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Energy density field approach for low- and medium-frequency vibroacoustic analysis of a car body using a probabilistic computational model

Authors :
Morad Kassem
Christian Soize
Laurent Gagliardini
Soize, Christian
PSA Peugeot Citroen
PSA Peugeot Citroën (PSA)
Laboratoire de Modélisation et Simulation Multi Echelle (MSME)
Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Paris-Est Marne-la-Vallée (UPEM)
Université Paris-Est Marne-la-Vallée (UPEM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)
Source :
Proceedings of SAE 2009 world congress, 2009., Proceedings of SAE 2009 world congress, 2009., Apr 2009, Detroit, Michigan, United States. pp.Pages: 09NVC-0248-1 to 09NVC-0248-5, HAL
Publication Year :
2009
Publisher :
HAL CCSD, 2009.

Abstract

International audience; A new energy-density field approach is proposed for low- and medium-frequency vibroacoustic analysis of complex industrial structures, using a probabilistic computational model. The observed structure is composed of a trimmed body coupled and its internal cavity. The objective of this paper is to take advantage of some statistical properties of the frequency response functions to build a simplified vibroacoustic model. In this approach, the Frequency Response Functions (FRF) of the vibroacoustic system are expressed as the product of a dimensionless "smooth" matrix and local mobilities or impedances, depending on their type (acoustical, vibratory or vibroacoustic). The stochastic computational model of the vibroacoustic system is obtained from the reduced mean computational model and is using a nonparametric probabilistic approach.

Details

Language :
English
Database :
OpenAIRE
Journal :
Proceedings of SAE 2009 world congress, 2009., Proceedings of SAE 2009 world congress, 2009., Apr 2009, Detroit, Michigan, United States. pp.Pages: 09NVC-0248-1 to 09NVC-0248-5, HAL
Accession number :
edsair.doi.dedup.....a73ebc2e7a4d6dccbca7757ad02c740c