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Decomposed boundary-based Fourier Neural Operator (DB-FNO) method for efficient parametric acoustic analysis with frequency-dependent boundary conditions
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DOI：10.1016/j.jsv.2026.120018.png)
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Abstract
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• We propose an efficient surrogate modeling technique for large-scale parametric acoustic waves. • It greatly reduces time and memory needs compared to existing methods. • The solution accuracy remains comparable to standard high-fidelity models. • It was successfully tested on various wave scattering and radiation problems. • It handles problems with frequency-dependent boundary conditions, enabling realistic engineering use.
Keywords:
Surrogate model
Acoustic wave
Boundary element method
Fourier neural operators
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4.9
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1.7W
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