2020-01-17T18:29:46Z
https://zenodo.org/oai2d
oai:zenodo.org:546611
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Cheng, XueSong
Zheng, Gang
Soga, Kenichi
Bandara, Samila
Kumar, Krishna
Diao, Yu
Xu, Jie
2015-07-02
Tunnel collapse presents a serious threat to the safety of urban construction. The traditional approach adopted to assess this
risk is to evaluate the factor of safety against failure. However, this analysis only determines on whether the tunnel will col-
lapse or not, and does not provide information on the magnitude of the post-failure behavior (for example, catastrophic or pro-
gressive) if the tunnel collapse occurs. In this study, a meshless method based on the material point method (MPM) was used
to investigate the post-failure behavior of tunnel heading collapse in two-dimensional plane-strain conditions. The capability
and accuracy of MPM were verified by comparing the elicited results to centrifuge test data and to analytical solutions ob-
tained from limit state methods. MPM simulations were conducted at different soil conditions (clay or sand) and profiles (ho-
mogenous or linear increasing strength) as well as at different tunnel geometries (i.e. tunnel depth and unlined length). The
differences in the post-failure behavior and mechanisms are examined and reported.
https://zenodo.org/record/546611
10.1007/s11431-015-5874-4
oai:zenodo.org:546611
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
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http://creativecommons.org/licenses/by/4.0/legalcode
Science China: Technological Sciences 58(12) 2139-2153
Tunnel stability
Collapse mechanism
material point method
large deformation
Post-failure behavior of tunnel heading collapse by MPM simulation
info:eu-repo/semantics/article
publication-article
oai:zenodo.org:821058
2019-11-04T07:12:09Z
user-cb-geo
user-kks32
Kumar, Krishna
Delenne, Jean-Yves
Soga, Kenichi
2017-06-16
This paper investigates the effect of initial volume fraction on the runout characteristics of collapse of granular columns on slopes in fluid. Two-dimensional sub-grain scale numerical simulations are performed to understand the flow dynamics of granular collapse in fluid. The Discrete Element (DEM) technique is coupled with the Lattice Boltzmann Method (LBM), for fluid-grain interactions, to understand the evolution of submerged granular flows. The fluid phase is simulated using Multiple-Relaxation-Time LBM (LBM-MRT) for numerical stability. In order to simulate interconnected pore space in 2D, a reduction in the radius of the grains (hydrodynamic radius) is assumed during LBM computations. The collapse of granular column in fluid is compared with the dry cases to understand the effect of fluid on the runout behaviour. A parametric analysis is performed to assess the influence of the granular characteristics (initial packing) on the evolution of flow and run-out distances for slope angles of 0°, 2.5°, 5° and 7.5°. The granular flow dynamics is investigated by analysing the effect of hydroplaning, water entrainment and viscous drag on the granular mass. The mechanism of energy dissipation, shape of the flow front, water entrainment and evolution of packing density is used to explain the difference in the flow characteristics of loose and dense granular column collapse in fluid.
https://zenodo.org/record/821058
10.5281/zenodo.821058
oai:zenodo.org:821058
doi:10.5281/zenodo.821057
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
LBM-DEM
Granular Column Collapse
Mechanics of granular column collapse in fluid at varying slope angles
info:eu-repo/semantics/article
publication-article
oai:zenodo.org:546602
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Kumar, Krishna
Soga, Kenichi
Delenne, Jean-Yves
2013-07-08
Avalanches, debris flows, and landslides are geophysical hazards, which involve rapid mass movement of granular
solids, water and air as a single-phase system. The dynamics of a granular flow involve at least three distinct scales: the
micro-scale, meso-scale, and the macro-scale. This study aims to understand the ability of continuum models to capture
the micro-mechanics of dry granular collapse. Material Point Method (MPM), a hybrid Lagrangian and Eulerian approach,
with Mohr-Coulomb failure criterion is used to describe the continuum behaviour of granular column collapse, while the
micromechanics is captured using Discrete Element Method (DEM) with tangential contact force model. The run-out profile
predicted by the continuum simulations matches with DEM simulations for columns with small aspect ratios (‘h/r’ < 2),
however MPM predicts larger run-out distances for columns with higher aspect ratios (‘h/r’ > 2). Energy evolution studies in
DEM simulations reveal higher collisional dissipation in the initial free-fall regime for tall columns. The lack of a collisional
energy dissipation mechanism in MPM simulations results in larger run-out distances. Micro-structural effects, such as shear
band formations, were observed both in DEM and MPM simulations. A sliding flow regime is observed above the distinct
passive zone at the core of the column. Velocity profiles obtained from both the scales are compared to understand the reason
for a slow flow run-out mobilization in MPM simulations.
