Published 2025-02-15

Triaxial stress-strain data of granular materials via discrete element modeling

Data source language:

  • English

Data reference:

  • Qu, T., Di, S., Feng, Y. T., Wang, M., & Zhao, T. (2021). Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning. International Journal of Plasticity, 144, 103046.

Contributors of raw data:

  • Tongming Qu, Shaocheng Di, Y.T. Feng, Min Wang, Tingting Zhao

Data description:

  • All the training data of triaxial testing is provided by discrete element modelling wherein a total of 4037 spherical particles with their radii uniformly distributed between 2mm and 4mm are used to generate the specimens. These specimens are isotropically consolidated to a confining pressure of 200 kPa. The normal and tangential contact stiffnesses are 105 N/m and 5 × 104 N/m, respectively. The interparticle frictional coefficient is 0.5, the particle density is 2600 kg/m3, the local damping coefficient is 0.5.

Keywords and subjects:

  • Constitutive models, Stress-strain relations, Triaxial tests, discrete element method

Availability:

  • publicly accessible

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