Yayın:
Wear prediction of 3D-printed acrylonitrile butadiene styrene-carbon nanotube nanocomposites at elevated temperatures

dc.contributor.authorFeratoglu, Kamil
dc.contributor.authorIstif, Ilyas
dc.contributor.authorGumus, Omer Yunus
dc.date.accessioned2026-06-27T14:49:38Z
dc.date.issued2023
dc.description.abstractIn this study, multi-wall carbon nanotube (MWCNT) reinforced acrylonitrile butadiene styrene (ABS) nanocomposite filaments are produced. Filaments are examined through thermogravimetric analysis (TGA) and definitive scanning calorimetry (DSC) analysis. Produced nanocomposite filaments are used in the fused deposition modeling (FDM) process to manufacture parts. Wear tests are conducted on 3D-printed parts using wear test apparatus with an attached heating module under different ambient temperatures. Hence, the influence of CNT reinforcement, along with different FDM process parameters and varying test conditions on the wear behavior of 3D-printed ABS-CNT parts, are examined. Worn surfaces of the specimens are examined by scanning electron microscopy (SEM). Nonlinear autoregressive exogenous (NARX) models are proposed for the prediction of the wear behavior of 3D-printed ABS-CNT nanocomposites. While wear rate is taken as output, ambient temperature and amount of nanofiller are accounted as input parameters along with the variation of coefficient of friction (COF) which is obtained from measured frictional force and three input-one output model structure is proposed for NARX. The use of multiple input-single output (MISO) model structure and examining the wear behavior of 3D-printed ABS-CNT samples under different wear test conditions with different FDM process parameters are the novelties in this work.en
dc.description.urihttps://doi.org/10.1515/polyeng-2022-0225
dc.identifier.doi10.1515/polyeng-2022-0225
dc.identifier.eissn2191-0340
dc.identifier.endpage332
dc.identifier.issn0334-6447
dc.identifier.issue4
dc.identifier.startpage318
dc.identifier.urihttps://hdl.handle.net/20.500.14981/65259
dc.identifier.volume43
dc.identifier.wos000952598800001
dc.language.isoeng
dc.publisherWALTER DE GRUYTER GMBH
dc.relation.ispartofJOURNAL OF POLYMER ENGINEERING
dc.subjectartificial neural network
dc.subjectfused deposition modelling
dc.subjectidentification
dc.subjectnanocomposite polymers
dc.subjectwear behaviour
dc.subjectMECHANICAL-PROPERTIES
dc.subjectPOLYMER COMPOSITES
dc.subjectPOLYPROPYLENE
dc.subjectPolymer Science
dc.titleWear prediction of 3D-printed acrylonitrile butadiene styrene-carbon nanotube nanocomposites at elevated temperatures
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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