@article {Komori:2017:0736-2935:4572,
title = "Parameter Identification for Vibro-Acoustic Systems by using Parametric Model Order Reduction",
journal = "INTER-NOISE and NOISE-CON Congress and Conference Proceedings",
parent_itemid = "infobike://ince/incecp",
publishercode ="ince",
year = "2017",
volume = "255",
number = "3",
publication date ="2017-12-07T00:00:00",
pages = "4572-4579",
itemtype = "ARTICLE",
issn = "0736-2935",
url = "https://ince.publisher.ingentaconnect.com/content/ince/incecp/2017/00000255/00000003/art00066",
author = "Komori, Kengo and Van De Walle, Axel and Toi, Takeshi and Desmet, Wim",
abstract = "Numerical simulations, such as the finite element method, have been recently used to calculate and predict noise and vibration behavior. Unfortunately, finite element models have a discrepancy as compared to real systems because of erroneous boundary conditions or model parameters.
In order to obtain accurate predictions, a good correspondence between the finite element model and real system are required. In this paper, model updating is performed for vibro-acoustic system by using a measured sound pressure. However, finite element models for vibro-acoustic simulations
typically induce a high computational cost. In order to mitigate these computational cost, model order reduction is proposed to reduce the number of degrees of freedom while maintaining a desired accuracy. Since parameter dependency has to be taken into account during model updating, parametric
model order reduction is performed. The resulting parametric reduced order model preserves the accuracy of the full order model and is used to identify several vibro-acoustic parameters through an inverse optimization procedure.",
}