Team Leader MOR

Dr. Lihong Feng
Dr. Lihong Feng
Team leader
Phone: +49 391 6110 379
Fax: +49 391 6110 453
Room: S3.12

Team members

Dr. Yao Yue
Dr. Yao Yue
Phone: +49 391 6110 433
Room: S1.08
Dr. Pawan Goyal
Dr. Pawan Goyal
Phone: +49 391 6110 386
Room: S3.09
Cleophas Kweyu
Cleophas Kweyu
Phone: +49 391 6110 464
Room: S2.09
M.Sc. Sridhar Chellappa
M.Sc. Sridhar Chellappa
Phone: +49 391 6110 384
Room: S3.09
Dr. Jens Saak
Dr. Jens Saak
Team leader
Phone: +49 391 6110 216
Fax: +49 391 6110 453
Room: S2.20
Dr. Sara Grundel
Dr. Sara Grundel
Team leader
Phone: +49 391 6110 475
Room: S2.11
Dr. Christian Himpe
Dr. Christian Himpe
Phone: +49 391 6110 364
Room: S2.19
Dr. Igor Pontes Duff Pereira
Phone: +49 391 6110 474
Room: S2.14
Dr. Patrick Kürschner
Dr. Patrick Kürschner
Phone: +49 391 6110 424
Room: S2.14
M. Sc. Petar Mlinarić
M. Sc. Petar Mlinarić
Phone: +49 391 6110 346
Room: S1.05
Manuela Hund
Manuela Hund
Phone: +49 391 6110 492
Room: S2.09
Links: ORCID
Steffen Werner, M.Sc.
Steffen Werner, M.Sc.
Phone: +49 391 6110 484
Room: S2.09
Links: ORCID

Model Order Reduction

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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. Using model order reduction, small systems of far less number of equations (reduced models) are derived, and can substitute the original large-scale systems in simulation, optimization, control, and other multi-query tasks. As a result, these analysis can be sped up by several orders of magnitude.  

Projects

Since: 01.2017Contact: Yao YueFunded by: MPI

Interpolatory and Data-driven Parametric Model Order Reduction

Since: 01.2017
Contact
: Yao Yue
Funded by: MPI
Since: 04.2017Contact: Sridhar Chellappa, Lihong FengFunded by: MPIPartner: OvGU, Technische Hochschule Bingen

Adaptive Model Order Reduction for Parametric Nonlinear Systems

Since: 04.2017
Contact:
Sridhar Chellappa, Lihong Feng
Funded by: MPI
Partner: OvGU, Technische Hochschule Bingen
Scine: 09.2014Contact: Cleophas M. Kweyu, Sridhar ChellappaFunded by: MPIPartner: MPI/MSD, Technische Hochschule Bingen

MOR in Process engineering, molecular simulations

Scine: 09.2014
Contact
: Cleophas M. Kweyu, Sridhar Chellappa
Funded by: MPI
Partner: MPI/MSD, Technische Hochschule Bingen

Concluded Projects

 
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