The Application of Improved Duncan-Chang Model in Unloading Soil

Yi He*, 1, 2, Xuejun Chen1, 3
1 Faculty of Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China
1 Civil Engineering Depart-ment, Luoyang Institute of Science and Technology, Luoyang 471023, China
1 Civil Engineering Department, Guilin University of Technology, Guilin 541004, China

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© 2014 He and Chen;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the 12 Jiangan Road Guilin, Guilin University of Technology, Guilin 541004, China; Tel: +8613907738446; E-mail:


On the basis of the representative samples of silty clay found in Wuhan, China, the lateral unloading of soil’s stress path produced by excavating foundation pit engineering, was simulated by triaxial experiment. A series of consolidated- drained true triaxial test and normal triaxial test were conducted. According to the results of tests, the parameter of the Duncan-Chang Model was determined. A modulus formula was used for the foundation soil in the lateral unloading stress path tests to replace the modulus formula of Duncan-Chang Model based on the σ3 =const . Moreover, the Duncan- Chang hyperbola nonlinear elastic constitutive model was used to simulate the plane strain test. A method to improve the ability of Duncan-Chang model in order to take into account the effects of the intermediate principal stress on the strength and deformation was presented as well as all the model parameters were also determined. The adaptability of the model for unloading the stress path was verified by comparing the theoretical stress-strain relationship and empirical stress-strain relationship.

Keywords: Foundation pit excavation, lateral unload, improved Duncan-Chang model.