Prediction of swelling pressures of expansive soils using artificial neural networks

  • Authors:

  • S. Banu Ikizler;Mustafa Aytekin;Mustafa Vekli;Fikret Kocabaş

  • Affiliations:

  • Civil Engineering Department, Karadeniz Technical University, Trabzon 61080, Turkey;Civil Engineering Department, Karadeniz Technical University, Trabzon 61080, Turkey;Civil Engineering Department, Bozok University, Yozgat, Turkey;Civil Engineering Department, Bartın University, Bartın, Turkey

  • Venue:
  • Advances in Engineering Software
  • Year:
  • 2010

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Abstract

Swelling behavior of expansive soil is a complicated phenomenon. In order to cope with the complications in describing the swelling behavior of expansive soil, researchers developed alternative approaches. In this paper, the prediction model of transmitted lateral swelling pressure, and vertical swelling pressures on a retaining structure was developed using artificial neural network (ANN) approach. In the first stage of this study, the lateral and vertical swelling pressures were measured with different thicknesses of expanded polystyrene (EPS) geofoam placed between one of the vertical walls of the steel testing box and the expansive soil. Then, artificial neural network was trained using these pressures for prediction transmitted lateral swelling pressure, and vertical swelling pressures on a retaining structure. Results obtained from this study showed that neural network-based prediction models could satisfactorily be used in obtaining the swelling pressures of the expansive soils.