https://zenodo.org/record/546602
10.5281/zenodo.546602
oai:zenodo.org:546602
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
Material Point Method (MPM)
Discrete Element Method (DEM)
Granular column collapse
Run-out profiles
Energy evolution
Density variations
Multi-scale modelling of granular avalanches
info:eu-repo/semantics/conferencePaper
publication-conferencepaper
oai:zenodo.org:546600
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Kumar, Krishna
Soga, Kenichi
Delenne, Jean-Yves
2012-08-01
Avalanches, landslides, and debris flows are geophysical hazards, which involve rapid
mass movement of granular solids, water, and air. Globally, landslides cause billions of
pounds in damage, and thousands of deaths and injuries each year. Hence, it is important to
understand the triggering mechanism and the evolution of flow. The momentum transfer
between the discrete and continuous phases significantly affects the dynamics of the flow
as a whole. Although certain macroscopic models are able to capture simple mechanical
behaviours, the complex physical mechanisms occurring at the grain scale, such as
hydrodynamic instabilities, formation of clusters, collapse, and transport, have largely
been ignored. In particular, when the solid phase reaches a high volume fraction, the strong
heterogeneity arising from the contact forces between the grains, and the hydrodynamic
forces, are difficult to integrate into the homogenization process involving global
averages. In order to describe the mechanism of immersed granular flows, it is important
to consider both the dynamics of the solid phase and the role of the ambient fluid. The
dynamics of the solid phase alone are insufficient to describe the mechanism of granular
flow in a fluid; it is important to consider the effect of hydrodynamic forces that reduce the
weight of the solids inducing a transition from dense-compacted to dense-suspended flows,
and the drag interactions which counteract the movement of the solids. Transient regimes
characterized by change in solid fraction, dilation at the onset of flow and development of
excess pore pressure, result in altering the balance between the stress carried by the fluid
and that carried by the grains, thereby changing the overall behaviour of the flow. In the
present study, 2D Lattice-Boltzmann and Discrete Element Method is adopted to capture
the fluid-soil interactions in underwater avalanches.
http://pubs.rsc.org/en/content/ebook/978-1-84973-360-1
https://zenodo.org/record/546600
10.5281/zenodo.546600
oai:zenodo.org:546600
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
LBM-DEM
Column collapse
Granular flows in fluid
info:eu-repo/semantics/conferencePaper
publication-conferencepaper
oai:zenodo.org:166103
2019-11-01T19:09:49Z
user-cb-geo
Gardner, Michael
Kolb, John
Sitar, Nicholas
2016-11-10
Generating a realistic representation of a fractured rock mass is a first step in
many different analyses. Field observations need to be translated into a 3-D
model that will serve as the input for these analyses. The block systems can
contain hundreds of thousands to millions of blocks of varying sizes and shapes;
generating these large models is very computationally expensive and requires
significant computing resources.
By taking advantage of the advances made in big data analytics and Cloud
Computing, we have a developed an open-source program - SparkRocks - that
generates block systems in parallel. The application runs on Apache Spark
which enables it to run locally, on a computer cluster or the Cloud. The block
generation is based on a subdivision and linear programming optimization as
introduced by Boon et al. (2015). SparkRocks automatically maintains load
balance among parallel processes and can be scaled up on the Cloud without
having to make any changes to the underlying implementation, enabling it to
generate real-world scale block systems containing millions of blocks in minutes.
