Inverse design and experimental verification of an acoustic sink based on machine learning

Applied Acoustics - Tập 180 - Trang 108153 - 2021
Nansha Gao1,2, Mou Wang1, Baozhu Cheng1, Hong Hou1
1Key Laboratory of Ocean Acoustic and Sensing, School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
2Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore

Tài liệu tham khảo

Cummer, 2016, Controlling sound with acoustic metamaterials, Nat Rev Mater, 1, 16001, 10.1038/natrevmats.2016.1 Yang, 2017, Sound absorption structures: from porous media to acoustic metamaterials, Annu Rev Mater Res, 47, 83, 10.1146/annurev-matsci-070616-124032 Zhu, 2018, Simultaneous observation of a topological edge state and exceptional point in an open and non-hermitian acoustic system, Phys Rev Lett, 121, 10.1103/PhysRevLett.121.124501 Ma, 2014, Acoustic metasurface with hybrid resonances, Nat Mater, 13, 873, 10.1038/nmat3994 Carbajo, 2020, Sound absorption of acoustic resonators with oblique perforations, Appl Phys Lett, 116, 10.1063/1.5132886 Duan, 2020, Acoustic impedance regulation of Helmholtz resonators for perfect sound absorption via roughened embedded necks, Appl Phys Lett, 117, 10.1063/5.0024804 Gao, 2019, Design and experimental investigation of V-folded beams with acoustic black hole indentations, J Acoust Soc Am, 145, EL79-83, 10.1121/1.5088027 Gao, 2021, Hybrid composite meta-porous structure for improving and broadening sound absorption, Mech Syst Signal Pr, 154, 10.1016/j.ymssp.2020.107504 Gao, 2021, Design, fabrication and sound absorption test of composite porous matamaterial with embedding I-plates into porous polyurethane, Appl Acoust, 175, 10.1016/j.apacoust.2020.107845 Lv, 2020, Temporal acoustic wave computational metamaterials, Appl Phys Lett, 117, 10.1063/5.0018758 Zhang, 2020, Symmetry-protected hierarchy of anomalous multipole topological band gaps in nonsymmorphic metacrystals, Nat Commun, 11, 65, 10.1038/s41467-019-13861-4 Weiner, 2020, Demonstration of a third-order hierarchy of topological states in a three-dimensional acoustic metamaterial, Sci Adv, 6, eaay4166, 10.1126/sciadv.aay4166 Xue, 2019, Acoustic higher-order topological insulator on a kagome lattice, Nat Mater, 18, 108, 10.1038/s41563-018-0251-x Gao, 2021, Teaching-learning-based optimization of an ultra-broadband parallel sound absorber, Appl Acoust, 178, 10.1016/j.apacoust.2021.107969 Gao NS, Luo DD, Cheng BZ, Hou H. Teaching-learning-based optimization of a composite metastructure in the 0–10 kHz broadband sound absorption range. J Acoust Soc Am 2020; 148: EL125-EL129. Xiong, 2017, Sound attenuation optimization using metaporous materials tuned on exceptional points, J Acoust Soc Am., 142, 2288, 10.1121/1.5007851 Park, 2017, Optimization of low frequency sound absorption by cell size control and multiscale poroacoustics modeling, J Sound Vib., 397, 17, 10.1016/j.jsv.2017.03.004 Chambers, 2020, Design and optimization of 3D folded-core acoustic liners for enhanced low-frequency performance, AIAA J., 58, 206, 10.2514/1.J058017 Brunton, 2020, Machine learning for fluid mechanics, Annu Rev Fluid Mech, 52, 477, 10.1146/annurev-fluid-010719-060214 Bianco, 2019, Machine learning in acoustics: Theory and applications, J Acoust Soc Am, 146, 3590, 10.1121/1.5133944 Gao, 2019, A bidirectional deep neural network for accurate silicon color design, Adv Mater, 31, 1905467, 10.1002/adma.201905467 Li, 2019, Machine-learning reprogrammable metasurface imager, Nat Commun, 10, 1082, 10.1038/s41467-019-09103-2 Bessa, 2019, Bayesian machine learning in metamaterial design: Fragile becomes supercompressible, Adv Mater, 31, 1904845, 10.1002/adma.201904845 Luo, 2020, Probability-density-based deep learning paradigm for the fuzzy design of functional metastructures, Research, 2020, 8757403, 10.34133/2020/8757403 Stinson, 1991, The propagation of plane sound waves in narrow and wide circular tubes, and generalization to uniform tubes of arbitrary cross-sectional shape, J Acoust Soc Am, 89, 550, 10.1121/1.400379 Johnson, 1987, Theory of dynamic permeability and tortuosity in fluid-saturated porous media, J Fluid Mech, 176, 379, 10.1017/S0022112087000727 Champoux, 1991, Dynamic tortuosity and bulk modulus in air-saturated porous media, J Appl Phys, 70, 1975, 10.1063/1.349482 Allard, 1992, New empirical equations for sound propagation in rigid frame fibrous materials, J Acoust Soc Am, 91, 3346, 10.1121/1.402824 Jimenez, 2017, Rainbow-trapping absorbers: Broadband, perfect and asymmetric sound absorption by subwavelength panels for transmission problems, Sci. Rep. UK, 7, 13595, 10.1038/s41598-017-13706-4 Romero-Garcia, 2016, Perfect and broadband acoustic absorption by critically coupled sub-wavelength resonators, Sci. Rep. UK, 6, 19519, 10.1038/srep19519 Cavalieri, 2019, Acoustic wave propagation in effective graded fully anisotropic fluid layers, J Acoust Soc Am, 146, 3400, 10.1121/1.5131653 Krizhevsky A, Sutskever I, Hinton G. Imagenet classification with deep convolutional neural networks. N I P S 2012; 25: 1097–1105. Yang, 2019, TS-RNN: Text steganalysis based on recurrent neural networks, IEEE Signal Proc Let, 26, 1743, 10.1109/LSP.2019.2920452 Sundermeyer, 2015, From feedforward to recurrent LSTM neural networks for language modeling, IEEE-ACM T Audio Spe, 23, 517 Gelly, 2018, Optimization of RNN-based speech activity detection, IEEE-ACM T Audio Spe, 26, 646 Song, 2017, Effective spectral and excitation modeling techniques for LSTM-RNN-based speech synthesis systems, IEEE-ACM T Audio Spe, 25, 2152 Acoustics-Determination of sound absorption coefficient and impedance in impedance tubes-Part2: Transfer-function method, ISO Standard 10534-2: 1998.