Evaluation of the Change in Undrained Shear Strength in Cohesive Soils due to Principal Stress Rotation Using an Artificial Neural Network

被引：0

作者：

Wrzesinski, Grzegorz ^{[1
]}

Sulewska, Maria Jolanta ^{[2
]}

Lechowicz, Zbigniew ^{[1
]}

机构：

[1] Warsaw Univ Life Sci, Fac Civil & Environm Engn, Nowoursynowska 159 St, PL-02776 Warsaw, Poland

[2] Bialystok Tech Univ, Fac Civil & Environm Engn, Wiejska 45E St, PL-15351 Bialystok, Poland

来源：

APPLIED SCIENCES-BASEL | 2018年 / 8卷 / 05期

关键词：

artificial neural network analysis; cohesive soil; normalized undrained shear strength; principal stress rotation; torsional shear hollow cylinder test; BEHAVIOR; ANISOTROPY; APPARATUS; KAOLIN;

D O I：

10.3390/app8050781

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

This paper presents a method describing the application of artificial neural networks to evaluate the change in undrained shear strength in cohesive soils due to principal stress rotation. For analysis, the results of torsional shear hollow cylinder (TSHC) tests were used. An artificial neural network with an architecture of 7-6-1 was able to predict the real value of normalized undrained shear strength, tau(fu)/sigma(v') based on soil type, over-consolidation ratio (OCR), plasticity index, I-p, and the angle of principal stress rotation, alpha, with an average relative error of around +/- 3%, and a single maximum value of relative error around 6%.

引用

页数：12

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