Sound absorption of foam-formed softwood fibers: Characterization, modeling, prediction

In contemporary society, the urgent need to transition to building materials with low or negative carbon dioxide footprints is driven by increasing environmental concerns. Therefore, bio-based materials draw increasing attention in research literature, especially when utilized as thermal and acoustic insulation. Traditional materials predominantly used as acoustic materials, such as mineral wools, incur substantial energy consumption during production, primarily through the melting of sand. In contrast, bio-based materials offer promising alternatives to current market leaders potentially achieving negative carbon footprints due to their low embodied energy and high carbon content. When sourced from industrial by-products, these materials have the ability to store carbon in buildings for decades. It is crucial to investigate the porous structures of these bio-fibrous materials to unlock their full potential. Therefore, this study focuses on the prediction and characterization of foam-formed softwood-based fibers and their acoustic properties. By evaluating analytical models, semi-phenomenological models, and experimental measurements, the prediction of sound absorption based on fiber diameter and density is assessed. Moreover, the material synthesis process and characterization are adapted to achieve a wider range of densities while taking elastic properties into account. The findings reveal that refining a recent analytical model for natural fibers through parameter fitting to non-acoustic parameters yields improved accuracy in predicting sound absorption curves. This work lays the groundwork to create environmentally sustainable sound absorbers with carefully tailored sound absorption properties. • Hybrid JCAL analytical model refined via fitting to non-acoustic parameters for better absorption predictions. • Foam-formed softwood fiber foams tuned across 19–64 kg/m 3 ; absorption maxima shift systematically with density. • JCAL/JCA/JCAL–Biot compared to measurements; JCAL–Biot captures elastic effects in high-density samples. • Sample fitting/compression affects estimated flow resistivity and elastic resonances, highlighting setup sensitivity.