Prediction of interior trim sound absorption using Statistical Energy Analysis

The study and prediction of acoustic performance of interior trim materials have always been of great interest for acoustic engineers. The aim of this study was to investigate the use of statistical energy analysis (SEA) to predict the acoustic performance of interior trim materials in term of sound absorption. To accurately predict the acoustic performance by SEA, it is important to evaluate and calculate the material physical properties such as porosity, flow resistivity, tortuosity, and viscous/thermal characteristic length of interior materials. In this study, the material physical parameters were measured and estimated using standardized test and inverse methods. Alpha cabin and impedance tube were used to measure the random and normal sound absorption coefficients respectively. The computer model based on SEA method was then validated with the experiment in order to obtain correlation between simulation and measurement. The prediction of normal sound absorptions was found to be in acceptable agreement with its corresponding test data, while prediction of random sound absorptions showed a relatively poor correlation with the test data. Moreover, poor correlation has been investigated with further analysis of the parametric data to enhance the correlation.