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Appl. Sci. 2018, 8(8), 1395; https://doi.org/10.3390/app8081395

Evaluation of the Undrained Shear Strength of Organic Soils from a Dilatometer Test Using Artificial Neural Networks

1
Faculty of Civil and Environmental Engineering, Warsaw University of Life Sciences–SGGW, Nowoursynowska 159 St., 02-776 Warsaw, Poland
2
Tokai University, 3-20-1, Orido Shimizu-ku, Shizuoka 424-8610, Japan
3
Faculty of Civil and Environmental Engineering, Bialystok University of Technology, Wiejska 45E St., 15-351 Bialystok, Poland
*
Author to whom correspondence should be addressed.
Received: 23 July 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 17 August 2018
(This article belongs to the Section Materials)
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Abstract

The undrained shear strength of organic soils can be evaluated based on measurements obtained from the dilatometer test using single- and multi-factor empirical correlations presented in the literature. However, the empirical methods may sometimes show relatively high values of maximum relative error. Therefore, a method for evaluating the undrained shear strength of organic soils using artificial neural networks based on data obtained from a dilatometer test and organic soil properties is presented in this study. The presented neural network, with an architecture of 5-4-1, predicts the normalized undrained shear strength based on five independent variables: the normalized net value of a corrected first pressure reading (pouo)/σ′v, the normalized net value of a corrected second pressure reading (p1uo)/σ′v, the organic content Iom, the void ratio e, and the stress history indictor (oc or nc). The neural model presented in this study provided a more reliable prediction of the undrained shear strength in comparison to the empirical methods, with a maximum relative error of ±10%. View Full-Text
Keywords: organic soils; undrained shear strength; dilatometer test; artificial neural networks organic soils; undrained shear strength; dilatometer test; artificial neural networks
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Lechowicz, Z.; Fukue, M.; Rabarijoely, S.; Sulewska, M.J. Evaluation of the Undrained Shear Strength of Organic Soils from a Dilatometer Test Using Artificial Neural Networks. Appl. Sci. 2018, 8, 1395.

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