Autumn School on Future Developments in Model Order Reduction location:Terschelling date:21-25 September 2009
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. 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. We have tried to use two MOR methods in optimization: SOAR and PIMTAP. SOAR does MOR on one parameter, while PIMTAP does MOR on multiple parameters. We first compare SOAR and PIMTAP in accuracy and performance. Then, we analyze the feasibility of derivative computation via reduced model and how to combine MOR with optimization algorithms. Numerical results show that using MOR in optimization could drastically reduce the optimization time.