Skip to the content

Lateral load bearing capacity model for piles in cohesive soils

Ahangar Asr, Alireza, Javadi, A, Johari, A and Chen, Y 2014, 'Lateral load bearing capacity model for piles in cohesive soils' , in: Proceedings of the 22nd UK National Conference of the Association for Computational Mechanics in Engineering , University of Exeter, pp. 264-267.

[img] PDF - Published Version
Restricted to Repository staff only

Download (180kB) | Request a copy

Abstract

In this research work an evolutionary approach is proposed to develop a structured polynomial model for predicting the lateral load bearing capacity of piles in undrained conditions. The proposed polynomial regression technique is an evolutionary data mining methodology that generates a transparent and structured representation of the behaviour of a system directly from raw data. It can operate on large quantities of data in order to capture nonlinear and complex relationships between contributing variables. Field measurement data from literature was used to develop the proposed model. Comparison of the proposed model predictions with the field data shows that the EPR model is capable of capturing, predicting and generalising predictions to unseen data cases the lateral load bearing capacity of piles with very high accuracy. The merits and advantages of the proposed methodology are also discussed.

Item Type: Book Section
Editors: Javadi, A and Hussain, MS
Additional Information: 2nd - 4th April 2014 College of Engineering, Mathematics and Physical Sciences, University of Exeter, UK
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Proceedings of the 22nd UK Conference of the Association for Computational Mechanics in Engineering
Publisher: University of Exeter
ISBN: 9780902746305
Funders: Non funded research
Depositing User: Dr Alireza Ahangar Asr
Date Deposited: 15 Dec 2015 10:33
Last Modified: 15 Dec 2015 10:33
URI: http://usir.salford.ac.uk/id/eprint/37442

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)

Downloads

Downloads per month over past year