Original paper
SAP-Net: Deep learning to predict sound absorption performance of metaporous materials
Abstract
Airborne sound absorption coefficient is the premise for investigating the sound absorption performance or mechanism of metaporous materials. The common numerical evaluation approach is FEM which is relatively computationally costly particularly when processing complex structures or a large batch of data. Rapidly developing deep learning algorithms, on the other hand, show a promising trend in the data-driven manner to learn and predict material...
Paper Details
Title
SAP-Net: Deep learning to predict sound absorption performance of metaporous materials
Published Date
Dec 1, 2021
Journal
Volume
212
Pages
110156 - 110156
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