Simulation Methods
Unified workflows across particle and grid methods for multiphysics engineering design.
CAM Lab advances reliable computational multiphysics to solve real engineering problems in fluids, structures, and particulate systems.
Research Keywords
SPH FEM FVM DEM Fluid-Structure Interaction Physics-Informed AI Graph Neural Networks Porous Microstructure Analysis Digital Twin
Highlights
Industry Relevance
Research topics are aligned with real industrial systems and digital engineering pipelines.
AI + Mechanics
Data-driven and physics-informed models accelerate prediction and optimization tasks.
Microstructure & Multiscale
Bridging pore-scale physics and macro-scale performance through digital microstructure modeling and upscaling frameworks.
Latest News & Publications
Latest News
- Homepage Renewal (2026-01-15)
- CAM Lab Presented at 2025 Autumn Meeting of the Korea Society of Rheology (2025-11-13)
Latest Publications
- Kim JS, Park HJ*. Comparative Study of Simulation Methods for the Digital Twin of a Chemical Stirrer (2025) - DOI
- Kim HJ, Kim J, Park HJ*. Graph Neural Network Modeling of Free-Surface Flows in Non-Newtonian Power-Law Fluids (2025) - DOI
- Choi S, Park HJ, Kim J*. A Review of Non-Newtonian Flows Around a Sphere (2025) - DOI
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