Volume 15: Sound, Vibration and Design 2009
DOI: 10.1115/imece2009-11065
|View full text |Cite
|
Sign up to set email alerts
|

A Structural-Acoustic Finite Element Method for Predicting Automobile Vehicle Interior Road Noise

Abstract: A structural-acoustic finite element model of an automotive vehicle is developed and experimentally evaluated for predicting the structural-borne interior noise in the passenger compartment when the vehicle travels over a randomly rough road at a constant speed. The structural-acoustic model couples a structural finite element model of the vehicle with an acoustic finite element model of the passenger compartment. Measured random road profile data provides the prescribed power spectral density excitation appli… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2013
2013
2021
2021

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(1 citation statement)
references
References 0 publications
0
1
0
Order By: Relevance
“…17 (Fischer et al 2014 [44]). The structural-acoustic finite element method is often used for modeling vehicle interior noise (Sung and Nefske, 2010 [45]), but it is only valid at low frequencies. Sung and Nefske (2009) [46] then presented a new statistical regression-based energy method for early vehicle design, which is suitable for high frequencies where the Statistical Energy Analysis (SEA) is often utilized in acoustics (Gur et al, 2015 [47]).…”
Section: Noise Categorizationmentioning
confidence: 99%
“…17 (Fischer et al 2014 [44]). The structural-acoustic finite element method is often used for modeling vehicle interior noise (Sung and Nefske, 2010 [45]), but it is only valid at low frequencies. Sung and Nefske (2009) [46] then presented a new statistical regression-based energy method for early vehicle design, which is suitable for high frequencies where the Statistical Energy Analysis (SEA) is often utilized in acoustics (Gur et al, 2015 [47]).…”
Section: Noise Categorizationmentioning
confidence: 99%