Enhancing the sound absorption performance of porous metals using tomography images

Abstract

Commercially available porous metals are known to provide useful sound absorption, but it may be possible to modify their structures to improve their acoustical properties. Images from high-resolution X-ray computer tomography have been used to make pore-level characterization of Inconel, Recemat and Porvair foams. Based on these characterisations, flow simulations have been used to deduce parameters that determine the acoustical properties according to the Johnson-Champoux-Allard (JCA) and Delany-Bazley-Miki (DBM) models. While the DBM model enables a good agreement with measured normal incidence absorption coefficients for glass fiber materials, the JCA model enables a better agreement with data for metallic foams. The predicted sound absorption spectra were observed to depend mainly on the permeability of the porous medium being better for structures with the smallest openings and extremely poor for those with larger connectivity. It is shown that dilating the skeletal frame i.e. increasing the width of the ‘struts’ in a metallic foam should lead to more efficient sound absorption. It is the hope that this approach would lend itself well to use in the design of enhanced soundproofing porous metals.