Prediction of bearing capacity of circular footings on soft clay stabilized with granular soil

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dc.authoridDemir, Ahmet/0000-0003-3559-8113
dc.authoridYildiz, Abdulazim/0000-0002-6755-1902
dc.contributor.authorOrnek, Murat
dc.contributor.authorLaman, Mustafa
dc.contributor.authorDemir, Ahmet
dc.contributor.authorYildiz, Abdulazim
dc.date.accessioned2025-01-06T17:36:39Z
dc.date.available2025-01-06T17:36:39Z
dc.date.issued2012
dc.description.abstractThe shortage of available and suitable construction sites in city centres has led to the increased use of problematic areas, where the bearing capacity of the underlying deposits is very low. The reinforcement of these problematic soils with granular fill layers is one of the soil improvement techniques that are widely used. Problematic soil behaviour can be improved by totally or partially replacing the inadequate soils with layers of compacted granular fill. The study presented herein describes the use of artificial neural networks (ANNs), and the multi-linear regression model (MLR) to predict the bearing capacity of circular shallow footings supported by layers of compacted granular fill over natural clay soil. The data used in running the network models have been obtained from an extensive series of field tests, including large-scale footing diameters. The field tests were performed using seven different footing diameters, up to 0.90 m, and three different granular fill layer thicknesses. The results indicate that the use of granular fill layers over natural clay soil has a considerable effect on the bearing capacity characteristics and that the ANN model serves as a simple and reliable tool for predicting the bearing capacity of circular footings in stabilized natural clay soil. (C) 2012. The Japanese Geotechnical Society. Production and hosting by Elsevier B.V. All rights reserved.
dc.description.sponsorshipTUBITAK (Scientific and Technological Research Council of Turkey) [106M496]; Cukurova University Scientific Research Project Directorate [MMF2006D28]
dc.description.sponsorshipThe work presented in this paper was carried out with funding from TUBITAK (Scientific and Technological Research Council of Turkey), Grant no. 106M496, and the Cukurova University Scientific Research Project Directorate, Grant no. MMF2006D28.
dc.identifier.doi10.1016/j.sandf.2012.01.002
dc.identifier.endpage80
dc.identifier.issn0038-0806
dc.identifier.issn2524-1788
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84864853226
dc.identifier.scopusqualityQ1
dc.identifier.startpage69
dc.identifier.urihttps://doi.org/10.1016/j.sandf.2012.01.002
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1929
dc.identifier.volume52
dc.identifier.wosWOS:000305314700006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherJapanese Geotechnical Soc
dc.relation.ispartofSoils and Foundations
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectBearing capacity
dc.subjectClay
dc.subjectField test
dc.subjectFooting
dc.subjectGranular material
dc.subjectLoad test
dc.subjectNeural networks
dc.titlePrediction of bearing capacity of circular footings on soft clay stabilized with granular soil
dc.typeArticle

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