
Li and co-author John Sansalone from University of Florida were honored for the paper “Benchmarking Reynolds-Averaged Navier-Stokes Turbulence Models for Water Clarification Systems,” which was published in the Journal of Environmental Engineering in 2021.
The Hering Medal is an annual prize that has been awarded since 1924 and previous winners include Ross McKinney (1964), who made the field’s first complete model for biological wastewater treatment. Li received a bronze medal and a cash prize of $1,500.
“Receiving the Medal was a moment of quiet reflection more than anything,” Li said. “It was a pause to acknowledge the journey, the many hands that contributed to the work, and the incremental steps that lead to broader discoveries.”
Li doesn’t know who nominated the paper for the award, a mystery that makes it even more meaningful.
“Knowing that someone I haven’t met was so impacted by our work that they nominated our paper for an award is an incredibly humbling and gratifying experience,” Li said. “It serves as a powerful reminder of the reach and impact that scholarly work can have.”
Establishing a New Standard
Reynolds-averaged Navier-Stokes (RANS) turbulence models are often used in computational fluid dynamic (CFD) simulations. But their accuracy for water and wastewater treatment systems such as oxidation ditches and clarification basins are often assumed and less examined.
In the last two decades, advancement of CFD modeling has enabled engineers to evaluate and improve urban water infrastructure designs (for potable water, stormwater, and wastewater) prior to construction. However, robust, and efficient simulation of turbulent flow and coupled pollutant transport remains a major challenge. High-fidelity simulations like large-eddy simulations (LES) can yield higher accuracy, but they are significantly more computationally expensive methods compared to RANS models.
Li and Sansalone’s study, which received funding from the U.S. Geological Survey via Water Resources Institute in ESSIE at the University of Florida, assess the predictive capability of RANS model with high-fidelity LES results and laser Doppler anemometry.
“I had observed discrepancies between RANS simulations and experimental data in certain turbulent flow structure, even in simple system geometry,” Li said. “These discrepancies highlighted some limitations of RANS models in capturing fundamental flow phenomena, which led me to explore more about the underlying assumptions, the range of their applicability, and potential improvements or alternatives to enhance their predictive capabilities.”
The study used a 30-year-old database of values gathered from physical tests with a bench-scale water clarification system. It considered three cases: two-sided deflector, one-sided deflector, and a system without a deflector. Overall, the LES model was “superior to the RANS turbulence models in all three cases considered.”
The results of the study were not intended to discourage the adoption of RANS models but to encourage a more deliberate approach to selecting a RANS model for water system simulations.
“I hope that the biggest impact of our benchmarking paper will be to establish a new standard for the accuracy and reliability of simulations in our field,” Li said. “By providing a comprehensive comparison of various models and identifying best practices, I aim to guide future research and applications towards more effective and efficient solutions, ultimately contributing to advancements in environmental engineering.”
UT Lab Helps Push Research Forward
Li’s high-impact research has benefited from his surroundings and the tools available in UT’s Water Infrastructure Laboratory, a multidisciplinary environmental fluid dynamics laboratory in CEE. The lab is equipped with state-of-the-art physical modeling facilities and numerical simulation platforms.
“UT offers a vibrant research environment with access to cutting-edge facilities, a collaborative community of scholars, and strong support for interdisciplinary projects,” Li said. “The university’s commitment to innovation and excellence, especially the recent AI Tennessee and Global Energy Ecosystems (GE2) initiatives aligns with my research goals, making it an ideal place for conducting high-impact research.”
Li has a paper coming out in March 2024 that will be published in Water Research, a peer-reviewed scientific journal covering research on the science and technology of water quality and its management.
Li is the first author, and the co-author is Mohamed Shatarah, a grad student in Li’s lab. They developed a composite neural network (CPNN) by combining a physics-informed neural network with a deep operator network.
They hope their new network will enable more civil/environmental engineers to perform on-demand CFD simulations. Currently, CFD is “primarily used in academic research in civil and environmental engineering” due to high computational cost and need for “specialized user skills.”
Whether Li’s latest paper receives an award or not, his greatest validation comes from his daily interactions. “The engagement with students and the broader academic community here continually inspires and challenges me to push the boundaries of my work,” Li said.
Contact
Rhiannon Potkey (865-974-0683, rpotkey@utk.edu)