Simulation Of Granular Flows Research Articles

Efficient lattice Boltzmann simulation of free-surface granular flows with μ(I)-rheology

This paper presents a lattice Boltzmann framework for accurate and efficient simulation of free-surface granular flows. The granular assembly is treated as a viscoplastic fluid, whose apparent viscosity varies locally with the shear rate and pressure according to a regularized μ(I)-rheology. A single-phase free-surface model is employed to track the evolution of the particle-air interface. The lattice Boltzmann implementation is first validated by simulating a steady-state granular flow on a rough inclined plane and a good agreement with the analytical solution is achieved. The validated model is then applied to simulate a transient granular column collapse problem. Compared to a companion discrete element simulation, the lattice Boltzmann model with the μ(I)-rheology is able to capture the overall dynamic behaviors of granular column collapse. However, a different behavior is observed when a similar Bingham viscoplastic model with a fixed yield stress is applied, highlighting the pressure dependent nature of granular flows. The proposed lattice Boltzmann formulation is highly efficient compared to the conventional computational fluid dynamics, and has the potential to conduct three-dimensional continuum simulation of large-scale geophysical flows with microscopic granular physics.

On POD-based modal analysis in simulations of granular flows

Understanding the dynamics of granular flows is of great significance in various engineering fields but challenging because of flow complexity. The discrete element method (DEM) is often employed in simulations of various granular systems. Recently, modal analysis has been shown to remarkably deepen the understanding of these systems. The principle of the modal analysis is to extract a set of dominant structures from experimental or numerical datasets. In this study, an advanced modal analysis technique, i.e., the Lanczos-based proper orthogonal decomposition (LPOD), is incorporated into numerical simulations of a particle system. Two types of applications are presented. First, the modal analysis based on the LPOD technique is adopted to evaluate particle mixing in a rolling drum. It is demonstrated that the POD-mode distributions of particle movements can reveal dominant mechanisms, such as convection/diffusion. Second, the LPOD technique based modal analysis is employed to validate the adequacy of a coarse-grained DEM in a spouted bed. The results show that similar patterns of POD modes and related energy spectra are observed in the original particle and the coarse-grained particle systems. Consequently, not only can POD analysis be used to identify main mixing mechanisms, but also POD results are shown to be new effective parameters in the validation of the coarse-grained DEM. • An advanced Lanczos-based POD (LPOD) was employed to analyze granular phenomena. • Applicability of the LPOD was shown in simulations of a drum and a spouted bed. • LPOD was demonstrated to effectively identify main mixing mechanisms. • LPOD provided new parameters to effectively validate a coarse-grained DEM.

Keynote lecture. The planar setup: A window through the complex interactions in granular flows

Granular flows are a complex process, involving a wide range of grain sizes, materials, varied viscous fluids, among others. For this reason, the simulation of granular flows requires a certain level of simplification, allowing the isolated study of its governing variables and extending the global observations to field events. Here, we present the planar setup as an alternative for studying simplified processes associated to granular flows. The planar setup consists of two windows separated by a thin gap and enclosing a granular assembly. We present two examples where the planar setup is adapted for the study of the competing action of segregation and disaggregation in a fractured grain under shear flow, and for the study of the stability scenarios of a flow impacting a permeable obstacle. The close visualization of the kinematics at the particle scale provides an ideal opportunity for describing the mechanisms behind the grain disaggregation or controlling the obstacle stability. Both examples highlight the advantages of the planar setup for the study of granular flows.

A numerical study on the effects of particle size distribution on run-out distance of granular flow

The discrete element method is a powerful numerical tool widely employed in granular flow simulations. To reduce computational costs, either monodisperse granular models or models with a limited number of particle sizes are used to estimate the risk of sediment-related disasters. This highlights the need for a thorough understanding on the effects of particle size distribution on the accuracy of granular simulations. In this study, a series of granular flow simulations was conducted with different particle size distributions. The results clearly indicate that the run-out distance strongly depends on the number of particle sizes and is underestimated in the conditions employed by the monodisperse granular model. The longest run-out distance was observed in case that the bidisperse granular model was employed, whereas run-out distance tends to a constant value when polydisperse granular model was employed. Because particle size segregation was observed during the flow, a series of vibration simulations was also conducted to estimate the degree of the size segregation. It was shown that each granular model has an inherent degree of size segregation. From the results of the granular flow simulations and vibration simulations, it was confirmed that the inherent degree of the size segregation clearly affects the run-out distance.

