Boundary admittance estimation for wave-based acoustic simulations using Bayesian inference

Acoustic surface admittance/impedance at domain boundaries is essential for wave-based acoustic simulations. This work applies two levels of Bayesian inference to estimate the order and the parameter values of the multipole admittance model. The frequency-dependent acoustic admittance is experimentally measured. Incorporating the maximum entropy strategy, the unified Bayesian framework is applied to the multipole approximation. Analysis results demonstrate that multipole model-based Bayesian inference is well suited to estimating the arbitrary frequency-dependent boundary condition within a wave-based simulation framework.