Dimensional stability and deformation analysis under mechanical loading of recycled PET-wood laminated composites with digital image correlation

dc.contributor.authorBakır, Kıvanç
dc.contributor.authorAydemir, Deniz
dc.contributor.authorBardak, Timuçin
dc.contributor.authorBardak, Timuçin
dc.contributor.authorBakır, Kıvanç
dc.contributor.authorAydemir, Deniz
dc.date.accessioned2025-10-18T13:25:00Z
dc.date.created2021
dc.date.issued2021
dc.departmentFakülteler, Orman Fakültesi, Orman Endüstri Mühendisliği Bölümü
dc.departmentMeslek Yüksekokulları, Bartın Meslek Yüksekokulu, Malzeme ve Malzeme İşleme Teknolojileri Bölümü
dc.description.abstractThe aim of this study is to investigate the dimensional stability, bending strength and modulus of elasticity at bending of recycled polyethylene terephthalate (PET) layers - wood laminated composites bonded with polyurethane (PU) adhesive and to analyze the deformation behavior with digital image correlation (DIC) during the bending test. The waste beverage bottles were collected from a trash bin and granulated with a cutter. PET layers were obtained by molding the granules at 265 degrees C under a hydraulic pressure. The composites were prepared with three and five layers of wood veneers and PET layers by using a hydraulic press at room temperature (24 degrees C) for 4 h. The digital image correlation was conducted to detect the deformation behavior of the composites during the bending test. According to the obtained results, water absorption and thickness swelling decreased with the addition of PET layers. Especially, PET layers outside blocked water absorption of the composites and provided higher resistance to water absorption in the composites when the amount of PET layers was raised. The presence of the PET layers decreased the bending strength and modulus of elasticity at bending of the composites, and the decrease in the bending strength and modulus of elasticity at bending was determined to range from 15% to 30%-46% and 50%, respectively. The mechanical simulation results obtained with the DIC were found to be similar to the results determined with the experimental test. The DIC results processed with open-source 2D digital image correlation MatLab software (NCORR) indicated higher deformation area and more densified stress distribution on the surface of the composites with PET layers. (C) 2020 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipBartin University [2017-FEN-A-009]
dc.description.sponsorshipThe study was supported by the Scientific Research Coordinator of Bartin University with project number 2017-FEN-A-009.
dc.identifier.doi10.1016/j.jclepro.2020.124472
dc.identifier.issn0959-6526
dc.identifier.issn1879-1786
dc.identifier.orcidBAKIR, KIVANC/0000-0002-1781-2975
dc.identifier.orcidAydemir, Deniz/0000-0002-7484-2126;
dc.identifier.scopus2-s2.0-85091945563
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.jclepro.2020.124472
dc.identifier.urihttps://hdl.handle.net/11772/23195
dc.identifier.volume280
dc.identifier.wosWOS:000608741500018
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofJournal of Cleaner Production
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.relation.sdgGoal-12: Responsible Consumption and Production
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzWoS_20251016
dc.subjectPolyethylene Terephthalate
dc.subjectWaste Bottles
dc.subjectValue-Added Materials
dc.subjectWood Veneers
dc.subjectDigital Image Correlation
dc.titleDimensional stability and deformation analysis under mechanical loading of recycled PET-wood laminated composites with digital image correlation
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication161d0d65-84d1-42ba-960e-efd2dc741e63
relation.isAuthorOfPublication7daa448c-a34e-414b-ade7-892ffbe9f54c
relation.isAuthorOfPublication836bc692-8f7f-4623-829c-2091411dbc33
relation.isAuthorOfPublication.latestForDiscovery161d0d65-84d1-42ba-960e-efd2dc741e63

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