Physical and Numerical Modelling
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The team develops numerical models to solve complex multi-physics problems. The main design requirement is that the resulting algorithms are efficient on massively hybrid supercomputers, for both distributed and shared memory systems.
Objectives
Why the emphasis on numerical modelling? It's essential to meet the dual requirements of accuracy in problem description and efficiency in parallel system implementation. Choosing between accuracy, complexity, and efficiency is crucial in modelling physical phenomena, especially when dealing with massively parallel supercomputers. Therefore, the group aims to strike a balance between quality and cost, providing transversal and application-based algorithms tailored to solve a wide array of complex physical problems.
Their objectives encompass a range of areas, including:
- Algebraic solvers (pipelined CG, Deflated CG, GMRES) and preconditioners (RAS, Gauss-Seidel, Linelet, coarse space corrections)
- Domain decomposition tools (Chimera, multi domain coupling, element search)
- Adaptive mesh refinement
- Stabilization strategies (VMS, shock capturing)
- Multiphysics coupling (FSI, Fluid-particle, Fluid-rigid body interactions)