Binaries and source code are available at https://github.com/cb-geo/spark-rocks.
This research was supported in part by the National Science Foundation (NSF) grant CMMI-1363354 and the Edward G. Cahill and John R. Cahill Endowed Chair funds.
https://zenodo.org/record/166103
10.5281/zenodo.166103
oai:zenodo.org:166103
url:https://zenodo.org/communities/cb-geo
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
Block Generation
Fractured Rock Mass
Parallel Computing
Cloud Computing
Apache Spark
Linear Programming
SparkRocks 1.0
info:eu-repo/semantics/other
software
oai:zenodo.org:546603
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Kumar, Krishna
Soga, Kenichi
Delenne, Jean-Yves
2014-09-03
In this study, two-dimensional sub-grain scale numerical simulations are performed to under-
stand the local rheology of dense granular flows in fluid. The Discrete Element (DEM) technique is coupled
with the Lattice Boltzmann Method (LBM), for fluid-grain interactions, to understand the evolution of im-
mersed granular flows. The fluid phase is simulated using Multiple-Relaxation-Time LBM (LBM-MRT) for
numerical stability. The Eulerian nature of the LBM formulation, together with the common explicit time step
scheme of both LBM and DEM makes this coupling strategy an efficient numerical procedure for systems dom-
inated by both grain–grain and grain–fluid interactions. In order to simulate interconnected pore space in 2D, a
reduction in the radius of the grains (hydrodynamic radius) is assumed during LBM computations. By varying
the hydrodynamic radius of the grains, granular materials of different permeabilities can be simulated. A para-
metric analysis is performed to assess the influence of the granular characteristics (initial packing, permeability,
slope of the inclined plane) on the evolution of flow and run-out distances. The effect of hydrodynamic forces
and hydroplaning on the run-out evolution is analysed by comparing the mechanism of energy dissipation and
flow evolution in dry and immersed granular flows. Voronoi tesselation was used to study the evolution of local
density and water entrainment at the flow front.
https://zenodo.org/record/546603
10.5281/zenodo.546603
oai:zenodo.org:546603
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
LBM-DEM
Underwater granular flows down inclined planes
info:eu-repo/semantics/conferencePaper
publication-conferencepaper
oai:zenodo.org:546607
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Mutabaruka, Patrick
Kumar, Krishna
Soga, Kenichi
Radjai, Farhang
Delenne, Jean-Yves
2015-05-26
We investigate by means of Contact Dynamics simulations the transient dynamics of a 2D
granular pile set into motion by applying shear velocity during a short time interval to all particles. The
spreading dynamics is directly controlled by the input energy whereas in recent studies of column collapse
the dynamics scales with the initial potential energy of the column. As in column collapse, we observe a
power-law dependence of the runout distance with respect to the input energy with nontrivial exponents.
This suggests that the power-law behavior is a generic feature of granular dynamics, and the values of
the exponents reflect the distribution of kinetic energy inside the material. We observe two regimes with
different values of the exponents: the low-energy regime reflects the destabilization of the pile by the impact
with a runout time independent of the input energy whereas the high-energy regime is governed by the
input energy. We show that the evolution of the pile in the high-energy regime can be described by a
characteristic decay time and the available energy after the pile is destabilized.
