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Title: Optimization of large-scale systems with model reduction
Authors: Yue, Yao
Meerbergen, Karl # ×
Issue Date: Sep-2009
Conference: Belgian-French-German Conference edition:14 location:Leuven, Belgium date:14-18 September 2009
Abstract: Numerical parameter studies of acoustic problems arising from applications such as airplane engines and insulation panels along motor ways or in houses are usually extremely expensive, since for each parameter value, an entire frequency response function needs to be computed. The computation of a single frequency response function for fixed parameter values is by itself already quite expensive.
Parameter studies are often carried out in order to choose the `optimal' values of the parameters.

The computational cost for the frequency response function has been dramatically reduced by a factor of ten or more by using model order reduction methods.
The goal of model order reduction (MOR) is to construct a low order model from the original large-scale model to solve
the original problem more efficiently.
It has been successfully applied to many different applications such as (vibro) acoustics, circuit simulation and controller design.
However, little work has been done to introduce MOR in optimization.

Our research group has recently started research on exploiting the properties of model reduction methods in optimization problems arising from acoustics.
This talk presents our first results.
Publication status: published
KU Leuven publication type: IMa
Appears in Collections:Numerical Analysis and Applied Mathematics Section
× corresponding author
# (joint) last author

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