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Volume :36 Issue : 1 2009      Add To Cart                                                                    Download

Prediction of the moment capacity of pier foundations in clay using neural networks

Auther : MUSTAFA LAMAN AND ERDAL UNCUOGLU

Cukurova University, Civil Engineering Department, 01330 Baleali, Adara, Turkey.

Email: mlaman@cukurova.edu.tr

 

 

Abstract

 

Short piers rely heavily on passive soil resistance and are consequently often referred to as side-bearing foundations. Methods based on a combination of limit state analyses, small-scale modelling or field observations have been used in design. Relatively little centrifuge modelling work at the appropriate stress levels has been reported on the moment capacity problem. The work presented herein describes the use of artificial neural networks (ANNs) for prediction of moment carrying capacity of short pier foundation in clay. The data used in running of network models have been obtained from extensive series of centrifuge model tests. The results indicate that the ANN model serves as simple and reliable tool to predict the moment carrying capacity of pier foundations in saturated clay.

 

Keywords: Centrifuge modelling, clay, foundation, model tests, neural network.

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