Sound field reconstruction (SFR) augments the information of a sound field captured by a
microphone array. Using basis function decomposition, conventional SFR methods are …

This study devised a physics-informed neural network (PINN) framework to solve the wave
equation for acoustic resonance analysis. The proposed analytical model, ResoNet …

Accurate broadband modeling of underwater acoustic channels is vital for underwater
acoustic detection, localization, and communication. Conventional modeling methodologies …

Physics-informed neural networks (PINN) is a machine learning (ML)-based method to solve
partial differential equations that has gained great popularity due to the fast development of …

Purpose The impedance boundary of the acoustic field greatly affects the sound pressure
distribution in the acoustic cavity. An innovative model for the identification of acoustic …

Room acoustic simulations at low frequencies often face significant uncertainties of material
parameters and boundary conditions due to absorbing material. We discuss the application …

The capabilities of Physics-Informed Neural Networks (PINNs) to solve the Helmholtz
equation in a simplified three-dimensional room are investigated. From a simulation point of …

The rapid urbanization and population growth have driven buildings to consume a
significant portion of the world's energy, with expectations of further increases in the future …

Accurate predictions of sound radiation are crucial for assessing sound emissions in the far
field. A widely used approach is the boundary element method, which traditionally solves the …