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| Abstract: Dynamical systems of large order appear in many applications. For an efficient simulation it can become necessary to reduce the system dimension using a reliable model order reduction method in particular in a many-query context when the system is to be solved for varying parameters and input signals. Nowadays it is often required that the models include physical parameters to allow more flexibility in simulation. These parameters should be preserved in the reduced-order system; a task that motivates the development of new approaches to model order reduction referred to collectively as parametric model order reduction. In this work we compare several methods for parametric model order reduction using common benchmark problems from the literature. |
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