A deep autoencoder based approach for the inverse design of an acoustic-absorber

This paper proposes an algorithm to perform the inverse design of a low-frequency acoustic absorber using a deep convolutional autoencoder network. A hybrid sound-absorber configuration based on Helmholtz resonators with inserted curvy neck and microperforated panel is suggested and its geometrical...

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Vydané v:	Engineering with computers Ročník 40; číslo 1; s. 279 - 300
Hlavní autori:	Mahesh, K., Ranjith, S. Kumar, Mini, R. S.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.02.2024 Springer Nature B.V
Predmet:	Absorbers Absorption spectra Accuracy Acoustic absorption Acoustic mapping Acoustics Algorithms Artificial neural networks CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer-Aided Engineering (CAD Control Effective medium theory Frequencies Helmholtz resonators Inverse design Math. Applications in Chemistry Mathematical and Computational Engineering Mathematical models Neural networks Noise reduction Original Article Parameters Sound transmission Systems Theory Electro-acoustic analogy Helmholtz resonator Low frequency sound absorption Analytical modelling Inverse design Convolutional autoencoder
ISSN:	0177-0667, 1435-5663
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