Water Infrastructure Laboratory

University of Tennessee, Knoxville

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Our Mission

To advance multiphysics and multiphase flow prediction in natural and built water infrastructures, and to enable robust and efficient NexGen water infrastructure design, optimization, and retrofit.

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Our Research

(1) leverages the high-performance computing (HPC) and high-order numerical method to elucidate the underlying turbulence physics and physicochemical fate dynamics of particulate matter, pathogens, and chemicals in fluid systems; (2) develops and benchmarks a wide range of open-source computational fluid dynamics (CFD) tool for water infrastructure simulation, optimization, uncertainty quantification and vulnerability assessment; (3) integrates machine learning (ML) and CFD for robust and efficient water infrastructure optimization and retrofit, and create CFD-ML augmented frameworks for engineering practices and environmental regulations.

Free-surface turbulent flows over pile. VOF+DS-LES, FVM 2nd order, 40 million DOF

Turbulence structure in a hydrodynamic separator. HRT-LES, SEM 15th order, 60 million DOF

Elution dynamics in stormwater clarification basins. DA-LES, FVM 3rd order, 4 million DOF

Treatment dyanmics of clarification-filtration system under storm event. VOF+URANS+LPT, FVM 2nd order, AMR

Phosphate transport and fate in a volumetric-adsorptive reactor. interAdsFoam, VOF+URANS, FVM 2nd order, Non-equilibrium adsorption

Particulate matter filtration in porous media. Pore-scale LPT, FVM 2nd order, 10 million DOF

Raw PIV image of turbulent flow in HS. 12 MP, 50 Hz, 1 ms

Vertical flow velocity around UAV. 12 MP, 90 Hz, 1 ms

Recent Publications

Our Team

Haochen Li
Haochen Li, PhD

PhD in Environmental Engineering, MS in Mechanical Engineering and Civil Engineering, University of Florida; BS in Coastal Engineering, Hohai University.
Faculty Page | Google Scholar

Kai Liu
Kai Liu, PhD

Researcher in AI-empowered reactive multiphase flow. PhD and MS in Mechanical Engineering, University of Florida; BS in Energy, Power System & Automation, Xi'an Jiaotong University
Google Scholar

Mohamed Shatarah
Mohamed Shatarah

BS in Mechanical Engineering, Alexandria University. Researcher in Physics-Informed Deep Learning and CFD with expertise in CFD applications, including solar energy and HVAC.
Google Scholar

Ahmed Abdelmeguid
Ahmed Abdelmeguid

BS in Mechanical Engineering, Alexandria University. Researcher in AI-augmented sensing and CFD with experience in hydrogen production, electrolysis, and advanced manufacturing.

Jeffrey Lind III
Jeffrey Lind III

Researcher in AI, LLM, and CFD | University of Colorado Boulder 26' Master's of Science in Computer Science | Founder of Shigeo Technologies
Personal Page

Muhyminul Islam
Muhyminul Islam

BS in Water Resources Engineering, Bangladesh University of Engineering and Technology. Researcher in Deep Learning, Urban Hydrology, and Renewable Energy.

Past Members

Water Infrastructure Laboratory [Ψ Lab]

Ψ Lab is a multidisciplinary environmental fluid dynamics laboratory in the Department of Civil and Environmental Engineering at University of Tennessee, Knoxville. Ψ Lab is equipped with state-of-the-art physical modeling facilities and numerical simulation platforms. Ψ Lab aims to transform urban water infrastructure planning and design through developing novel computational fluid dynamics (CFD) and artificial intelligence (AI) tools.

Contact Information

325 John D. Tickle Engineering Building
851 Neyland Drive
Knoxville, TN 37996-2313, U.S.

Tel: +1 865-974-7731
Email: hli111@utk.edu