Experimental Study and Regression Modeling of Sound Absorption Coefficient for Wood Panels.

This study presents a predictive model for estimating the sound absorption coefficient of perforated and non-perforated wooden panels, based on experimental data. Measurements were conducted on four wood species: fir wood (Abies alba), pine wood (Pinus sylvestris), pedunculate oak (Quercus robur), and sessile oak (Quercus petraea) in three panel thicknesses (11 mm, 18 mm and 25 mm), with perforation ratios of 0%, 10%, and 20%. The normal-incidence absorption coefficient was measured using the impedance tube method in accordance with ISO 10534-2. Measurements were performed in a 100 mm impedance tube, selected to match the specimen dimensions; therefore, the analysis is limited to the valid plane-wave frequency range of this tube, between 250 and 1600 Hz. Previous studies have shown that both panel thickness and perforation ratio significantly influence mid- and high-frequency absorption. Our results confirm that increased panel thickness and perforation enhance absorption, consistent with findings reported for micro-perforated and porous wood panels. Based on the measured values, we developed first-order regression functions linking the absorption coefficient to material density, thickness, and perforation percentage. The resulting equations allow reverse estimation of one or more physical parameters to meet target acoustic performance requirements. This data-driven approach provides a practical tool for designing wooden absorbers with predictable behavior and complements existing analytical models for acoustic optimization.