My Account Log in

1 option

Improving SEA Predictions with Experimental Data Gulfstream Aerospace Corporation

SAE Technical Papers (1906-current) Available online

View online
Format:
Conference/Event
Author/Creator:
Wang, Wang, author.
Contributor:
Maxon, John
Conference Name:
SAE 2011 Noise and Vibration Conference and Exhibition (2011-05-16 : Grand Rapids, Michigan, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 2011
Summary:
Statistical Energy Analysis (SEA) has been used widely by industry and academia for more than 20 years to predict the mid-to-high frequency range behavior of complex acoustic systems. At Gulfstream Aerospace Corporation (GAC), SEA models have been developed to predict the interior cabin noise levels of completed Gulfstream aircraft. These models are also used for acoustic evaluations of design changes prior to implementation as well as a diagnostic tool for investigating noise and vibration issues. Throughout the development of the SEA models, extensive experimental testing in GAC's Acoustic Test Facility (ATF) was conducted on numerous aircraft components represented in the models. This paper demonstrates the importance of using experimental data to improve the accuracy of the SEA predictions by accurately adjusting the material properties and acoustic parameters of the SEA model to better match the ATF experimental data. This is particularly important for complicated SEA models with thousands of subsystems and junctions
Notes:
Vendor supplied data
Publisher Number:
2011-01-1701
Access Restriction:
Restricted for use by site license

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account