Parametric Model Order Reduction in Elastic Multibody Systems

Parameter preserving model order reduction for efficient simulation and optimization of elastic structures.

Project description

For many applications in elastic multibody dynamics, the mass-, stiffness-, and input matrix of the elastic bodies have to be modelled parametrically in order to obtain meaningful models. Classical model order reduction methods cannot be applied for such kind of problems since they do not preserve the parameter dependency in the reduced models. Therefore, the aim of this research project is the development and the investigation of parameric model order reduction methods which preserve the parameter dependency in the reduced order model explicitly. In the following some applications of parametric model order reduction will be presented.


Shape optimzation of a cantilever beam.

Structural Optimization with Reduced Order Models

The increasing demand for energy and resources efficient technical products makes the use of lightweight structures necessary. Usually, the Finite-Element-Method is used for modelling complex components. Afterwards these models can be used for optimization to achieve the desired weight reduction. However, the numerical effort for solving these optimization problems may become tremendous for fine discretized models making the optimization problems unsolvable in acceptable computation times. The goal of this research project is therefore the development of methods for parametric model order reduction for structural and shape optimization problems to enable efficient solutions to these kinds of problems.

Workflow for parametric model reduction with interpolation of local reduced system matrices


The research project is granted by the German Research Foundation (German: Deutsche Forschungsgemeinschaft): 


This image shows Peter Eberhard

Peter Eberhard

Prof. Dr.-Ing. Prof. E.h.
To the top of the page