The prediction and evaluation of recycled polypropylene fiber and aggregate incorporated foam concrete using Artificial Neural Networks

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dc.authorscopusid57120104100
dc.authorscopusid57471145100
dc.authorscopusid58530020000
dc.authorscopusid9741842600
dc.contributor.authorYildizel S.A.
dc.contributor.authorUzun M.
dc.contributor.authorArslan M.A.
dc.contributor.authorOzbakkaloglu T.
dc.date.accessioned2024-01-22T12:22:34Z
dc.date.available2024-01-22T12:22:34Z
dc.date.issued2024
dc.departmentKMÜen_US
dc.description.abstractReinforcement with recycled fiber is widely investigated to improve the mechanical behavior of foam concrete. In addition, the use of recycled aggregate in concrete provides benefits in terms of sustainability as it reduces the use of raw materials. In this research, 6 mm-long fibers and aggregates obtained from waste polypropylene were utilized in foam concrete production. This study also presents an evaluation of the recycled polypropylene fiber (PppF) and aggregate (PppA) incorporated foam concretes using ANOVA and ANNs. The ANN model was developed to estimate the compressive and flexural strengths, dry density, and thermal conductivity. The results indicated that the use of recycled polypropylene fiber increased the compressive and flexural strengths, however, polypropene aggregates affected the strengths negatively. And mixtures with higher levels of RppA and RppF have lower thermal conductivities. The slump of fresh concrete had an apparent reduction with the increase in RppA quantity. Also, both the ANN and ANOVA approaches were appropriate for optimizing and estimating responses. © 2023 Elsevier Ltden_US
dc.description.sponsorshipThe author would like to acknowledge KMU-BILTEM for their help and support.en_US
dc.identifier.doi10.1016/j.conbuildmat.2023.134646
dc.identifier.issn09500618
dc.identifier.scopus2-s2.0-85180978732
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.conbuildmat.2023.134646
dc.identifier.urihttps://hdl.handle.net/11492/8048
dc.identifier.volume411en_US
dc.identifier.wosWOS:001145226000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Ltden_US
dc.relation.ispartofConstruction and Building Materialsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzkmusnmz
dc.subjectANNen_US
dc.subjectANOVAen_US
dc.subjectFoam Concreteen_US
dc.subjectRecycled Polypropylene aggregateen_US
dc.subjectRecycled Polypropylene fiberen_US
dc.subjectAnalysis of variance (ANOVA)en_US
dc.subjectBending strengthen_US
dc.subjectConcrete aggregatesen_US
dc.subjectNeural networksen_US
dc.subjectPolypropylenesen_US
dc.subjectThermal conductivityen_US
dc.subjectANNen_US
dc.subjectCompressive and flexural strengthsen_US
dc.subjectFoam concretesen_US
dc.subjectMechanical behavioren_US
dc.subjectRecycled aggregatesen_US
dc.subjectRecycled fibersen_US
dc.subjectRecycled polypropyleneen_US
dc.subjectRecycled polypropylene aggregateen_US
dc.subjectRecycled polypropylene fiberen_US
dc.subjectFibersen_US
dc.titleThe prediction and evaluation of recycled polypropylene fiber and aggregate incorporated foam concrete using Artificial Neural Networksen_US
dc.typeArticle

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