Yiping Sun1,2, Jiadui Chen1, Qiang Bai1, Xuefeng Zhao1, Meng Tao1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1693-1716, 2022, DOI:10.32604/cmes.2022.019336
Abstract Research on the acoustic performance of an anechoic coating composed of cavities in a viscoelastic material has recently become an area of great interest. Traditional forward research methods are unable to manipulate sound waves accurately and effectively, are difficult to analyse, have time-consuming solution processes, and have large optimization search spaces. To address these issues, this paper proposes a deep learning-based inverse research method to efficiently invert the material parameters of Alberich-type sound absorption coatings and rapidly predict their acoustic performance. First, an autoencoder (AE) model is pretrained to reconstruct the viscoelastic material parameters of an Alberich-type sound absorption coating,… More >
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