https://zenodo.org/record/546607
10.1140/epje/i2015-15047-x
oai:zenodo.org:546607
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
The European Physical Journal - E 38(47) 1-7
Contact dynamics
granular pile
transient dynamics
Transient dynamics of a 2D granular pile
info:eu-repo/semantics/article
publication-article
oai:zenodo.org:160339
2019-11-04T07:11:08Z
user-cb-geo
user-kks32
Soundararajan, Krishna Kumar
2015-01-16
Geophysical hazards usually involve multiphase flow of dense granular solids and water. Understanding the mechanics of granular flow is of particular importance in predicting the run-out behaviour of debris flows. The dynamics of a homogeneous granular flow involve three distinct scales: the microscopic scale, the meso-scale, and the macroscopic scale. Conventionally, granular flows are modelled as a continuum because they exhibit many collective phenomena. Recent studies, however, suggest that a continuum law may be unable to capture the effect of inhomogeneities at the grain scale level, such as orientation of force chains, which are micro-structural effects. Discrete element methods (DEM) are capable of simulating these micro-structural effects, however they are computationally expensive. In the present study, a multi-scale approach is adopted, using both DEM and continuum techniques, to better understand the rheology of granular flows and the limitations of continuum models. The collapse of a granular column on a horizontal surface is a simple case of granular flow; however, a proper model that describes the flow dynamics is still lacking. In the present study, the generalised interpolation material point method (GIMPM), a hybrid Eulerian – Lagrangian approach, is implemented with the Mohr-Coloumb failure criterion to describe the continuum behaviour of granular flows. The granular column collapse is also simulated using DEM to understand the micro-mechanics of the flow. The limitations of MPM in modelling the flow dynamics are studied by inspecting the energy dissipation mechanisms. The lack of collisional dissipation in the Mohr-Coloumb model results in longer run-out distances for granular flows in dilute regimes (where the mean pressure is low). However, the model is able to capture the rheology of dense granular flows, such as the run-out evolution of slopes subjected to lateral excitation, where the inertial number I < 0.1. The initiation and propagation of submarine flows depend mainly on the slope, density, and quantity of the material destabilised. Certain macroscopic models are able to capture simple mechanical behaviours, however the complex physical mechanisms that occur at the grain scale, such as hydrodynamic instabilities and formation of clusters, have largely been ignored. In order to describe the mechanism of submarine granular flows, it is important to consider both the dynamics of the solid phase and the role of the ambient fluid. In the present study, a two-dimensional coupled Lattice Boltzmann LBM – DEM technique is developed to understand the micro-scale rheology of granular flows in fluid. Parametric analyses are performed to assess the influence of initial configuration, permeability, and slope of the inclined plane on the flow. The effect of hydrodynamic forces on the run-out evolution is analysed by comparing the energy dissipation and flow evolution between dry and immersed conditions.
PhD Thesis
https://zenodo.org/record/160339
10.5281/zenodo.160339
oai:zenodo.org:160339
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
Granular flows
Material Point Method
Discrete Element Method
Lattice Boltzmann Method
Multi-phase flows
GPU
Multi-scale multiphase modelling of granular flows
info:eu-repo/semantics/doctoralThesis
publication-thesis
oai:zenodo.org:546614
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Kumar, Krishna
Soga, Kenichi
Delenne, Jean-Yves
Radjai, Farhang
2017-01-09
Transient granular flows, such as rock falls, debris flows, and aerial and submarine avalanches, occur very often in nature. In the
geotechnical context, transient movements of large granular slopes are a substantial factor of risk due to their destructive force
and the transformations they may produce in the landscape. This paper investigates the ability of MPM, a continuum approach,
to reproduce the evolution of a granular slope destabilised by an external energy source. In particular, a central issue is whether
the power-law dependence of run-out distance and time observed with respect to the initial geometry or energy can be reproduced
by a simple Mohr-Coulomb plastic behaviour. The effect of base friction on the run-out kinematics is studied by comparing the
data obtained from the DEM and MPM simulations. The mechanism of energy dissipation is primarily through friction and the
MPM is able to predict the run-out response in good agreement with the DEM simulations. At very low excitation energies, the
DEM simulations show longer run-out in comparison to the MPM due to local destabilization at the flow front. At low input
energies, a larger fraction of the energy is consumed in the destabilisation process, hence the amount energy available for flow is
less. However, at higher input energy, where most of the energy is dissipated during the spreading phase, the run-out distance has
a weak dependence on the distribution of velocity in the granular mass
https://zenodo.org/record/546614
10.1016/j.proeng.2017.01.032
oai:zenodo.org:546614
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
Procedia Engineering 175(1) 94 - 101
