Research interests
Environmental hydraulics, sediment
transport, multiphase flow, CFD, machine learning applications in hydraulics modeling
The major thrust in our research is to develop and utilize novel computational models, both physics-based and data-driven, for problems in environmental hydraulics and water resource engineering in general. Complementary to computational modeling, we also do some lab experiments and analytical work.
The major thrust in our research is to develop and utilize novel computational models, both physics-based and data-driven, for problems in environmental hydraulics and water resource engineering in general. Complementary to computational modeling, we also do some lab experiments and analytical work.
Numerical models and tools
- OpenFOAM: Our major research package with multiple applications
- pyHMT2D: Python package for 2D Hydraulic Modeling Tools
- dl4HM: Deep-learning for Hydraulics Modeling, a python package for building data-driven machine learning models.
- HydroSed2D: Our open source 2D depth-averaged hydrodynamic model with sedimen transport.
- EFDC: Environmental Fluid Dynamics Code, we used it for the Chicago River, IL, and Clinton Lake, IL.
Experimental work
- Scour around porous hydraulic structures
- Rock weir hydraulics
- Sediment movement through synthetic turf