A granular energy-controlled boundary condition for discrete element simulations of granular flows on erodible surfaces

Entrainment of the substrate, which can cause the volume of geophysical flows to increase by many times and greatly affects its mobility, occurs frequently. Even though many large-scale studies have been conducted to investigate entrainment during flows, particle-scale studies are urgently needed to understand this complex process. We propose a novel configuration with an energy-controlled boundary to model inclined granular flows on erodible surfaces with the aim of investigating the rheological features of granular flows with entrainment. The erosion degree is controlled by adjusting the energy of the bottom granular bed. The bulk velocity, stress, microstructure, and constitutive behavior are systematically analyzed. Our simulations capture the exponentially decaying velocity in the creeping region, confirming that this configuration can be applied to study geophysical flows with entrainment. The velocity at the free surface increases with erosion depth, which means entrainment can greatly enhance the mobility of granular flow. However, the flow in the shear band still belongs to the inertial regime. The novel energy-controlled configuration provides effective and efficient way to investigate granular flows on erodible surfaces, serving as an initial step to understand geophysical flows involving entrainment, which is essential to develop new geo-disaster mitigation strategy.

Computational fluid dynamic simulations of granular flows: Insights on the flow-wall interaction dynamics

Dry volcanic granular flows are gravity-driven currents composed of solid particles where particle-particle interactions dominate the motion. The interaction with topography is a relevant factor controlling the propagation of such flows. In this paper we investigate the dynamics of channelised volcanic granular flows by comparing large-scale experiments with multiphase computational fluid dynamic simulations using the Two-Fluid Model approach, with an emphasis on the dynamics regulating the flow-wall interactions. We use the software MFIX to carry out sensitivity analysis of the boundary conditions for the solid phase implemented in the numerical code. The sensitivity analysis shows how the choice of the boundary condition and of the relevant parameters controlling the boundary conditions highly affect the dynamics of the whole flow. Finally, a preliminary benchmark of the MFIX boundary conditions with one large-scale experiment is presented, showing good agreement between the simulated and experimental flow front velocities.

Correction to: Modelling of the coefficients of restitution for prolate spheroid particles and its application in simulations of 2D granular flow

Correction to: Modelling of the coefficients of restitution for prolate spheroid particles and its application in simulations of 2D granular flow

A Predictor–corrector scheme for simulation of two-phase granular flows over a moved bed with a variable topography

In this paper, we propose a numerical simulation of two-phase shallow granular flows through a moved bed with a variable irregular topography via a predictor corrector scheme. This method consists of predictor and corrector stages. The predictor stage contains a parameter to control the numerical diffusion that is performed by utilizing limiters and Riemann invariant theory. The corrector stage recovers the balance conservation equation. In the first part, we solve numerically the one-dimensional equation for two-phase shallow granular flows over a fixed bed with irregular topography. In the second part, we consider the model equations for the bed-load sediment transport, the governing model equations consist of two components, specifically, a geophysical flows part and interstitial fluid. The sediment part is described by the Exner equation when the velocity can be considered to be the solid velocity, fluid velocity or a mean value of both of them.

Input files for DEM simulation of dry granular flows generated by the collapse of granular columns with different inter-particle frictions.

Input files for DEM simulation of dry granular flows generated by the collapse of granular columns with different inter-particle frictions.

