Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks

doi:10.16183/j.cnki.jsjtu.2019.242

Abstract

Abstract:

In this paper, the prediction of the energy transmission spectrum for layered periodic structures is studied. By considering three cases of geometric parameters and physical parameters changing individually or simultaneously, a deep back propagation (BP) neural network is constructed to realize accurate prediction of the energy transmission spectrum of layered periodic structure. A comparison of the predicted results with those obtained by the radial basis function (RBF) neural network verifies the effectiveness of the proposed method.

Key words: layered periodic structure, deep back propagation (BP) neural network, radial basis function (RBF) neural network, energy transmission spectrum, attenuation domain

CLC Number:

TU591

LIU Chenxu, YU Guilan. Prediction of Energy Transmission Spectrum of Layered Periodic Structures by Neural Networks[J]. Journal of Shanghai Jiao Tong University, 2021, 55(1): 88-95.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

References 17

[1]	SIGALAS M M, ECONOMOU E N. Elastic and acoustic wave band structure[J]. Journal of Sound and Vibration, 1992, 158(2): 377-382.
[2]	LIU Z, ZHANG X, MAO Y, et al. Locally resonant sonic materials[J]. Science, 2000, 289(5485): 1734-1736.
[3]	LECUN Y, BENGIO Y, HINTON G. Deep learning[J]. Nature, 2015, 521(7553): 436-444.
[4]	王斌，刘允才，茅红伟. 一种基于产生式分数空间的单样本人脸识别方法[J]. 上海交通大学学报，2017, 51(2): 202-208.
	WANG Bin, LIU Yuncai, MAO Hongwei. Single sample face identification based on generative score space[J]. Journal of Shanghai Jiao Tong University, 2017, 51(2): 202-208.
[5]	YADAV D, YADAV T, VERMA A. Performance analysis of PMSM drive using Artificial Neural Network technique[C]∥2016 International Conference on Emerging Trends in Communication Technologies. Dehradun, India: IEEE, 2016: 16760722.
[6]	CHAN W, JAITLY N, LE Q, et al. Listen, attend and spell: A neural network for large vocabulary conversational speech recognition[C]∥2016 IEEE International Conference on Acoustics, Speech and Signal Processing. Shanghai, China: IEEE, 2016: 16004539.
[7]	SIGTIA S, BENETOS E, DIXON S. An end-to-end neural network for polyphonic piano music transcription[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2016, 24(5): 927-939.
[8]	DA SILVA FERREIRA A, MALHEIROS-SILVEIRA G N, HERNANDEZ-FIGUEROA H E. Computing optical properties of photonic crystals by using multilayer perceptron and extreme learning machine[J]. Journal of Lightwave Technology, 2018, 36(18): 4066-4073.
[9]	LIU D J, TAN Y X, KHORAM E, et al. Training deep neural networks for the inverse design of nanophotonic structures[J]. ACS Photonics, 2018, 5(4): 1365-1369.
[10]	MA W, CHENG F, XU Y H, et al. Probabilistic representation and inverse design of metamaterials based on a deep generative model with semi-supervised learning strategy[J]. Advanced Materials, 2019, 31(35): 1901111.
[11]	LIU C X, YU G L, ZHAO G Y. Neural networks for inverse design of phononic crystals[J]. AIP Advances, 2019, 9(8): 085223.
[12]	XIANG H J, SHI Z F, WANG S J, et al. Periodic materials-based vibration attenuation in layered foundations: Experimental validation[J]. Smart Materials and Structures, 2012, 21(11): 112003.
[13]	SHI Z F, CHENG Z B, XIANG H J. Seismic isolation foundations with effective attenuation zones[J]. Soil Dynamics and Earthquake Engineering, 2014, 57: 143-151.
[14]	HUANG J K, LIU W, SHI Z F. Surface-wave attenuation zone of layered periodic structures and feasible application in groundvibration reduction[J]. Construction and Building Materials, 2017, 141: 1-11.
[15]	CAMLEY R E, DJAFARI-ROUHANI B, DOBRZYNSKI L, et al. Transverse elastic waves in periodically layered infinite and semi-infinite media[J]. Physical Review B, 1983, 27(12): 7318.
[16]	ZHOU X Z, WANG Y S, ZHANG C Z. Effects of material parameters on elastic band gaps of two-dimensional solidphononic crystals[J]. Journal of Applied Physics, 2009, 106(1): 014903.
[17]	KINGMA D P, BA J. Adam: A method for stochastic optimization[DB/OL](2017-01-30)[2019-07-15]. .