Experimental and numerical study reveals superior acoustic prediction using the Johnson–Champoux–Allard model for polyurethane foams, suggesting robust frameworks for noise control design.
Polyurethane foams (PUFs) are extensively used in acoustic applications due to their porous structure and high sound energy dissipation, making them ideal for noise control. In this context, this study presents an experimental and numerical analysis of homogeneous and multilayer open-cell PUF systems, evaluating their acoustic performance over a wide frequency range. Three modelling approaches were assessed: the empirical Delany–Bazley (DB) model, the modified DB–Miki model and the semi-phenomenological Johnson–Champoux–Allard (JCA) model. To complement these models, an inverse parameter identification procedure in MATLAB was employed to extract key non-acoustic parameters: porosity, tortuosity, airflow resistivity, and viscous characteristic length, directly from measured sound absorption data, enabling a more physically meaningful characterization. Results indicate that DB and DB–Miki models provide reasonable predictions at mid-range frequencies but show limitations at low frequencies. Conversely, the JCA model achieves higher predictive accuracy across the full spectrum, effectively capturing complex dissipation phenomena in multilayer structures. These findings highlight the value of combining inverse parameter estimation with suitable acoustic models to reliably characterize porous materials, offering a robust approach for designing PUF-based acoustic solutions.
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Tayari et al. (2026) studied this question.
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