Journal of Food, Agriculture and Environment

Models to predict the elastic parameters of soil-rock mixture

Author(s):

Shun-qing Liu ^{1, 2}, Bao-ning Hong ^{1, 2}*, Tao Cheng ^{1, 2}, Xin Liu ^{1, 2}

Recieved Date: 2013-01-12, Accepted Date: 2013-04-26

Abstract:

To calculate the elastic deformations experienced by soil-rock mixtures subjected to static or dynamic loads, knowledge of their elastic parameters is required. The elastic parameters are normally evaluated in the laboratory using conventional triaxial compressive tests on cylindrical samples. For meaningful test results, it is necessary to maintain a ratio of sample diameter to maximum particle size of approximately 6 to 1 or greater. However soil-rock mixtures have oversized rock particles that make it impossible to test them in the conventional triaxial apparatus. This study presents the application of theoretical models developed by Hashin and Greszczuk that calculate the elastic parameters of a composite made of an elastic matrix containing large rock dispersed particles. The Hashin and Greszczuk models require only knowledge of elastic parameters of the matrix (which can be obtained form conventional compression tests) coupled with the concentration by volume or weight of the large rock particles in order to calculate the elastic parameters of soil-rock mixtures. The Hashin and Greszczuk models were firstly demonstrated by laboratory test data. And then particle flow code biaxial tests were used to demonstrated the theoretical models. It was found by them that the Hashin model predicted well the measured elastic parameters of the soil-rock mixtures. But the Greszczuk model was relatively poor to predict the results. Conventional tests can be made easily to the clay matrix, by using the theoretical models presented and demonstrated in this study, the elastic parameters of soil-rock mixtures can now be determined easily in the laboratory.

Keywords:

Models, elastic parameter, soil-rock mixture, particle flow code, triaxial compressive test

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Journal: Journal of Food, Agriculture and Environment
Year: 2013
Volume: 11
Issue: 2
Category: Environment
Pages: 1272-1276

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