Simulating pile load-settlement behavior from CPT data using intelligent computing
Analysis of pile load-settlement behavior is a complex problem due to the participation of many factors involved. This paper presents a new procedure based on artificial neural networks (ANNs) for simulating the load-settlement behavior of pile foundations embedded in sand and mixed soils (subjected...
| Main Authors: | , |
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| Format: | Journal Article |
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springer
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/39168 |
| _version_ | 1848755517827055616 |
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| author | Alkroosh, Iyad Nikraz, Hamid |
| author_facet | Alkroosh, Iyad Nikraz, Hamid |
| author_sort | Alkroosh, Iyad |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Analysis of pile load-settlement behavior is a complex problem due to the participation of many factors involved. This paper presents a new procedure based on artificial neural networks (ANNs) for simulating the load-settlement behavior of pile foundations embedded in sand and mixed soils (subjected to axial loads). Three ANN models have been developed, a model for bored piles and two other models for driven piles (a model for each of concrete and steel piles). The data used for development of the ANN models is collected from the literature and comprise a series of in-situ piles load tests as well as cone penetration test (CPT) results. The data of each model is divided into two subsets: Training set for model calibration and independent validation set for model verification. Predictions from the ANN models are compared with the results of experimental data and with predictions of number of currently adopted load-transfer methods. Statistical analysis is used to verify the performance of the models. The results indicate that the ANN model performs very well and able to predict the pile load-settlement behaviour accurately. |
| first_indexed | 2025-11-14T08:57:34Z |
| format | Journal Article |
| id | curtin-20.500.11937-39168 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:57:34Z |
| publishDate | 2011 |
| publisher | springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-391682017-09-13T16:05:06Z Simulating pile load-settlement behavior from CPT data using intelligent computing Alkroosh, Iyad Nikraz, Hamid Prediction – Pile load-settlement model – Artificial neural networks Analysis of pile load-settlement behavior is a complex problem due to the participation of many factors involved. This paper presents a new procedure based on artificial neural networks (ANNs) for simulating the load-settlement behavior of pile foundations embedded in sand and mixed soils (subjected to axial loads). Three ANN models have been developed, a model for bored piles and two other models for driven piles (a model for each of concrete and steel piles). The data used for development of the ANN models is collected from the literature and comprise a series of in-situ piles load tests as well as cone penetration test (CPT) results. The data of each model is divided into two subsets: Training set for model calibration and independent validation set for model verification. Predictions from the ANN models are compared with the results of experimental data and with predictions of number of currently adopted load-transfer methods. Statistical analysis is used to verify the performance of the models. The results indicate that the ANN model performs very well and able to predict the pile load-settlement behaviour accurately. 2011 Journal Article http://hdl.handle.net/20.500.11937/39168 10.2478/s13531-011-0029-2 springer restricted |
| spellingShingle | Prediction – Pile load-settlement model – Artificial neural networks Alkroosh, Iyad Nikraz, Hamid Simulating pile load-settlement behavior from CPT data using intelligent computing |
| title | Simulating pile load-settlement behavior from CPT data using intelligent computing |
| title_full | Simulating pile load-settlement behavior from CPT data using intelligent computing |
| title_fullStr | Simulating pile load-settlement behavior from CPT data using intelligent computing |
| title_full_unstemmed | Simulating pile load-settlement behavior from CPT data using intelligent computing |
| title_short | Simulating pile load-settlement behavior from CPT data using intelligent computing |
| title_sort | simulating pile load-settlement behavior from cpt data using intelligent computing |
| topic | Prediction – Pile load-settlement model – Artificial neural networks |
| url | http://hdl.handle.net/20.500.11937/39168 |