Material Point Method (MPM)
Discrete Element Method (DEM)
Transient dynamics
Modelling transient dynamics of granular slopes: MPM and DEM
info:eu-repo/semantics/conferencePaper
publication-conferencepaper
oai:zenodo.org:3464564
2019-11-01T19:11:11Z
user-cb-geo
user-kks32
Kumar, Krishna
Salmond, Jeffrey
Kularathna, Shyamini
Wilkes, Christopher
Tjung, Ezra
Biscontin, Giovanna
Soga, Kenichi
2019-01-13
In this paper, we describe a new scalable and modular material point method (MPM) code developed for solving large-scale problems in continuum mechanics. The MPM is a hybrid Eulerian-Lagrangian approach, which uses both moving material points and computational nodes on a background mesh. The MPM has been successfully applied to solve large-deformation problems such as landslides, failure of slopes, concrete flows, etc. Solving these large-deformation problems result in the material points actively moving through the mesh. Developing an efficient parallelisation scheme for the MPM code requires dynamic load-balancing techniques for both the material points and the background mesh. This paper describes the data structures and algorithms employed to improve the performance and portability of the MPM code. An object-oriented programming paradigm is adopted to modularise the MPM code. The Unified Modelling Language (UML) diagram of the MPM code structure is shown in Figure 1. Modern CPUs are designed for Single Instruction Multiple Data (SIMD) operations and vectorizations. A parallel vector container is used to store and operate on the material points and the nodes in the background mesh. The material point properties such as acceleration, velocities, and positions can be updated independent of other material points in the mesh without resulting in a race condition, hence no special locking mechanism is necessary. On the other hand, nodes share information with all the material points in the cells connected to the node (and also the neighbouring cells in the case of GIMP). Updating these nodal information (for e.g., velocity / momentum) requires aggregating properties from all the material points in the associated cell and its neighbours. To prevent race conditions on nodal updates, an associated mutex lock is enabled at each node during a property update. Thus, all functions on material points and nodes in the code are parallel operations. At a function level, updating information such as location, stresses, and strains requires iterating over each component using a `for` loop. A for-loop with a known size can be unrolled and optimised during compilation. However, the flexibility of modelling different phases and dimensions using a single material point (for e.g., 2D v. 3D arrays and multi-phase represented on a single material point), requires a dynamically sized array, which cannot be unrolled at compile-time. To improve the compile-time optimisation, the material point class is templatised based on dimension and the number of phases, and the node class is templatised with an additional degrees of freedom argument. Templates in C++ enables optimisation as the array sizes are known at compilation. A generic factory pattern that can handle constructors with arbitrary number of arguments is developed to instantiate material points, nodes and cells of required types. Although parallel vector containers are useful to vectorise, fetching a particular node or a material point requires iterating through all the components in a container and has a worst performance order of O(n), where `n` is the size of the container. To improve the performance of identifying a material point pointer or a nodal pointer, a map data structure is used. A map has an average order of lookup O(1). A map is created with the unique global id of the node / material point as the key. The map container is used to identify and apply functions (for e.g., boundary conditions) at a given node or a material point. In the MPM, the velocity and acceleration boundary conditions are applied at the nodes. Non-prismatic boundaries like those that can be found in landslides pose problems when applying nodal boundary conditions on irregular surfaces. The MPM code uses isoparametric elements to model complex geometries and boundary conditions. Unlike the Finite Element Method, where the location of Gauss points in an element is known in the natural coordinates, the use of isoparametric elements in the MPM requires transforming the location of material points from the real coordinates to the natural coordinates. The inverse transform of the linear mapping from natural to real coordinates does not have an analytical solution in 3D. The MPM code uses Newton Raphson iterations to transform the coordinates. Affine transformation is used to make an improved the initial guess, which oftentimes does not require the Newton Raphson iterations. This combined approach in transforming real to natural coordinates improves the solution speed, and the performance is similar to using cartesian grids. Inputs to the MPM code is configured through a JSON data structure. The MPM code allows for check point restart using HDF5 data of material points stored at each time-step. The results from the MPM simulations are visualized using a compressed binary VTK files. An interactive Jupyter Notebook can also be used to perform post-processing and analysis on the simulation results stored in HDF5 format. The MPM code is distributed under MIT license and is available at [https://github.com/cb-geo/mpm](https://github.com/cb-geo/mpm).