Coupling Depth-Averaged and 3D numerical models for the simulation of granular flows

Continuum-based numerical models are widely used to simulate debris flows due to their reliability in predicting the movement path, depth and velocity, which are key parameters to design mitigation structures. Nowadays, two main families of continuum-based models exist: depth-averaged (DA) models and three-dimensional (3D) models. If the former are already able to determine the key flow parameters, only the latter allow a detailed investigation of a flow-structure interaction. The study of the whole propagation path with a 3D model would be extremely complex and time-consuming, but the whole process influences the flow-structure interaction. Therefore, this work aims to couple a DA model and a 3D model (DA-3D). The first model simulates the flow in the upper part of the propagation path, where no structure exists. The second model takes over upstream of the structure to be analysed. At the transition from one model to the other, the coupling requires that outputs of the DA model become inputs of the 3D model. The validation of the DA-3D model is made through numerical simulations of the experimental results obtained on a flume apparatus at laboratory scale. The obtained numerical results confirmed the successful coupling of the two models.

Modelling of the coefficients of restitution for prolate spheroid particles and its application in simulations of 2D granular flow

Modelling of the coefficients of restitution for prolate spheroid particles and its application in simulations of 2D granular flow

Numerical Simulation of Granular and Multiphase Flows through Porous Media Obtained by Image Analysis

Numerical Simulation of Granular and Multiphase Flows through Porous Media Obtained by Image Analysis

Some considerations on the rheology of dense frictional cylindrical particles

Discrete element method simulations of granular shear flows of frictional cylindrical particles are performed. From the simulations, solid-phase pressure, shear stress, and bulk friction coefficient μ can be measured, allowing the investigation of the effects of particle properties on the macroscopic flow behaviors. Thus, the inertial number I based rheological models, which were frequently used for the spherical particles in the previous work, are examined for the applicability to cylindrical particles in the present study. It is found that the particle aspect ratio, interparticle friction coefficient, and particle size polydispersity all affect the bulk friction coefficient-inertial number correlation and the solid volume fraction-inertial number correlation, and their effects vary in different flow regimes, which exhibit different mechanical behaviors.

Runout and deflection of granular flow past an array of obstacles on a slope

The interaction between granular flow and an array of obstacles is an important research subject in geological disaster prevention. We used a numerical model for the depth-integrated equations formulated in a bed-fitted coordinate system to simulate the runout and deflection of granular flow past an array of simple obstacles. Numerical simulations of granular flow encountering arrays of square columns and tetrahedral pyramids gave a lot of interesting and fascinating deposits. We then proposed a new dimensionless index called deflection efficiency (DE), together with the runout efficiency (RE) to quantify the comprehensive effects of the obstacle system on the runout and deflection behavior. There are three physical effects, a dissipation effect through bow shock, a deflection effect by splitting the granular flow, and a retention effect via trapping some granular mass, the combinations of which determine the mobility and deposit of granular flow. We found that RE decreases as either the height or number of rows of obstacles increases because of the dissipation effect, while DE increases as height increases due to the deflection effect for both tetrahedral and square column obstacles. However, if the retention effect was as important as the deflection effect, the DE could be reduced when the row numbers increase further. These findings provide some constructive help for the design of obstacle arrays and complement the understanding of subsequent flow after interaction between granular flow and obstacle arrays.

GPU accelerated MFiX-DEM simulations of granular and multiphase flows

In this research, a Graphical Processing Unit (GPU) accelerated Discrete Element Method (DEM) code was developed and coupled with the Computational Fluid Dynamic (CFD) software MFiX to simulate granular and multiphase flows with heat transfers and chemical reactions. The Fortran-based CFD solver was coupled with the CUDA/C++ based DEM solver through inter-process pipes. The speedup to the CPU version of MFiX-DEM is about 130–243 folds in the simulation of particle packings. In fluidized bed simulations, the DEM computation time is reduced from 91% to 17% with a speedup of 78 folds. The simulation of Geldart A particle fluidization revealed a similar level of importance of both fluid and particle coarse-graining. The filtered drag derived from the two-fluid model is suitable for Euler-Lagrangian simulations with both fluid and particle coarse-graining. It overcorrects the influence of sub-grid structures if used for simulations with only fluid coarse-graining.

