3 papers
eess.AS2025
Physics-Informed Deep Learning for Nonlinear Friction Model of Bow-string Interaction
Xinmeng Luan, Gary Scavone
This study investigates the use of an unsupervised, physics-informed deep learning framework to model a one-degree-of-freedom mass-spring system subjected to a nonlinear friction b…
eess.AS2025
Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks
Xinmeng Luan, Kazuya Yokota, Gary Scavone
This study investigates the application of Physics-Informed Neural Networks (PINNs) to inverse problems in acoustic tube analysis, focusing on reconstructing acoustic fields from n…
eess.AS2025
Physics-Informed Neural Network-Driven Sparse Field Discretization Method for Near-Field Acoustic Holography
Xinmeng Luan, Mirco Pezzoli, Fabio Antonacci +1
We propose the Physics-Informed Neural Network-driven Sparse Field Discretization method (PINN-SFD), a novel self-supervised, physics-informed deep learning approach for addressing…