Uncertainty of Input Data for Wave-based Room Acoustic Simulations in Large Non-trivial Environments
Giulia Fratoni, Dario D’Orazio, Massimo Garai · 2022
In the last decades, wave-based simulation methods have been applied to an increasing number of 3D virtual rooms thanks to the scientific and computational advances in numerical models.However, there is still a lack of adequate material properties required for those simulations, in terms of accessible lists of various frequency-dependent boundary conditions.Such input parameters can be retrieved from sound absorption coefficients, exploiting the availability of several consolidated datasets typically employed in ray-tracing simulations.The present work aims at quantifying and assessing the degree of uncertainty underlying this critical step in non-trivial environments.With this purpose, parallel calibrations have been carried out on distinct case studies based on experimental data using finite-difference time-domain (FDTD) and geometrical acoustics (GA) approaches.The outcomes highlight significant discrepancies at low frequencies between the different input data for various materials, suggesting a potential decrease (up to 45%) in sound absorption coefficient before the conversion to specific acoustic impedances.