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This paper introduces Granular algorithm enhancing Material Point Method (MPM) that allows for simulation of granular flows in the quasi-static state, the moderate flow state and the disconnected flow state. The paper first shows the shortcomings of MPM algorithms in modelling the different states of granular flows. Next, it proposes Granular MPM, an enhancement that explicitly introduces the different states of granular flow into MPM and defines the rules for the transition between those states. Subsequently, the paper gives the algorithm and implementation for Granular MPM. The provided algorithm can enhance the common versions of MPM, including original MPM, Generalised Interpolation Material Point and Convected Particle Domain Interpolation. Finally, the paper evaluates Granular MPM and compares it with other available formulation based on: (i) an examination of the behaviour of granular points on a slope, (ii) a simulation of a granular flow over two disconnected inclined surfaces, (iii) a simulation of a silo filling and (iv) a simulation of Toyoura sand flow experiment. The results of Granular MPM simulations are significantly more realistic when compared to the results obtained by other available MPM formulations. The results also indicate that Granular MPM allows for more accurate replication of steady state flows and reduces the grid dependency of MPM when modelling the disconnected flow state, as the initial contact is independent from the grid size. (C) 2021 The Author(s). Published by Elsevier Ltd.
- Granular flow
- Continuum mechanics
- Material point method
FingerprintDive into the research topics of 'From solid to disconnected state and back: Continuum modelling of granular flows using material point method'. Together they form a unique fingerprint.
- 1 Finished
Progressive failure and post-failure modelling of slopes with Generalized Interpolation Material Point Method
Sołowski, W., Tran, Q. A., Lei, X. & Seyedan, S.
01/09/2015 → 31/08/2019
Project: Academy of Finland: Other research funding
Seyedan, Seyedmohammadjavad (Recipient), 2022
Prize: Award or honor granted for a specific workFile