Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy

This paper introduces a new objective-driven design method based on deep learning for meta-structure absorber for X-band (8–12 GHz) application. The method consists of three steps; at Step 1, developing a simulator to predict a spectrum of microwave from a conductive layer of absorber as an image in...

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Autores principales:	Han-Ik On, Leekyo Jeong, Minseok Jung, Dong-Joong Kang, Jun-Hyub Park, Hak-Joo Lee
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Microwave absorber FDTD Deep learning VAE CMA-ES Balancing loss Materials of engineering and construction. Mechanics of materials TA401-492
Acceso en línea:	https://doaj.org/article/ceb41be6506b488bb10628a411516ceb
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spelling	oai:doaj.org-article:ceb41be6506b488bb10628a411516ceb2021-11-28T04:27:44ZOptimal design of microwave absorber using novel variational autoencoder from a latent space search strategy0264-127510.1016/j.matdes.2021.110266https://doaj.org/article/ceb41be6506b488bb10628a411516ceb2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S0264127521008212https://doaj.org/toc/0264-1275This paper introduces a new objective-driven design method based on deep learning for meta-structure absorber for X-band (8–12 GHz) application. The method consists of three steps; at Step 1, developing a simulator to predict a spectrum of microwave from a conductive layer of absorber as an image input, at Step 2, designing an autoencoder network to take the patterns as input and outputs the same pattern, at Step 3, making an inverse design method for a new pattern under a given goal (spectrum). The proposed method was verified by comparing with the reflectance spectrum calculated by FDTD on the designed absorber with an optimal conductive pattern layer. For the effective training of a general random-like pixel patterns, the variational autoencoder (VAE) that uses a new adaptive annealing loss and a symmetricity layer block in VAE decoder is suggested to improve the training performance. The covariance Matrix Adaptation Evolution Strategy (CMA-ES) which searches the optimal pattern in the VAE latent space is used for suggesting the candidates of the optimal pattern. The proposed method can find an optimal absorber with minimum −16 dB reflectance in X-band that exceed the best absorption among all the training samples obtained by FDTD.Han-Ik OnLeekyo JeongMinseok JungDong-Joong KangJun-Hyub ParkHak-Joo LeeElsevierarticleMicrowave absorberFDTDDeep learningVAECMA-ESBalancing lossMaterials of engineering and construction. Mechanics of materialsTA401-492ENMaterials & Design, Vol 212, Iss , Pp 110266- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Microwave absorber FDTD Deep learning VAE CMA-ES Balancing loss Materials of engineering and construction. Mechanics of materials TA401-492
spellingShingle	Microwave absorber FDTD Deep learning VAE CMA-ES Balancing loss Materials of engineering and construction. Mechanics of materials TA401-492 Han-Ik On Leekyo Jeong Minseok Jung Dong-Joong Kang Jun-Hyub Park Hak-Joo Lee Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
description	This paper introduces a new objective-driven design method based on deep learning for meta-structure absorber for X-band (8–12 GHz) application. The method consists of three steps; at Step 1, developing a simulator to predict a spectrum of microwave from a conductive layer of absorber as an image input, at Step 2, designing an autoencoder network to take the patterns as input and outputs the same pattern, at Step 3, making an inverse design method for a new pattern under a given goal (spectrum). The proposed method was verified by comparing with the reflectance spectrum calculated by FDTD on the designed absorber with an optimal conductive pattern layer. For the effective training of a general random-like pixel patterns, the variational autoencoder (VAE) that uses a new adaptive annealing loss and a symmetricity layer block in VAE decoder is suggested to improve the training performance. The covariance Matrix Adaptation Evolution Strategy (CMA-ES) which searches the optimal pattern in the VAE latent space is used for suggesting the candidates of the optimal pattern. The proposed method can find an optimal absorber with minimum −16 dB reflectance in X-band that exceed the best absorption among all the training samples obtained by FDTD.
format	article
author	Han-Ik On Leekyo Jeong Minseok Jung Dong-Joong Kang Jun-Hyub Park Hak-Joo Lee
author_facet	Han-Ik On Leekyo Jeong Minseok Jung Dong-Joong Kang Jun-Hyub Park Hak-Joo Lee
author_sort	Han-Ik On
title	Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
title_short	Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
title_full	Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
title_fullStr	Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
title_full_unstemmed	Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
title_sort	optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/ceb41be6506b488bb10628a411516ceb
work_keys_str_mv	AT hanikon optimaldesignofmicrowaveabsorberusingnovelvariationalautoencoderfromalatentspacesearchstrategy AT leekyojeong optimaldesignofmicrowaveabsorberusingnovelvariationalautoencoderfromalatentspacesearchstrategy AT minseokjung optimaldesignofmicrowaveabsorberusingnovelvariationalautoencoderfromalatentspacesearchstrategy AT dongjoongkang optimaldesignofmicrowaveabsorberusingnovelvariationalautoencoderfromalatentspacesearchstrategy AT junhyubpark optimaldesignofmicrowaveabsorberusingnovelvariationalautoencoderfromalatentspacesearchstrategy AT hakjoolee optimaldesignofmicrowaveabsorberusingnovelvariationalautoencoderfromalatentspacesearchstrategy
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Optimal design of microwave absorber using novel variational autoencoder from a latent space search strategy

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