A physics-informed deep operator network infers globally consistent acoustic surface admittance spectra from near-field measurements while enforcing the Helmholtz equation, momentum equation, and Robin boundary conditions during training.
This separation of roles re- duces the complexity of the learning problem and enables the model to generalize to arbitrary spatial evaluation points54
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Physics-informed neural operators for the in situ characterization of locally reacting sound absorbers
A physics-informed deep operator network infers globally consistent acoustic surface admittance spectra from near-field measurements while enforcing the Helmholtz equation, momentum equation, and Robin boundary conditions during training.