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

Laman M., Uncuoglu E.

KUWAIT JOURNAL OF SCIENCE & ENGINEERING, vol.36, pp.33-52, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36
  • Publication Date: 2009
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.33-52
  • Erciyes University Affiliated: No


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 foundations in clay. The data used in the running of network models have been obtained from an extensive series of centrifuge model tests. The results indicate that the ANN model serves as a simple and reliable tool to predict the moment carrying capacity of pier foundations in saturated clay.