Modeling with ANN and effect of pumice aggregate and air entrainment on the freeze-thaw durabilities of HSC

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dc.authoridTurkmen, Ibrahim/0000-0001-7560-0535
dc.authoridKARAKOÇ, MEHMET BURHAN/0000-0002-6954-0051
dc.authorwosidTurkmen, Ibrahim/AAH-1541-2019
dc.authorwosidKARAKOÇ, MEHMET BURHAN/ABG-5446-2020
dc.contributor.authorKarakoc, Mehmet Burhan
dc.contributor.authorDemirboga, Ramazan
dc.contributor.authorTurkmen, Ibrahim
dc.contributor.authorCan, Ibrahim
dc.date.accessioned2024-08-04T21:00:01Z
dc.date.available2024-08-04T21:00:01Z
dc.date.issued2011
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe objective of this work is to calculate the compressive strength, ultrasound pulse velocity (UPV), relative dynamic modulus of elasticity (RDME) and porosity induced into concrete during freezing and thawing. Freeze-thaw durability of concrete is of great importance to hydraulic structures in cold areas. In this paper, freezing of pore solution in concrete exposed to a freeze-thaw cycle is studied by following the change of concrete some mechanical and physical properties with freezing temperatures. The effects of pumice aggregate (PA) ratios on the high strength concrete (HSC) properties were studied at 28 days. PA replacements of fine aggregate (0-2 mm) were used: 10%, 20%, and 30%. The properties examined included compressive strength, UPV and RDME properties of HSC. Results showed that compressive strength, UPV and RDME of samples were decreased with increase in PA ratios. Test results revealed that HSC was still durable after 100, 200 and 300 cycles of freezing and thawing in accordance with ASTM C666. After 300 cycles, HSC showed a reduction in compressive strength between 6% and 21%, and reduction in RDME up to 16%. For 300 cycles, the porosity was increased up to 12% for HSC with PA. In this paper, feed-forward artificial neural networks (ANNs) techniques are used to model the relative change in compressive strength and relative change in UPV in cyclic thermal loading. Then genetic algorithms are applied in order to determine optimum mix proportions subjected to 300 thermal cycling. (C) 2011 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipTurkey Sciences and Research Council of Turkey (TUBITAK) [106M014]en_US
dc.description.sponsorshipThe authors are grateful to the Turkey Sciences and Research Council of Turkey (TUBITAK) for their financial support for this project (106M014).en_US
dc.identifier.doi10.1016/j.conbuildmat.2011.04.068
dc.identifier.endpage4249en_US
dc.identifier.issn0950-0618
dc.identifier.issn1879-0526
dc.identifier.issue11en_US
dc.identifier.startpage4241en_US
dc.identifier.urihttps://doi.org/10.1016/j.conbuildmat.2011.04.068
dc.identifier.urihttps://hdl.handle.net/11616/103705
dc.identifier.volume25en_US
dc.identifier.wosWOS:000293319600019en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherElsevier Sci 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.subjectFreeze-thawen_US
dc.subjectPumice aggregateen_US
dc.subjectHigh strength concreteen_US
dc.subjectCompressive strengthen_US
dc.subjectUltrasound pulse velocityen_US
dc.subjectArtificial neural networken_US
dc.titleModeling with ANN and effect of pumice aggregate and air entrainment on the freeze-thaw durabilities of HSCen_US
dc.typeArticleen_US

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