Prediction of Hybrid fibre-added concrete strength using artificial neural networks

dc.contributor.authorDemir A.
dc.date.accessioned2024-07-22T08:13:29Z
dc.date.available2024-07-22T08:13:29Z
dc.date.issued2015
dc.description.abstractFibre-added concretes are frequently used in large site applications such as slab and airports as well as in bearing system elements or prefabricated elements. It is very difficult to determine the mechanical properties of the fibre-added concretes by experimental methods in situ. The purpose of this study is to develop an artificial neural network (ANN) model in order to predict the compressive and bending strengths of hybrid fibre-added and non-added concretes. The strengths have been predicted by means of the data that has been obtained from destructive (DT) and non-destructive tests (NDT) on the samples. NDTs are ultrasonic pulse velocity (UPV) and Rebound Hammer Tests (RH). 105 pieces of cylinder samples with a dimension of 150 × 300 mm, 105 pieces of bending samples with a dimension of 100×100×400 mm have been manufactured. The first set has been manufactured without fibre addition, the second set with the addition of %0.5 polypropylene and %0.5 steel fibre in terms of volume, and the third set with the addition of %0.5 polypropylene, %1 steel fibre. The water/cement (w/c) ratio of samples parametrically varies between 0.3-0.9. The experimentally measured compressive and bending strengths have been compared with predicted results by use of ANN method. Copyright © 2015 Techno-Press, Ltd.
dc.identifier.DOI-ID10.12989/cac.2015.15.4.503
dc.identifier.issn15988198
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/16350
dc.language.isoEnglish
dc.publisherTechno-Press
dc.subjectBending (forming)
dc.subjectBending strength
dc.subjectConcretes
dc.subjectNeural networks
dc.subjectPolypropylenes
dc.subjectShotcreting
dc.subjectSteel fibers
dc.subjectTensile strength
dc.subjectUltrasonic testing
dc.subjectArtificial neural network models
dc.subjectCompressive
dc.subjectConcrete strength
dc.subjectExperimental methods
dc.subjectHybrid fibres
dc.subjectNon-destructive test
dc.subjectPrefabricated elements
dc.subjectUltrasonic pulse velocity
dc.subjectNondestructive examination
dc.titlePrediction of Hybrid fibre-added concrete strength using artificial neural networks
dc.typeArticle

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