A cloud-based 3D BEM framework for predicting the diffusion coefficient

The experimental measurement of the diffusion coefficient according to ISO 17497-2 is very time-consuming and requires several sample periods to evaluate the effect of diffraction lobes, an anechoic or large reflection-free volume, and far-field conditions. Wave-based BEM methods have predicted the diffusion coefficient very accurately [Hargreaves, T, Cox, T.J., Lam, YW, D’Antonio, P., (2000), “Surface diffusion coefficients for room acoustics: Free-field measures, “J. Acoust. Soc. Am. 108 (4), 1710-1720]. This work will describe a new 3D BEM, cloud-based Python Virtual Goniometer program called VIRGO, which predicts the free-field diffusion coefficient from 3D CAD files. The program accurately predicts the properties of a reference 1-dimensional hemicylinder and periodic diffraction grating lobes from a 2-dimensional hemisphere. Furthermore, 3-dimensional polar responses and normalized diffusion coefficient of additional number-theoretic and optimized profiled and curvilinear shapes will also be compared with scale model boundary-plane goniometer measurements. The results will verify that it is possible to predict the diffusion coefficients following ISO 17497-2 in.reasonable time frames without having to fabricate or 3D print scale models or full-scale samples.