Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/33019
DC Field | Value | Language |
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dc.contributor.author | Braun, Kevin T. | - |
dc.contributor.author | Markou, George | - |
dc.contributor.author | Jacobsz, S. W. | - |
dc.contributor.author | Calitz, Duan | - |
dc.date.accessioned | 2024-10-02T11:03:59Z | - |
dc.date.available | 2024-10-02T11:03:59Z | - |
dc.date.issued | 2024-06-01 | - |
dc.identifier.citation | Structures, 2024, vol.64 | en_US |
dc.identifier.issn | 23520124 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/33019 | - |
dc.description.abstract | The design of pile foundations that are expected to develop significant lateral loading is a complex procedure that requires the development of objective and accurate design formulae that will not be based on semi-empirical know-how. For this reason, the main objective of this research work is to develop predictive models that will be able to compute the overall mechanical response of reinforced concrete (RC) piles embedded in unsaturated clay. To achieve this goal, experimental data, and advanced nonlinear 3D detailed finite element (FE) modelling were used to construct datasets comprising multiple results related to the ultimate capacity and corresponding horizontal deformation of RC piles that are loaded horizontally until failure. In total, three datasets were developed and then used to train and test predictive models through the use of various machine learning (ML) algorithms. After successfully developing various predictive models, an out-of-sample dataset was developed and used to further validate the accuracy and extendibility of the predictive models. Finally, the most accurate ML-generated predictive model was used to predict the mechanical response of a RC pile embedded in unsaturated clay that was experimentally tested. The ability of the proposed predictive model is demonstrated through this pilot research work. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Structures | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Soil-structure interaction | en_US |
dc.subject | Machine learning algorithms | en_US |
dc.subject | Predictive models | en_US |
dc.subject | Reinforced concrete pile | en_US |
dc.subject | Horizontal load-displacement response | en_US |
dc.title | Developing predictive models for the load-displacement response of laterally loaded reinforced concrete piles in stiff unsaturated clay using machine learning algorithms | en_US |
dc.type | Article | en_US |
dc.collaboration | University of Pretoria | en_US |
dc.collaboration | Neapolis University Pafos | en_US |
dc.collaboration | SRK Consulting | en_US |
dc.subject.category | Computer and Information Sciences | en_US |
dc.subject.category | ENGINEERING AND TECHNOLOGY | en_US |
dc.subject.category | Civil Engineering | en_US |
dc.subject.category | Other Engineering and Technologies | en_US |
dc.journals | Open Access | en_US |
dc.country | South Africa | en_US |
dc.country | Cyprus | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1016/j.istruc.2024.106532 | en_US |
dc.identifier.scopus | 2-s2.0-85193046284 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85193046284 | - |
dc.relation.volume | 64 | en_US |
cut.common.academicyear | empty | en_US |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.fulltext | With Fulltext | - |
crisitem.journal.journalissn | 2352-0124 | - |
crisitem.journal.publisher | Elsevier | - |
crisitem.author.dept | Department of Civil Engineering and Geomatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0002-6891-7064 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Άρθρα/Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Developing predictive models.pdf | 10 MB | Adobe PDF | View/Open |
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