The transfer of information between non-matching meshes is an important ingredient for coupled multi-physics simulations. For most coupled problems information, such as displacements or stresses, has to be exchanged between, two different meshes. As an example consider fluid-structure interaction (FSI) problem, where information has to be transferred between a fluid and an elastic body (the "S"tructure in FSI).
As it turns out, the design of a stable transfer operator between, e.g., the fluid mesh and the structure mesh, is far from trivial, as unwanted effects such as spurious modes can arise. As a consequence, standard interpolation techniques are often not sufficient. We discuss the difficulties related to straight forward approaches as interpolation and motivate and present as a stable alternative, the so called variational transfer.
Prof. Rolf Krause's research focuses on numerical simulation, machine learning, optimization, and data driven approaches. The complexity of real world applications constitutes a challenge for model and data based prediction, turning the development of models and of solution methods into a challenging task. In addition to a well balanced combination of methodological and mathematical knowledge, it also requires experience in dealing with subtle aspects of the implementation.