Issue |
MATEC Web Conf.
Volume 337, 2021
PanAm-Unsat 2021: 3rd Pan-American Conference on Unsaturated Soils
|
|
---|---|---|
Article Number | 02005 | |
Number of page(s) | 8 | |
Section | Constitutive and Numerical Modeling | |
DOI | https://doi.org/10.1051/matecconf/202133702005 | |
Published online | 26 April 2021 |
Examining the predictive capabilities of a bounding surface plasticity-based hyperelastic constitutive model for unsaturated granular soils
1 Department of Engineering, Cambridge University, Civil Engineering Building 7a, JJ Thomson Avenue, Cambridge, UK, CB3 0FA
2 800 West University Parkway, Department of Engineering, Utah Valley University, Orem, UT, USA, 84058
3 301 DuPont Hall, Department of Civil and Environmental Engineering, University of Delaware, Newark, DE, USA, 19716
* Corresponding author: kmanahiloh@uvu.edu
The performance of a recently developed state-dependent constitutive model for unsaturated granular soils is evaluated. The model employs the Bounding Surface plasticity framework and evaluates elastic strains assuming hyperelastic behavior. To realistically simulate the deformation of unsaturated granular soils, the mechanical behavior was modeled without a purely elastic component. The inherent hydro-mechanical coupling was realized by introducing a Bishop-type effective stress, an appropriate work-conjugate variable, and a soil-water characteristic curve function. Relevant details about the model development, parameter estimation, and the assessment of the model’s predictive capabilities are presented. The model performance is evaluated with experimental data obtained for drained and constant-water stress paths. With a given a set of parameter values, the model realistically simulates the main features that characterize the shear and volumetric behavior of unsaturated granular soils over a wide range of matric suction, density, and net confining pressure. This is found to be true for both drained and constant-water stress paths.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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