Characterization of fibrous media transport parameters from multi-compression-ratio measurements of normal incidence sound absorption

This study presents a novel approach for estimating the transport parameters that characterize the acoustic behavior of fibrous materials using the Johnson-Champoux-Allard equivalent fluid model. We propose an inversion technique, based on an optimization algorithm, to fit the Johnson-Champoux-Allard model's predictions of normal incidence sound absorption coefficient to multi-compression-ratio experimental data. Experimental measurements using the two-microphone technique within an impedance tube are conducted on fibrous material samples tested at various compression ratios. Optimization is performed using both a non-linear programming solver and a genetic algorithm. Validation of the proposed method shows good agreement with well-established techniques and demonstrates its effectiveness across a range of fibrous materials. A sensitivity analysis emphasizes the importance of selecting appropriate boundaries for the search space in the optimization process. To enhance the robustness of optimization, a two-step iterative procedure is proposed. This straightforward methodology offers a robust and reliable framework for characterizing the transport properties of fibrous materials. Its ease of implementation and accuracy make it a valuable tool for enhancing material design and optimization in acoustic engineering.