Diffusion equation-based room acoustic modeling using a physically informed neural network

Abstract

In coupled volumes sound energy oscillates between the two rooms. To understand this sound energy flow, we use a diffusion equation model. The diffusion equation with a finite difference solution has been used to model sound energy flow in rooms. However, the finite difference approach requires a fine mesh, making it less computationally efficient for complex geometries or large scales. This work implements a mesh free solution using a physically informed neural network (PINN) with automatic differentiation. We can use PINN to simulate a sound energy impulse response in a room and predict room acoustics of complex geometries.