https://zenodo.org/record/3464564
10.5281/zenodo.3464564
oai:zenodo.org:3464564
doi:10.5281/zenodo.3464563
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
MPM
Material Point Method
Scalable and modular material point method for large-scale simulations
info:eu-repo/semantics/conferencePaper
publication-conferencepaper
oai:zenodo.org:3464562
2019-11-01T19:11:10Z
user-cb-geo
user-kks32
Tjung, Ezra
Kularathna, Shyamini
Kumar, Krishna
Soga, Kenichi
2020-02-25
The Material Point Method (MPM) is a hybrid Eulerian-Lagrangian approach capable of simulating large deformation problems of history-dependent materials. While the MPM can represent complex and evolving material domains by using Lagrangian points, boundary conditions are often applied to the Eulerian nodes of the background mesh nodes. Hence, the use of a structured mesh may become prohibitively restrictive for modeling complex boundaries such as a landslide topography. We study the suitability of unstructured background mesh with isoparametric elements to model irregular boundaries in the MPM. An inverse mapping algorithm is used to transform the material points from the global coordinates to the local natural coordinates. Dirichlet velocity and frictional boundary conditions are applied in the local coordinate system at each boundary node. This approach of modeling complex boundary conditions is validated by modeling the dynamics of a gravity-driven rigid block sliding on an inclined plane. This method is later applied to a flume test of controlled debris flow on an inclined plane conducted by the United States Geological Survey (USGS).
https://zenodo.org/record/3464562
10.5281/zenodo.3464562
oai:zenodo.org:3464562
doi:10.5281/zenodo.3464561
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
mpm
Modeling Irregular Boundaries Using Isoparametric Elements in Material Point Method
info:eu-repo/semantics/conferencePaper
publication-conferencepaper
oai:zenodo.org:546613
2019-11-04T07:12:47Z
user-cb-geo
user-kks32
Soga, Kenichi
Eduardo, Alonso
Yerro, Alba
Kumar, Krishna
Bandara, Samila
2016-03-01
Traditional geotechnical analyses for landslides involve failure prediction (i.e. onset of failure) and the design of structures that can safely withstand the applied loads. The analyses provide limited information on the post-failure behaviour. Modern numerical methods are able to simulate large mass movements and there is an opportunity to utilise such methods to evaluate the risks of catastrophic damage if a landslide occurs. In this paper, various large-deformation analysis methods are introduced and their applicability for solving landslide problems is discussed. Since catastrophic landslides often involve seepage forces, consideration of the coupled behaviour of soil and pore fluid is essential. Two approaches to model soil–pore fluid coupling in large-deformation analysis using the material point method (MPM) are introduced. An example simulation is presented for each approach; one on a model levee failure and the other on a natural cut slope failure (the Selborne experiment conducted by Cooper and co-workers in 1998). In the levee failure case, MPM simulation was able to capture a complex failure mechanism including the development of successive shear bands. The simulation was also able to predict excess pore pressure generation during the failure propagation and the subsequent consolidation stage. The simulations demonstrated the importance of the dilation characteristics of soil as well as changes in geometry for the post-failure behaviour. In the Selborne case, MPM was able to simulate the progressive failure of brittle, overconsolidated clay. The evolution of shear stresses along the failure surface was also captured by the MPM. The changes in the pore pressure and the actual shape of the failure surface were simulated by the MPM. The importance of accurately modelling the shear band within the MPM framework is highlighted.
https://zenodo.org/record/546613
10.1680/jgeot.15.LM.005
oai:zenodo.org:546613
url:https://zenodo.org/communities/cb-geo
url:https://zenodo.org/communities/kks32
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/legalcode
Geotechnique 66(3) 246-273
landslides
Material point method (MPM)
Numerical modelling
Trends in large-deformation analysis of landslide mass movements with particular emphasis on the material point method
info:eu-repo/semantics/article
publication-article