Improving SEA Predictions with Experimental Data

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.