Research Area S
Simulation
Coordination: Prof. Dr. S. Le Borne
Efficient and reliable implementations of simulation processes require a thorough understanding of techniques combining adaptive discretization & approximation efforts together with advanced solution procedures on the one hand, and on the other hand, of current and future high-performance computing (HPC) aspects.
The projects in this research area develop novel adaption strategies for kernel-based approximations (S1), simulation strategies for large-scale inverse problems (S3), and develop tailored preconditioning techniques for large-scale fluid dynamic applications (S2).
An efficient use of these technologies usually requires not only a mere re-editing of software parts, but necessitates re-thinking of the employed mathematical approaches and algorithms.
PhD-Projects:
S1 (Adaptive Kernels) - Adaptive kernel-based approaches for fluid flow simulations
S2 (Preconditioning) - Preconditioners for RBF-FD discretized fluid flow problems
S2.2 (Preconditioning) - Low-rank correction for preconditioners in fluid flow problems
S3 (Blood Flow) - Blood Flow modeling and estimation by magnetic particle imaging
S4 (Structure-preserving discretization) - Preserving structures of transport-dominated phenomena discretely