Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7749-2021
https://doi.org/10.5194/gmd-14-7749-2021
Model description paper
 | 
22 Dec 2021
Model description paper |  | 22 Dec 2021

An explicit GPU-based material point method solver for elastoplastic problems (ep2-3De v1.0)

Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov

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Cited articles

Alejano, L. R. and Bobet, A.: Drucker–Prager Criterion, Rock Mech. Rock Eng., 45, 995–999, https://doi.org/10.1007/s00603-012-0278-22012. a
Alkhimenkov, Y., Räss, L., Khakimova, L., Quintal, B., and Podladchikov, Y.: Resolving wave propagation in anisotropic poroelastic media using graphical processing units (GPUs), J. Geophys. Res.-Sol. Ea., 126, e2020JB021175, https://doi.org/10.1029/2020JB021175, 2021. a, b, c, d, e
Anderson, C. E.: An overview of the theory of hydrocodes, Int. J. Impact Eng., 5, 33–59, https://doi.org/10.1016/0734-743X(87)90029-7, 1987. a
Bandara, S. and Soga, K.: Coupling of soil deformation and pore fluid flow using material point method, Comput. Geotech., 63, 199–214, https://doi.org/10.1016/j.compgeo.2014.09.009, 2015. a
Bandara, S., Ferrari, A., and Laloui, L.: Modelling landslides in unsaturated slopes subjected to rainfall infiltration using material point method, Int. J. Numer. Anal. Met., 40, 1358–1380, https://doi.org/10.1002/nag.2499, 2016. a, b
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Short summary
We propose an implementation of the material point method using graphical processing units (GPUs) to solve elastoplastic problems in three-dimensional configurations, such as the granular collapse or the slumping mechanics, i.e., landslide. The computational power of GPUs promotes fast code executions, compared to a traditional implementation using central processing units (CPUs). This allows us to study complex three-dimensional problems tackling high spatial resolution.
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