Core Research Areas

Adaptivity for Optimization (AO)

Adaptive techniques are widely used for solving problems involving PDEs, an there is large agreement that adaptivity in discretizing PDEs is indispensable constructing efficient algorithms. The study of adaptive techniques for optimization problems with PDEs is a highly active research area, which is reflected in several dissertation topics.

Non-Smoothness in Function Spaces (NS)

Many application problems lead to mathematical models with inherent nonsmooth behavior. This may result from physics itself or from its mathematical formalization, as for instance in the case of inequality constraints. The infinite-dimensional nature of all problems involving PDEs requires a proper treatment of different kinds of nonsmoothness in (infinite-dimensional) function spaces. This approach allows to identify and analyze the core structure of the problems and to exploit them for the construction of efficient algorithms.

Interfaces: Separating and Coupling Structures (IS)

Complex models with different physical phenomena on different spatial domains call for the study of transfer processes across interfaces separating these domains. The transfer of information across interfaces crucially influences the behavior of the system. Additionally, the physical system itself can influence the geometrical location of an interface which leads to moving or free boundary value problems. In many application settings the interface plays the role of the design variable resulting in shape optimization or shape identification problems.


TUM Mathematik Rutschen Universität der Bundeswehr München Technische Universität Graz Karl-Franzens-Universität Graz Technische Universität München
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