Using ANN and ANFIS to predict the mechanical and chloride permeability properties of concrete containing GGBFS and CNI

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dc.contributor.authorBoga, Ahmet Raif
dc.contributor.authorOzturk, Murat
dc.contributor.authorTopcu, Ilker Bekir
dc.date.accessioned2020-03-26T18:44:22Z
dc.date.available2020-03-26T18:44:22Z
dc.date.issued2013
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis study examined the effects of using ground-granulated blast furnace slag (GGBFS) and calcium nitrite-based corrosion inhibitor (CNI) on the mechanical and durability properties of concrete (compressive strength, splitting tensile strength, chloride ion permeability). Concrete specimens containing only blast furnace slag, calcium nitrite-based corrosion inhibitors, and a combination of these components in different ratios were produced with reference specimens. On the 28th, 56th and 90th days following production, tests were administered that involved allowing all specimens to cure via two different methods, which include the condition under uncontrolled relative humidity (air cure - K1) and temperature, as well as the standard cure condition (water cure - K2). The effects of cure type and curing period on concrete containing GGBFS and CNI were determined. In total, 162 tests were administered for compressive strength, splitting tensile strength, and chloride ion permeability (54 tests each). In addition, the formulated four-layered artificial neural network method (ANN) and the adaptive neuro-fuzzy inference system (ANFIS) were trained using 120 of the 162 specimens. The methods were tested with the other 42 specimens for each parameter. Increasing the curing periods and applying the water cure instead of the air cure on concrete containing GGBFS and CNI resulted in significant improvement of the mechanical properties and chloride ion permeability of the concrete. It was also determined that experimental data can be estimated to a notably close extent via the ANN and ANFIS models. (c) 2012 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.compositesb.2012.05.054en_US
dc.identifier.endpage696en_US
dc.identifier.issn1359-8368en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage688en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.compositesb.2012.05.054
dc.identifier.urihttps://hdl.handle.net/20.500.12395/29984
dc.identifier.volume45en_US
dc.identifier.wosWOS:000314193200073en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCI LTDen_US
dc.relation.ispartofCOMPOSITES PART B-ENGINEERINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectCeramic-matrix composites (CMCs)en_US
dc.subjectElectrical propertiesen_US
dc.subjectStrengthen_US
dc.subjectComputational modelingen_US
dc.titleUsing ANN and ANFIS to predict the mechanical and chloride permeability properties of concrete containing GGBFS and CNIen_US
dc.typeArticleen_US

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