- Michael Hinze, University of Hamburg
- Kunibert G. Siebert, University of Stuttgart
- Winnifried Wollner, University of Hamburg
"Adaptivity and Model Order Reduction in PDE Constrained Optimization"
The perspectives of MOR in simulation, control and optimization of coupled PDE systems are manifold.
These
among other things include the development of reduced order models for
parametrized nonlinear PDE systems, which are valid over large
input/output domains, and the reduction of high-fidelity components in
networks.
During the last decade simulation-based MOR techniques, as balanced truncation model reduction,
proper orthogonal decomposition (POD), reduced basis methods, and adaptive finite element concepts,
like
the dual weighted residual method, became more and more important also
as solution tools for optimization problems with PDE constraints.
It is now timely to combine the recent achievements in optimization, reduced order modeling, and
adaptivity to develop reliable and robust solution tools for large-scale PDE constrained optimization
problems, and to transfer these tools to real world applications.
The
proposed minisymposium brings together researchers working actively in
the field of PDE constrained optimization utilizing reduced order
modeling techniques and scientists so far mainly involved in the
development of model order reduction techniques for complex physical
systems.
Special focus is put on exchange of ideas between these
research areas, and to enhance knowledge in model reduction techniques
combined with PDE constrained optimization in the applications.
To
achieve these goals it is intended to invite scientists working on
model reduction and/or adaptivity in the field of PDE constrained
optimization, distinguished scientists from the field of MOR
techniques, leading experts from the field of adaptive discretization
methods, as well as scientists from engineering or physical
applications.
>>>Program