Physics-informed and graph-based models for rapid non-Newtonian free-surface flow prediction.
Period: 2026-2028 (proposed)
Sponsor: National Research Foundation of Korea (under review)
Conducted a comparative study between CFD and Smoothed Particle Hydrodynamics (SPH) for hydrodynamic performance evaluation of stirred reactors. Developed a particle-based multiphysics modeling framework to assess mixing characteristics and flow behavior, demonstrating the enhanced flexibility and scalability of SPH for digital twin applications in complex reactive systems.
Period: 2024
Sponsor: SCNU-Supported Faculty Research Project
Designed and implemented a physics-based computational modeling framework for twin-screw extrusion processes in separator manufacturing. Developed a reduced-order digital twin capable of real-time prediction of thermo-mechanical behavior, including pressure evolution, shear fields, and residence time distribution. The platform enabled data-driven process optimization and advanced digital manufacturing integration.
Period: 2022-2023
Sponsor: LG Chem (Internal R&D Project)