Citation: | GAO Zhaorui, LI Zheng, JIANG Yongfeng, SHEN Cheng, MENG Han. Acoustic Performance Rapid Prediction and Structural Optimization for Resonant SoundAbsorbing Metamaterials Based on Artificial Neural Networks[J]. Applied Mathematics and Mechanics, 2024, 45(8): 1058-1069. doi: 10.21656/1000-0887.450170 |
[2]MAA D Y. Theory of microslit absorbers[J].Acta Acustica, 2000, 25(6): 481-485.
|
郭梦媛, 刘崇锐, 苏文斌, 等. 高阶微穿孔型超材料低频宽带吸声机理[J]. 西安交通大学学报, 2024,58(4): 192-199
, 220.(GUO Mengyuan, LIU Chongrui, SU Wengbin, et al. Low-frequency broadband absorption mechanism of high-order micro-perforated meta-materials[J].Journal of Xi’an Jiaotong University, 2024, 58(4): 192-199, 220.(in Chinese))
|
[3]MAA D Y, LIU K. Sound absorption characteristics of microperforated absorber for random incidence[J].Acta Acustica, 2000, 25(4): 289-296.
|
[4]LALY Z, ATALLA N, MESLIOUI S A. Acoustical modeling of micro-perforated panel at high sound pressure levels using equivalent fluid approach[J].Journal of Sound and Vibration, 2018, 427: 134-158.
|
[5]GAI X L, XING T, LI X H, et al. Sound absorption of microperforated panel with L shape division cavity structure[J].Applied Acoustics, 2017, 122: 41-50.
|
[6]LEE D H, KWON Y P. Estimation of the absorption performance of multiple layer perforated panel systems by transfer matrix method[J].Journal of Sound and Vibration, 2004, 278(4): 847-860.
|
[7]GAI X L, XING T, LI X H, et al. Sound absorption properties of microperforated panel with membrane cell and mass blocks composite structure[J].Applied Acoustics, 2018, 137: 98-107.
|
[8]LIU X W, YU C L, XIN F X. Gradually perforated porous materials backed with Helmholtz resonant cavity for broadband low-frequency sound absorption[J].Composite Structures, 2021, 263: 113647.
|
[9]ZHANG H J, WANG Y, LU K Y, et al. SAP-net: deep learning to predict sound absorption performance of metaporous materials[J].Materials & Design, 2021, 212: 110156.
|
[10]YANG H T, ZHANG H J, WANG Y, et al. Prediction of sound absorption coefficient for metaporous materials with convolutional neural networks[J].Applied Acoustics, 2022, 200: 109052.
|
[11]PAN B R, SONG X, XU J J, et al. Accelerated inverse design of customizable acoustic metaporous structures using a CNN-GA-based hybrid optimization framework[J].Applied Acoustics, 2023, 210: 109445.
|
[12]IANNACE G, CIABURRO G, TREMATERRA A. Modelling sound absorption properties of broom fibers using artificial neural networks[J].Applied Acoustics, 2020, 163: 107239.
|
[13]SHEN X M, BAI P F, YANG X C, et al. Low frequency sound absorption by optimal combination structure of porous metal and microperforated panel[J].Applied Sciences-Basel, 2019, 9(7): 1507.
|
[14]TANG Y F, LI F H, XIN F X, et al. Heterogeneously perforated honeycomb-corrugation hybrid sandwich panel as sound absorber[J].Materials & Design, 2017, 134: 502-512.
|
[15]TANG Y F, XIN F X, HUANG L X, et al. Deep subwavelength acoustic metamaterial for low-frequency sound absorption[J].Europhysics Letters, 2017, 118(4): 44002.
|
[16]WANG S B, WANG B, FAN J, et al. Inversion of equivalent parameters of acoustic coating based on genetic algorithm[J].Journal of Ship Mechanics, 2023, 27(3): 456-469.
|
[17]JIANG Y F, SHEN C, MENG H, et al. Design and optimization of micro-perforated ultralight sandwich structure with N-type hybrid core for broadband sound absorption[J].Applied Acoustics, 2023, 202: 109184.
|
[18]王飞萌, 王良模, 王陶, 等. 微穿孔板-三聚氰胺吸音海绵-空腔复合结构声学性能优化设计[J]. 北京化工大学学报(自然科学版), 2022, 49(1): 113-121.(WANG Feimeng, WANG Liangmo, WANG Tao, et al. Optimization of the acoustic performance of micro-perforated panel-melamine sound-absorbing sponge-cavity composite structures[J].Journal of Beijing University of Chemical Technology (Natural Science), 2022, 49(1): 113-121.(in Chinese))
|
[19]LI H X. Fuzzy logic systems are equivalent to feedforward neural networks[J].Science in China (Series E): Technological Sciences, 2000, 43(1): 42-54.
|
[20]LING S H, LAM H K, LEUNG F H F, et al. A genetic algorithm based neural-tuned neural network[C]//Proceedings of the 〖STBX〗29th Annual Conference of the IEEE Industrial Electronics Society. Roanoke, America, 2003: 2423-2428.
|
[21]WANG X Y, ZHANG Y. Chaotic diagonal recurrent neural network[J].Chinese Physics B, 2012, 21(3): 038703.
|
[22]WEN L, QIU Z W, QI R N. Passenger capacity prediction based on genetic neural network[C]//Proceedings of the 1st International Symposium on Information Engineering and Electronic Commerce. Ternopil, Ukraine, 2009: 696-700.
|
[23]姚浩, 夏桂然, 刘泽佳, 等. 基于机器学习的黏钢构件黏接层缺陷识别方法研究[J]. 应用数学和力学, 2024, 45(4): 429-442.(YAO Hao, XIA Guiran, LIU Zejia, et al. A defect identification method for bonding layers of adhesive steel members based on machine learning[J].Applied Mathematics and Mechanics, 2024, 45(4): 429-442.(in Chinese))
|
[24]CIABURRO G, IANNACE G. Modeling acoustic metamaterials based on reused buttons using data fitting with neural network[J].Journal of the Acoustical Society of America, 2021, 150(1): 51-63.
|
[25]CIABURRO G, IANNACE G. Membrane-type acoustic metamaterial using cork sheets and attached masses based on reused materials[J].Applied Acoustics, 2022, 189: 108605.
|
[26]LUO Z H, LI T, YAN Y W, et al. Prediction of sound insulation performance of aramid honeycomb sandwich panel based on artificial neural network[J].Applied Acoustics, 2022, 190: 108656.
|
[27]DOUTRES O, ATALLA N, OSMAN H. Transfer matrix modeling and experimental validation of cellular porous material with resonant inclusions[J].Journal of the Acoustical Society of America, 2015, 137(6): 3502-3513.
|