A nested Fourier-MIONet surrogate predicts radiative heat transfer in multi-resolution 3D fire simulations with 2-4% error at reduced computational cost compared to direct RTE solves.
Reliable extrapolation of deep neural operators informed by physics or sparse observations.Computer Methods in Applied Mechanics and Engineer- ing, 412:116064
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Nested Fourier-enhanced neural operator for efficient modeling of radiation transfer in fires
A nested Fourier-MIONet surrogate predicts radiative heat transfer in multi-resolution 3D fire simulations with 2-4% error at reduced computational cost compared to direct RTE solves.