Research Interests
My fields of research include multi-physics simulation, fluid-solid interaction, reduced order model and data analysis, applications of machine learning on engineering problems.
Selected Projects
Vascular Model Processing
Preprocessing steps for the blood flow simulation. Mesh file is downloaded from open-source database Vascular Model Repository.
Wave Interactions with Floating Structures Including Moorings
The floating structures on the water surface under the impact of waves can be studied by numerical simulations, and the stability of the structures can be studied by roll, pitch, yaw, etc.
Fluid-solid Coupling by Neural Networks
Complex physical process can be learned and replaced by machine learning model. Use the IB-PINN machine learning model to conduct fluid–solid coupling is shown to be fast, reliable, and accurate.
Wall Shear Stress Analysis for Blood Vessel’s Inner Surface
To analyze the WSS in complex fluids with cell suspensions, numerical simulations of blood flows in simple straight channels were conducted, where the fluid-solid interactions were simulated by immersed boundary-lattice Boltzmann method. The spatiotemporal dynamics of WSS were analyzed using dynamic mode decomposition (DMD), which is a technique that can extract the low-rank spatiotemporal features from complex fluids.
Dynamic Mode Decomposition on Covid-19 Data
Understanding the dynamics and spreading of COVID-19 is important in disease control and mitigation.
Investigation on Hydrodynamics of Fish Swimming
The fish swimming is achieved by immersed boundary-lattice Boltzmann method based on opensource software Palabos, and dynamic mode decomposition is applied on the simulation results.