Indirect Characterization of Fibrous Materials Using In-Situ Acoustic Impedance and JCAL-Based Parameter Optimization

This paper presents a novel indirect methodology for the characterization of fibrous sound-absorbing materials based on in-situ acoustic impedance measurements. The proposed approach relies on the combined measurement of sound pressure and particle velocity to estimate the surface acoustic impedance of the sample under test, enabling material characterization directly in realistic measurement conditions. An inverse identification framework based on the Johnson-Champoux-Allard-Lafarge (JCAL) model is employed to optimize the material parameters that exhibit the strongest influence on the acoustic response, namely airflow resistivity, effective sample thickness, and viscous characteristic length.