Large deformation analysis of granular materials with stabilized and noise-free stress treatment in smoothed particle hydrodynamics (SPH)

This paper presents a new smoothed particle hydrodynamics (SPH) model for the large deformation analysis of granular materials with improved accuracy and stability. In order to remove the spurious stress profile during the post-failure process which is a common issue for the application of SPH to geotechnical problems, an innovative stress diffusion term is formulated. Further a new boundary treatment is proposed with the use of renormalization techniques to give a first-order consistent wall boundary conditions for geotechnical applications. This methodology is able to deal with complex geometries such as sharp corners. A number of test cases are considered to examine the robustness and accuracy of the proposed technique. Results show that the new boundary formulation is able to improve the accuracy of the solution even for a relatively coarse particle resolution. The stress diffusion term reduces the numerical noise that affects the stress under large deformations, resulting in a smooth stress field. The proposed SPH model is finally applied to the simulation of granular flow and tunnel face collapse, showing satisfactory agreement and convergence with experimental results.

Viscous Effects on the Particle Size Segregation in Geophysical Mass Flows: Insights From Immersed Granular Shear Flow Simulations

AbstractSize segregation is a common feature in geophysical mass flow deposits and is an active process during motion. The presence of interstitial fluids in such flows affect the motion of constituent particles and result in complex segregation behaviors. Effects of the viscosity and density of various interstitial fluids on the rate of particle size segregation are investigated through coupled granular‐fluid simulations of immersed plane‐sheared flows. The segregation rate decreases as the fluid viscosity increases, but remains constant when the viscosity is below certain threshold values. In the low viscosity limit, segregation is affected only by the relative density between the particles and the fluid, and by flow inertial conditions. Analysis of segregation forcing terms based on the mixture theory of segregation reveals that the decrease of segregation rates with the viscosity is due to the increase of fluid drag forces, which effectively weaken the contact stress gradients responsible for driving the large particles to migrate upward. Viscous damping also diminishes velocity fluctuations and thereby inhibits the migration of particles throughout the mixture. The transition in the viscosity dependence is shown to correspond to the transition between granular‐fluid flow regimes. An empirical scaling formula is developed which accounts for the effects of fluid viscosity and the relative density on size segregation immersed in different fluids.

Input files for DEM simulation of dry granular flows generated by the collapse of granular columns with different fractal particle size distributions

Input files for DEM simulation of dry granular flows generated by the collapse of granular columns with different fractal particle size distributions

A Lagrangian differencing dynamics method for granular flow modeling

In this paper, a new Lagrangian differencing dynamics (LDD) method is presented for the simulation of granular flows. LDD is a truly meshless method, which employs second-order consistent spatial operators derived from the Taylor expansion and point renormalization. A decoupled pressure-velocity formulation is employed to derive the pressure Poisson equation, which ensures smooth pressure results in time. Granular media are modeled as viscoplastic materials with the Drucker-Prager yield surface. The velocity equation is formulated and solved in an implicit form, in order to handle large viscosities from the constitutive model. Furthermore, a position-based dynamics technique is used to maintain uniform distribution of the Lagrangian points. The presented LDD method for granular flows is validated by simulating two numerical examples. The results are compared with experimental and numerical data from the literature.

Machine learning accelerated discrete element modeling of granular flows

Granular flows are widely encountered in many industrial processes and natural phenomena. Discrete Element Modeling (DEM) is a useful tool for understanding and troubleshooting devices processing granular materials. However, its applicability is significantly limited by the huge computational cost associated with detecting and computing collisions. In this research, the computation speed of DEM was accelerated by orders of magnitude using a convolutional neural network to replace the direct calculation of particle–particle and particle-boundary collisions. The MFiX software was used to generate the training and testing dataset. A GPU accelerated TensorFlow model was used to train the neural network and test the results. The model fluctuations caused by different training steps were reduced with a multi-scale loss function. The accuracy was improved with more frames within one training step. The modeling of a rotating drum and a hopper demonstrated the accuracy and efficiency of this machine learning accelerated DEM in the simulation of granular flows.