Design of acoustic absorbing metasurfaces using a data-driven approach
<div><p>The design of acoustic metasurfaces with desirable properties is challenging due to their artificial nature and the large space of physical and geometrical parameters. Until recently, design strategies were primarily based on numerical simulations based on finite-element or finit...
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| منشور في: |
2023
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| _version_ | 1864513528331763712 |
|---|---|
| author | Hamza Baali (14603380) |
| author2 | Mahmoud Addouche (4422286) Abdesselam Bouzerdoum (17900021) Abdelkrim Khelif (4422280) |
| author2_role | author author author |
| author_facet | Hamza Baali (14603380) Mahmoud Addouche (4422286) Abdesselam Bouzerdoum (17900021) Abdelkrim Khelif (4422280) |
| author_role | author |
| dc.creator.none.fl_str_mv | Hamza Baali (14603380) Mahmoud Addouche (4422286) Abdesselam Bouzerdoum (17900021) Abdelkrim Khelif (4422280) |
| dc.date.none.fl_str_mv | 2023-05-29T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1038/s43246-023-00369-0 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Design_of_acoustic_absorbing_metasurfaces_using_a_data-driven_approach/25139693 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Materials engineering Mechanical engineering Information and computing sciences Data management and data science Machine learning Metamaterials Electromagnetic wave propagation Acoustic wave propagation Locally resonant structures (LRS) Metasurfaces Sound absorption Acoustic cloaking Complete sound reflection Complete sound transmission Wavefront tailoring Finite Element methods (FEM) Finite-difference time-domain (FDTD) methods Genetic algorithms Neural network architectures Gradient-based optimization Backpropagation algorithm Mean squared error (MSE) loss Levenberg-Marquardt algorithm Two-Microphone transfer function method Reflection factor Dynamic signal acquisition module |
| dc.title.none.fl_str_mv | Design of acoustic absorbing metasurfaces using a data-driven approach |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <div><p>The design of acoustic metasurfaces with desirable properties is challenging due to their artificial nature and the large space of physical and geometrical parameters. Until recently, design strategies were primarily based on numerical simulations based on finite-element or finite-difference time-domain methods, which are limited in terms of computational speed or complexity. Here, we present an efficient two-stage data-driven approach for analyzing and designing membrane-type metasurface absorbers with desirable characteristics. In the first stage, a forward model consisting of a neural network is trained to map an input, comprising the membrane parameters, to the observed sound absorption spectrum. In the second stage, the learned forward model is inverted to infer the input parameters that produce the desired absorption response. The metasurface membrane parameters, which serve as input to the neural network, are estimated by minimizing a loss function between the desired absorption profile and the output of the learned forward model. Two devices are then fabricated using the estimated membrane parameters. The measured acoustic absorption responses of the fabricated devices show a very close agreement with the desired responses.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Communications Materials<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s43246-023-00369-0" target="_blank">https://dx.doi.org/10.1038/s43246-023-00369-0</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_da4b0a89ae28d9b545ba0075656c083c |
| identifier_str_mv | 10.1038/s43246-023-00369-0 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25139693 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Design of acoustic absorbing metasurfaces using a data-driven approachHamza Baali (14603380)Mahmoud Addouche (4422286)Abdesselam Bouzerdoum (17900021)Abdelkrim Khelif (4422280)EngineeringMaterials engineeringMechanical engineeringInformation and computing sciencesData management and data scienceMachine learningMetamaterialsElectromagnetic wave propagationAcoustic wave propagationLocally resonant structures (LRS)MetasurfacesSound absorptionAcoustic cloakingComplete sound reflectionComplete sound transmissionWavefront tailoringFinite Element methods (FEM)Finite-difference time-domain (FDTD) methodsGenetic algorithmsNeural network architecturesGradient-based optimizationBackpropagation algorithmMean squared error (MSE) lossLevenberg-Marquardt algorithmTwo-Microphone transfer function methodReflection factorDynamic signal acquisition module<div><p>The design of acoustic metasurfaces with desirable properties is challenging due to their artificial nature and the large space of physical and geometrical parameters. Until recently, design strategies were primarily based on numerical simulations based on finite-element or finite-difference time-domain methods, which are limited in terms of computational speed or complexity. Here, we present an efficient two-stage data-driven approach for analyzing and designing membrane-type metasurface absorbers with desirable characteristics. In the first stage, a forward model consisting of a neural network is trained to map an input, comprising the membrane parameters, to the observed sound absorption spectrum. In the second stage, the learned forward model is inverted to infer the input parameters that produce the desired absorption response. The metasurface membrane parameters, which serve as input to the neural network, are estimated by minimizing a loss function between the desired absorption profile and the output of the learned forward model. Two devices are then fabricated using the estimated membrane parameters. The measured acoustic absorption responses of the fabricated devices show a very close agreement with the desired responses.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Communications Materials<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s43246-023-00369-0" target="_blank">https://dx.doi.org/10.1038/s43246-023-00369-0</a></p>2023-05-29T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1038/s43246-023-00369-0https://figshare.com/articles/journal_contribution/Design_of_acoustic_absorbing_metasurfaces_using_a_data-driven_approach/25139693CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/251396932023-05-29T03:00:00Z |
| spellingShingle | Design of acoustic absorbing metasurfaces using a data-driven approach Hamza Baali (14603380) Engineering Materials engineering Mechanical engineering Information and computing sciences Data management and data science Machine learning Metamaterials Electromagnetic wave propagation Acoustic wave propagation Locally resonant structures (LRS) Metasurfaces Sound absorption Acoustic cloaking Complete sound reflection Complete sound transmission Wavefront tailoring Finite Element methods (FEM) Finite-difference time-domain (FDTD) methods Genetic algorithms Neural network architectures Gradient-based optimization Backpropagation algorithm Mean squared error (MSE) loss Levenberg-Marquardt algorithm Two-Microphone transfer function method Reflection factor Dynamic signal acquisition module |
| status_str | publishedVersion |
| title | Design of acoustic absorbing metasurfaces using a data-driven approach |
| title_full | Design of acoustic absorbing metasurfaces using a data-driven approach |
| title_fullStr | Design of acoustic absorbing metasurfaces using a data-driven approach |
| title_full_unstemmed | Design of acoustic absorbing metasurfaces using a data-driven approach |
| title_short | Design of acoustic absorbing metasurfaces using a data-driven approach |
| title_sort | Design of acoustic absorbing metasurfaces using a data-driven approach |
| topic | Engineering Materials engineering Mechanical engineering Information and computing sciences Data management and data science Machine learning Metamaterials Electromagnetic wave propagation Acoustic wave propagation Locally resonant structures (LRS) Metasurfaces Sound absorption Acoustic cloaking Complete sound reflection Complete sound transmission Wavefront tailoring Finite Element methods (FEM) Finite-difference time-domain (FDTD) methods Genetic algorithms Neural network architectures Gradient-based optimization Backpropagation algorithm Mean squared error (MSE) loss Levenberg-Marquardt algorithm Two-Microphone transfer function method Reflection factor Dynamic signal acquisition module |