An implicit Material Point Method applied to granular flows
Tipus de documentComunicació de congrés
Condicions d'accésAccés obert
The main objective of this work lies in the development of a variational implicit Material Point Method (MPM), implemented in the open source Kratos Multiphysics framework. The ability of the MPM technique to solve large displacement and large deformation problems is widely recognised and its use ranges over many problems in industrial and civil engineering. In the current work the continuum based implicit MPM is applied to engineering applications, where granular material flow is involved. For the resolution of the length and time scale of these particular problems, both continuum and discrete models are typically used. Even if discrete techniques predict more feasible results, nowadays, their use is limited to the investigation of element tests of particles, or to the simulation of reduced systems, not allowing to make important decisions in the analysis and design of granular processes. Some advantages of MPM over discrete methods are tested, such as, the ability to simulate granular flow at the large scale with acceptable computational cost and the capability to get information of stress and strain state in a more straightforward way. The focus of this paper is a comparative study between an irreducible and a mixed formulation, both implemented in the MPM code, to assess the improvement in accuracy and reliability of the numerical results when the latter formulation is adopted.
CitacióIaconeta, I., Larese, A., Rossi, R., Oñate, E. An implicit Material Point Method applied to granular flows. A: International Conference on The Material Point Method for Modelling Large Deformation and Soil–Water–Structure Interaction. "Procedia Engineering, volume 175: proceedings of the 1st International Conference on the Material Point Method (MPM 2017), 10–13 January 2017, Delft, The Netherlands". Delft: Elsevier, 2017, p. 226-232.
Versió de l'editorhttp://www.sciencedirect.com/science/article/pii/S1877705817300176