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.
The DeepONet predictions are shown alongside the corresponding reference spectrum over the frequency range from 100 to 5000 Hz
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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.