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TBL Modeling for Aircraft Interior Noise Prediction Using Statistical Energy Analysis

Journal Article
2013-01-1931
ISSN: 1946-3995, e-ISSN: 1946-4002
Published May 13, 2013 by SAE International in United States
TBL Modeling for Aircraft Interior Noise Prediction Using Statistical Energy Analysis
Sector:
Citation: Moeller, M. and Miller, T., "TBL Modeling for Aircraft Interior Noise Prediction Using Statistical Energy Analysis," SAE Int. J. Passeng. Cars - Mech. Syst. 6(2):1239-1250, 2013, https://doi.org/10.4271/2013-01-1931.
Language: English

Abstract:

The turbulent boundary layer (TBL) that forms on the outside of a commercial airplane in flight is a significant source of noise. During cruise, the TBL can be the dominant source of noise. Because it is a significant contributor to the interior noise, it is desirable to predict the noise due to the TBL. One modeling approach for the acoustic prediction is statistical energy analysis (SEA). This technique has been adopted by North American commercial airplane manufacturers. The flow over the airplane is so complex that a fully resolved pressure field required for noise predictions is not currently analytically or numerically tractable. The current practice is to idealize the flows as regional and use empirical models for the pressure distribution. Even at this level of idealization, modelers do not agree on appropriate models for the pressure distributions. A description of the wall pressure is insufficient to predict the structural response. A structural model is also required. For interior noise predictions a common assumption is that the motion of the structure is small and does not affect the boundary layer and wall pressures. Thus the boundary layer and structural modes are independent of each other. Therefore they can be solved and applied as a force to the structural model. Current aircraft models reported in the open literature are reviewed. Then a brief review of TBL modeling is presented. The application of these models to flat plate prediction is presented. The performance of the models is compared and contrasted. The effect of the choice of structural model is highlighted.