Team Leader MOR

Dr. Lihong Feng
Dr. Lihong Feng
Phone: +49 391 6110 379
Fax: +49 391 6110 453

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. Using model order reduction, small systems of far less number of equations (reduced models) are derived, and can substitute the original large-scale systems for simulation. As a result, the simulation can be sped up by several orders of magnitude.  

The technique of model order reduction (MOR) has been successfully applied in the communities of mechanical engineering, fluid dynamics, control, circuit simulation, microelectromechanical systems (MEMS) simulation, uncertainty quantification, etc. for decades. The robustness of MOR has been demonstrated in all application areas above. In the CSC group, with wide and successful cooperation with international scientist, novel MOR methods, algorithms and software have been developed and are still being investigated for the above applications. More results for MOR especially focusing on nonlinear and parametrized systems are being expected in the near future.  

Application Driven Research

Methodological Research

 
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