Geomechanics and Engineering

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Application of artificial neural networks in settlement prediction of shallow foundations on sandy soils

  • Luat, Nguyen-Vu (Department of Architectural Engineering, Sejong University) ;
  • Lee, Kihak (Department of Architectural Engineering, Sejong University) ;
  • Thai, Duc-Kien (Department of Civil and Environmental Engineering, Sejong University)
  • Received : 2019.08.27
  • Accepted : 2020.02.06
  • Published : 2020.03.10
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Abstract

This paper presents an application of artificial neural networks (ANNs) in settlement prediction of a foundation on sandy soil. In order to train the ANN model, a wide experimental database about settlement of foundations acquired from available literatures was collected. The data used in the ANNs model were arranged using the following five-input parameters that covered both geometrical foundation and sandy soil properties: breadth of foundation B, length to width L/B, embedment ratio Df/B, foundation net applied pressure qnet, and average SPT blow count N. The backpropagation algorithm was implemented to develop an explicit predicting formulation. The settlement results are compared with the results of previous studies. The accuracy of the proposed formula proves that the ANNs method has a huge potential for predicting the settlement of foundations on sandy soils.

Keywords

Acknowledgement

Supported by : Ministry of Land, Infrastructure and Transport of Korean Government

The research described in this paper was financially supported by Ministry of Land, Infrastructure and Transport of Korean Government (Grant 20CTAP-C143093-03).

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