Evaluation of soil-concrete interface shear strength based on LS-SVM
Chunshun Zhang,Jian Ji,Yilin Gui,Jayantha Kodikara,Sheng-Qi Yang,Lei He
Abstract
The soil-concrete interface shear strength, although has been extensively studied, is still difficult to predict as a result of the dependence on many factors such as normal stresses, surface roughness, particle sizes, moisture contents, dilation angles of soils, etc. In this study, a well-known rigorous statistical learning approach, namely the least squares support vector machine (LS-SVM) realized in a ubiquitous spreadsheet platform is firstly used in estimating the soil-structure interface shear strength. Instead of studying the complicated mechanism, LSSVM enables to explore the possible link between the fundamental factors and the interface shear strengths, via a sophisticated statistic approach. As a preliminary investigation, the authors study the expansive soils that are found extensively in most countries. To reduce the complexity, three major influential factors, e.g., initial moisture contents, initial dry densities and normal stresses of soils are taken into account in developing the LS-SVM models for the soilconcrete interface shear strengths. The predicted results by LS-SVM show reasonably good agreement with experimental data from direct shear tests.
(1) Chunshun Zhang, Sheng-Qi Yang — State Key Lab for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, P.R. China
(2) Jian Ji — Key Lab of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing, P.R. China
(3) Chunshun Zhang, Jian Ji, Jayantha Kodikara — Department of Civil Engineering, Monash University, Australia
(4) Yilin Gui — School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
(5) Lei He — School of Civil Engineering, Southeast University, Nanjing, P.R. China.
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