Uncertainty and sensitivity analysis of non-acoustic parameters on acoustic characteristics prediction models for porous foam materials

Porous foam materials are widely used in noise control applications. Their acoustic performance can be predicted by acoustic models composed of non-acoustic parameters such as flow resistivity, porosity, tortuosity, viscosity, and characteristic length. However, the influence of these parameters on model outputs varies across different frequency ranges. Therefore, when using a single model for predictions across the entire frequency range, parameters may not fully act within the frequency range where their influence is greatest. To reduce prediction errors and improve the correlation between predicted numerical results and experimental data, uncertainty and sensitivity analyses can be conducted to determine the extent of each parameter's influence at different frequency ranges. In this study, polyurethane foam materials are investigated, and uncertainty and sensitivity analyses are performed on two acoustic models. Firstly, the uncertainty of parameters is assessed using the Monte Carlo method. Secondly, Sobol index method is employed to reveal the influence of parameters across various frequency ranges. Finally, by comparing the results of both analyses, the optimal frequency ranges for each parameter can be summarized. This provides valuable reference for enhancing the accuracy of acoustic model predictions.