Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model
The inverse design of acoustic metamaterials for broadband sound absorption remains challenging due to the complex coupling dynamics and the ill-posed nature of mapping target absorption spectra to geometric parameters. This study proposes a deterministic autoencoder-like framework that integrates r...
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| Language: | English |
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Elsevier
2025-09-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025027288 |
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| author | Zhenyang Huang Zhongpeng Li Jinshun Hu Yongshui Lin Weiguo Wu Xiaofei Cao |
| author_facet | Zhenyang Huang Zhongpeng Li Jinshun Hu Yongshui Lin Weiguo Wu Xiaofei Cao |
| author_sort | Zhenyang Huang |
| collection | DOAJ |
| description | The inverse design of acoustic metamaterials for broadband sound absorption remains challenging due to the complex coupling dynamics and the ill-posed nature of mapping target absorption spectra to geometric parameters. This study proposes a deterministic autoencoder-like framework that integrates response prediction and inverse design modeling, enabling highly accurate bidirectional mapping between geometric parameters and absorption spectra. To address the ill-posed nature of inverse problems, particularly when dealing with non-physical or user-defined target spectra, a probabilistic generative model—conditional Variational Autoencoders (cVAEs)—is employed. This model constructs a disentangled latent space, facilitating the generation of multiple feasible geometric solutions for a single user-defined spectras. This probabilistic generative model requires only four absorbers to achieve quasi-perfect sound absorption (absorption coefficient α≥0.9) across any user-defined frequency bands within 400∼1300 Hz. This significantly reduces the complexity and difficulty of the design process, as the target absorption spectra can be arbitrarily customized. Furthermore, the proposed method significantly accelerates the inverse design of microperforated panel, ensuring adaptability to both physically realizable and non-physical input spectra without compromising broadband noise absorption performance. |
| format | Article |
| id | doaj-art-3225b38e90c2474cbf7c98421c1a13c9 |
| institution | DOAJ |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-3225b38e90c2474cbf7c98421c1a13c92025-08-20T02:58:00ZengElsevierResults in Engineering2590-12302025-09-012710666110.1016/j.rineng.2025.106661Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative modelZhenyang Huang0Zhongpeng Li1Jinshun Hu2Yongshui Lin3Weiguo Wu4Xiaofei Cao5Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Department of Engineering Structure and Mechanics, School of Physics and Mechanics, Wuhan University of Technology, Wuhan 430070, ChinaHubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Department of Engineering Structure and Mechanics, School of Physics and Mechanics, Wuhan University of Technology, Wuhan 430070, ChinaHubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Department of Engineering Structure and Mechanics, School of Physics and Mechanics, Wuhan University of Technology, Wuhan 430070, ChinaHubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Department of Engineering Structure and Mechanics, School of Physics and Mechanics, Wuhan University of Technology, Wuhan 430070, China; Corresponding author at: Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Department of Engineering Structure and Mechanics, School of Physics and Mechanics, Wuhan University of Technology, Wuhan 430070, ChinaGreen & Smart River-Sea-Going Ship, Cruise and Yacht Research Center, Wuhan University of Technology, Wuhan 430063, ChinaHubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, Department of Engineering Structure and Mechanics, School of Physics and Mechanics, Wuhan University of Technology, Wuhan 430070, ChinaThe inverse design of acoustic metamaterials for broadband sound absorption remains challenging due to the complex coupling dynamics and the ill-posed nature of mapping target absorption spectra to geometric parameters. This study proposes a deterministic autoencoder-like framework that integrates response prediction and inverse design modeling, enabling highly accurate bidirectional mapping between geometric parameters and absorption spectra. To address the ill-posed nature of inverse problems, particularly when dealing with non-physical or user-defined target spectra, a probabilistic generative model—conditional Variational Autoencoders (cVAEs)—is employed. This model constructs a disentangled latent space, facilitating the generation of multiple feasible geometric solutions for a single user-defined spectras. This probabilistic generative model requires only four absorbers to achieve quasi-perfect sound absorption (absorption coefficient α≥0.9) across any user-defined frequency bands within 400∼1300 Hz. This significantly reduces the complexity and difficulty of the design process, as the target absorption spectra can be arbitrarily customized. Furthermore, the proposed method significantly accelerates the inverse design of microperforated panel, ensuring adaptability to both physically realizable and non-physical input spectra without compromising broadband noise absorption performance.http://www.sciencedirect.com/science/article/pii/S2590123025027288Broadband absorptionAcoustic metamaterialsDeep learningInverse designProbabilistic generative modelUser-defined spectrum |
| spellingShingle | Zhenyang Huang Zhongpeng Li Jinshun Hu Yongshui Lin Weiguo Wu Xiaofei Cao Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model Results in Engineering Broadband absorption Acoustic metamaterials Deep learning Inverse design Probabilistic generative model User-defined spectrum |
| title | Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model |
| title_full | Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model |
| title_fullStr | Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model |
| title_full_unstemmed | Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model |
| title_short | Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model |
| title_sort | accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model |
| topic | Broadband absorption Acoustic metamaterials Deep learning Inverse design Probabilistic generative model User-defined spectrum |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025027288 |
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