Artificial neural network application for novel 3D printed nonuniform ceramic reflectarray antenna

Basit Öğe Kaydı
dc.authorid0000-0002-3351-4433en_US
dc.authorid0000-0001-5588-9407en_US
dc.contributor.authorMahouti, Mehran
dc.contributor.authorKuşkonmaz, Nilgün
dc.contributor.authorMahouti, Peyman
dc.contributor.authorBelen, Mehmet Ali
dc.contributor.authorPalandöken, Merih
dc.date.accessioned2020-04-03T12:03:51Z
dc.date.available2020-04-03T12:03:51Z
dc.date.issued2020
dc.departmentAÇÜ, Mühendislik Fakültesien_US
dc.description.abstractThe main inconvenience in design process of modern high performance reflec-tarray antennas is that these designs are heavily depended on full-wave electro-magnetic simulation tools, where in most of the cases the design optimizationprocess would be an inefficient or impractical. However, thanks to the recentadvances in computer-aided design and advanced hardware systems, artificialneural networks based modeling of microwave systems has become a popularresearch topic. Herein, design optimization of an alumina-based ceramic sub-strate reflectarray antenna by using multilayer perceptron (MLP) and 3D printingtechnology had been presented. MLP-based model of ceramic reflectarray (CRA)unit element is used as a fast, accurate, and reliable surrogated model for the pre-diction of reflection phase of the incoming EM wave on the CRA unit cell withrespect to the variation of unit elements design parameters, operation frequency,and substrate thickness. The structural design of a reflectarray antenna with non-uniform reflector height operating in Xband has been fabricated for the experi-mental measurement of reflectarray performance using 3D printer technology.The horn feeding based CRA antenna has a measured gain characteristic of22 dBi. The performance of the prototyped CRA antenna is compared with thecounterpart reflectarray antenna designs in the literature.
dc.description.sponsorshipYildiz Technical University: 2015-07-02-YL03en_US
dc.identifier.citationMahouti, M., Kuskonmaz, N., Mahouti, P., Belen, M. A., & Palandoken, M. (2020). Artificial neural network application for novel 3D printed nonuniform ceramic reflectarray antenna. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. 33(6),en_US
dc.identifier.doi10.1002/jnm.2746
dc.identifier.issue6
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://hdl.handle.net/11494/2016
dc.identifier.volume33
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBelen, Mehmet Ali
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofInternational Journal of Numerical Modelling: Electronic Networks, Devices and Fields
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject3D printeren_US
dc.subjectArtificial neural networken_US
dc.subjectCeramic, Reflectarrayen_US
dc.subjectSurrogate-based modelingen_US
dc.titleArtificial neural network application for novel 3D printed nonuniform ceramic reflectarray antennaen_US
dc.typeArticle

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
[ X ]
İsim:
mehran.mahouti.pdf
Boyut:
2 MB
Biçim:
Adobe Portable Document Format
Açıklama:
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
[ X ]
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Elektrik - Elektronik Mühendisliği Bölümü Yayın Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu