Predicting energy absorption parameters of aluminum lattice structures filled tubes via artificial neural networks

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dc.authorid0000-0001-5551-6934
dc.authorid0000-0001-7583-7655
dc.contributor.authorÇetin, Erhan
dc.contributor.authorBaykasoğlu, Cengiz
dc.contributor.authorBaykasoğlu, Adil
dc.date.accessioned2019-12-09T07:30:46Z
dc.date.available2019-12-09T07:30:46Z
dc.date.issued2019en_US
dc.departmentHitit Üniversitesi, Mühendislik Fakültesi, Makine Mühendisliği Bölümü
dc.description.abstractIn this paper, the energy absorption parameters of aluminum body centered cubic lattice structures filled thin-walled tubes under axial loading are predicted via artificial neural networks (ANNs). Different tube thickness, lattice member diameters and number of lattice unit cells are considered as design variables, the total amount of energy absorption (EA), the specific energy absorption (SEA), the mean crush force (MCF) and the peak crush force (PCF) are considered as design criteria (energy absorption parameters). The proposed approach is based on finite element simulations for construction of the sample design space and verification, ANNs for predicting the energy absorption parameters. The results showed that the proposed ANN approach is able to predict the energy absorption parameters with high accuracy.
dc.description.provenanceSubmitted by Cengiz Baykasoğlu (cengizbaykasoglu@hitit.edu.tr) on 2019-12-07T16:19:06Z No. of bitstreams: 2 license_rdf: 700 bytes, checksum: 79da7ba44461b593b4f6afc1f09853c4 (MD5) iatens_bildiri.pdf: 673504 bytes, checksum: 137e78b22ed9c1c95c1216e56ad9d65f (MD5)en
dc.description.provenanceApproved for entry into archive by Zeynep Umut Arslan (umutarslan@hitit.edu.tr) on 2019-12-09T07:30:46Z (GMT) No. of bitstreams: 2 license_rdf: 700 bytes, checksum: 79da7ba44461b593b4f6afc1f09853c4 (MD5) iatens_bildiri.pdf: 673504 bytes, checksum: 137e78b22ed9c1c95c1216e56ad9d65f (MD5)en
dc.description.provenanceMade available in DSpace on 2019-12-09T07:30:46Z (GMT). No. of bitstreams: 2 license_rdf: 700 bytes, checksum: 79da7ba44461b593b4f6afc1f09853c4 (MD5) iatens_bildiri.pdf: 673504 bytes, checksum: 137e78b22ed9c1c95c1216e56ad9d65f (MD5) Previous issue date: 2019en
dc.description.sponsorshipScientific Research Projects Governing Unit of Hitit University, project No: MUH19004.18.001en_US
dc.identifier.citationÇetin, E., Baykasoğlu, C., Baykasoğlu, A. (2019). Predicting energy absorption parameters of aluminum lattice structures filled tubes via artificial neural networks. The International Aluminium-Themed Engineering and Natural Sciences Conference, October 4-6 2019, Seydişehir, Turkey.
dc.identifier.endpage536en_US
dc.identifier.startpage532en_US
dc.identifier.urihttps://hdl.handle.net/11491/5464
dc.language.isoen
dc.relation.ispartofThe International Aluminium-Themed Engineering and Natural Sciences Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial Neural Networksen_US
dc.subjectEnergy Absorptionen_US
dc.subjectLattice Structuresen_US
dc.subjectEnergy Absorptionen_US
dc.subjectFinite Element Methoden_US
dc.titlePredicting energy absorption parameters of aluminum lattice structures filled tubes via artificial neural networks
dc.typeConference Object

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