Avalanche and landslide simulation using the material point method: flow dynamics and force interaction with structures

Mast, Carter M.; Arduino, Pedro; Miller, Gregory R.; Mackenzie‐Helnwein, Peter

doi:10.1007/s10596-014-9428-9

Cited by 72 publications

(35 citation statements)

References 27 publications

(34 reference statements)

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“…MPM has been able to simulate a diverse array of complex problems. A partial list includes modeling complex biological structures [1] (including resolving cellular structure of wood [2][3][4]), granular materials [5], land slides and avalanches [6], explosive welding [7], cutting simulations [8,9], sea ice dynamics [10], snow dynamics [11] and fracture simulations [12,13].…”

Section: Introductionmentioning

confidence: 99%

A new method for material point method particle updates that reduces noise and enhances stability

Hammerquist

Nairn

2017

Computer Methods in Applied Mechanics and Engineering

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Current material point method (MPM) particle updates use a PIC approach, a FLIP approach, or a linear combination of PIC and FLIP. A PIC update filters velocity in each time step, which causes unwanted numerical diffusion, while FLIP eliminates that diffusion, but may retain too much noise. This paper develops a new particle update termed XPIC(m) (for eXtended PIC of order m) because it generalizes PIC updates. XPIC(1) is identical to current PIC methods, but higher orders of XPIC(m) address the over filtering and numerical diffusion of PIC, while still filtering out noise caused by the nontrivial null space of the extrapolation matrix used in MPM. As m → ∞, XPIC(m) converges to a modified FLIP update with orthogonal removal of null space noise. The frequency response and filtering properties of XPIC(m) are investigated and several numerical examples demonstrate its advantages over other update methods.

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Section: Introductionmentioning

confidence: 99%

A new method for material point method particle updates that reduces noise and enhances stability

Hammerquist

Nairn

2017

Computer Methods in Applied Mechanics and Engineering

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“…For example, explicit nature of the presented MPM formulation only allows for adoptation of linear elements; however, the first derivative of shape functions for these elements are discontinuous which can lead to numerical noise in the calculation known as particle crossing problem [3]. Several improvements including using Generalized Interpolation [1], Spline shape function [2], anti-locking approach [25,26] and mixed integration [6] were proposed to treat such problem. Here, the computationally efficient method of mixed integration was implemented.…”

Section: Materials Point Methodsmentioning

confidence: 99%

Numerical evaluation of mean-field homogenisation methods for predicting shale elastic response

2016

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Numerical evaluation of mean-field homogenisation methods for predicting shale elastic responseReceived: date / Accepted: date Abstract Homogenisation techniques have been successfully used to estimate the mechanical response of synthetic composite materials, due to their ability to relate the macroscopic mechanical response to the material microstructure. The adoption of these mean-field techniques in geo-composites such as shales is attractive, partly because of the practical difficulties associated with the experimental characterisation of these highly heterogeneous materials. In this paper, numerical modelling has been undertaken to investigate the applicability of homogenisation methods in predicting the macroscopic, elastic response of clayey rocks. The rocks are considered as two-level composites consisting of a porous clay matrix at the first level and a matrix-inclusion morphology at the second level . The simulated microstructures ranged from a simple system of one inclusion/void embedded in a matrix to complex, random microstructures. The effectiveness and limitations of the different homogenisation schemes were demonstrated through a comparative evaluation of the macroscopic elastic response, illustrating the appropriate schemes for upscaling the microstructure of shales. Based on the numerical simulations and existing experimental observations, a randomly distributed pore system for the micro-structure of porous clay matrix has been proposed which can be used for the subsequent development and validation of shale constitutive models and their flow properties. Finally, the homogenisation techniques were used to predict the experimental measurements of elastic response. The developed methodology is proved to be a valuable too for verifying the accuracy and performance of the homogenisation techniques.

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“…Most MPM modeling uses a regular grid of equallysized cells. Regular grids are used because of simplicity afforded to some calculations and because they are needed in problems with large movement through the grid [19,21,26,41]. The literature on mesh refinement in MPM is sparse.…”

Section: Mpm Gridmentioning

confidence: 99%

Modeling nanoindentation using the Material Point Method

Hammerquist

Nairn

2018

J. Mater. Res.

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Avalanche and landslide simulation using the material point method: flow dynamics and force interaction with structures

Cited by 72 publications

References 27 publications

A new method for material point method particle updates that reduces noise and enhances stability

A new method for material point method particle updates that reduces noise and enhances stability

Numerical evaluation of mean-field homogenisation methods for predicting shale elastic response

Modeling nanoindentation using the Material Point Method

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