Model Order Reduction

Model Order Reduction

In order to get a deep insight into the underlying process, dynamics, structure or devices, modeling and simulation are unavoidable in many research and application fields. The resulting mathematical models are usually in the form of partial differential equations. To simulate such models, spatial (-time) discretization is necessary, which results in large-scale, complex systems with enormous number of equations. The simulation becomes time-consuming because of the large scale and complexity of the systems.

Developed from well-established mathematical theories and robust numerical algorithms, model order reduction (MOR) has been recognized as an efficient tool for fast simulation.

Projects

Model Order Reduction for Battery Models

Funded by: MPI
Funding period: since 12.2019
Contact: Karim Cherifi, Lihong Feng
Partners: OvGU, Technische Hochschule Bingen
Funded by: MPI
Funding period: since 04.2017
Contact: Sridhar Chellappa, Lihong Feng


Funded by: MPI
Funding period: since 11.2019
Contact: Jennifer Przybilla, Peter Benner

more
Partners: Prof. Dr. Peter Benner (MPI Magdeburg, OVGU), Prof. Dr. Sebastian Sager (OVGU), Prof. Dr. Kai Sundermacher MPI Magdeburg, OVGU)Prof. Dr. Martin Stoll (TU Chemnitz)
Industrial partners:  AVACON und BASF
Funded by: BMBF
Contact: Peter Benner, Lihong Feng, Shaima Monem
more
Funded by: MPI
Funding period: since 07/2019

Contact: Carmen Gräßle, Peter Benner 

more

Concluded Projects

Partners: OvGU, Technische Hochschule Bingen, MPI Leipzig
Funded by:
MPI/IMPRS
Funding period:
2014-2019
Contact
Cleophas Kweyu


Go to Editor View