Discrete Element Method Technique Research Articles

Improving the prediction accuracy of small-strain shear modulus of granular soils through PSD: An investigation enabled by DEM and machine learning technique

This study presents a numerical investigation into the effect of particle size distribution (PSD) on the small-strain shear modulus (G0) of granular soils using the discrete element method (DEM). Drained triaxial tests were conducted on a set of spherical particle assemblies covering a wide variety of PSDs. The tests demonstrated that the G0 decreases with increasing the coefficient of uniformity (Cu), assuming the confining pressure (p’) and the void ratio (e) remain constant. A corrected void ratio (e4), which regards mechanically unstable particles with less than four contacts as void, was developed. Analyses performed afterward revealed that e4 is more strongly correlated with G0 than e. Consequently, a Hardin-based G0 model parameterized by e4 and p’ was established and it is more accurate than two commonly used models, which are parameterized by e, p’ and Cu. Furthermore, micromechanical and microstructural features were investigated to acquire a better understanding of why models based on e and Cu yield less accurate results than models based on e4. Finally, a hybrid model combining the high explanatory power of statistical models with the high predictive power of machine learning models were proposed. The hybrid model which only uses measurable macroscopic parameters performs on par with the microstructural model and is more accurate than conventional empirical models. The proposed model offers a simple and streamlined approach to predicting G0 with satisfactory accuracy, which is a feasible strategy for maximizing the utilization of copious experimental data.

GPU-based SPH-DEM Method to Examine the Three-Phase Hydrodynamic Interactions between Multiphase Flow and Solid Particles

Particulate flows in a gas-liquid multiphase mixture (i.e., three-phase flows) are frequently encountered in various fields as well as the chemical engineering, resource engineering, ocean engineering, and nuclear engineering domains. Thus, the numerical modeling for such three-phase flows is essential to evaluate and enhance the fluidic design of the existing industrial devices or increase the engineering safety/efficiency. In terms of the solid particle phase, the discrete element method (DEM) has demonstrated outstanding capability in numerically modeling solid–solid interactions. For multiphase CFD model, several numerical techniques, ranging from the Eulerian–Eulerian two-fluid model to a fully resolved DNS solver, have been coupled with the DEM to model the three-phase flow. Most of the existing research on three-phase particulate flows was based on coupled grid-based CFD and DEM techniques. Considering that many three-phase particulate flows in industries are driven by a vapor/gas phase that forms a sharp interface with the liquid, coupling DEM with particle-based Lagrangian CFD methods, which can handle multi-phase flows without any interface capturing or associated correlations, can also be a good option or alternative for modeling such three-phase flows. In this respect, a three-phase flow solver was established in this study by coupling the DEM with a Lagrangian smoothed particle hydrodynamics (SPH) model while adopting the unresolved phase coupling between the two techniques. In order to overcome the low computational efficiency of these two numerical methods, GPU-based acceleration is adopted for speedup of SPH-DEM coupled solver due to its high compatibility for Lagrangian methods offered by thousands of GPU processors. The results of a scalability analysis indicated that the accelerated version exhibited an enhanced performance especially when many Lagrangian nodes are used in simulation. Several benchmark simulations were conducted to demonstrate the capability and applicability of the SPH-DEM solver in various multi-phase applications associated with particulate flows. The results of numerical simulations validated the feasibility of the momentum exchange model, and the potential and applicability of the SPH-DEM coupled solver for three-phase flow was demonstrated through a three-phase SPH-DEM simulation on the gas-driven leveling behavior of a particulate bed.

Combination of the finite element method and particle-based methods for predicting the failure of reinforced concrete structures under extreme water forces

We present a combination of the Finite Element Method (FEM), the Particle Finite Element Method (PFEM), and the Discrete Element Method (DEM) for modeling and analyzing the failure of reinforced concrete structures under impulsive wave forces originating from free-surface flows in critical water hazards. The free-surface water flow is modeled with the PFEM, while the structural behavior and the fractures induced by the water forces in the structure are modeled with a coupled FEM–DEM technique. The concrete material behavior is simulated with a standard isotropic damage model. The reinforcing bars are modeled by a rule of mixtures procedure, for simplicity. The possibilities of the new integrated PDFEM approach for predicting the evolution of free-surface tsunami-type waves and their devastating effect on constructions are validated with experiments on the failure of reinforced concrete plates under large impacting waves, performed in a laboratory facility in Japan.

Computational study of the industrial synthesis of tungsten powders

Discrete Element Method (DEM) is a highly employed Lagrangian technique to represent particulate systems. When DEM techniques are extended by adding thermochemical conversion of solid particles as well as their interaction with the surrounding fluid, numerous challenging applications can be numerically studied. Nevertheless, industrial applications with large number of particles, such as powder synthesis or blast furnaces, are often time or size limited due to the high computational efforts that these simulations demand. This contribution introduces the Agglomerated Particle Method (APM) as a numerical technique aiming to reduce the computational costs of coupled Discrete Element Method and Computational Fluid Dynamics (DEM-CFD) approaches for the thermochemical conversion of powder beds.From experimental and numerical investigation on thermochemical conversion of packed beds has been observed that the temperature or composition of particles in a small spatial domain do not vary significantly. Consequently, one single numerical solution may be representative for all the particles on such a domain. Thus, a collection of neighbor particles are represented by one single agglomerated particle solved by eXtended Discrete Element Method (XDEM) techniques.The proposed model is firstly assessed with classic benchmark problems for heating and drying of packed beds. Later, the model approach is employed for predicting the industrial synthesis of metallic tungsten powder.The comparison of APM predictions with resolved XDEM predictions and experimental data shows the proposed model as a viable technique to solve large scale powder applications, such as tungsten powder production, at feasible time.

Numerical modelling to predict fracturing rock (Thanet chalk) due to naturally occurring faults and fluid pressure

Outcrop mapping of a chalk cliff and wavecut platform in Thanet, Southeast England show a complex fracture pattern that seems to be controlled by meso-scale strike-slip faults within the chalk. The response of these faults to changes to in situ stress and fluid pressure is thought to control the nucleation and propagation of fractures in the chalk. In this study the DEM (Discrete Element Method) technique has been employed as a follow up to previous field and numerical (boundary and finite element method) investigations to ascertain the role of the faults in the initiation and nucleation of fractures The role of fluid pressure, in-situ stress, and fault geometry are recognised as focal factors. The generation of localised areas of tensile stresses due to fluid pressure and stress perturbations have been shown to cause the initiation of fractures around the fault bends. For releasing bends, localised tensile stresses tend to occur along the central segment of the fault bend, whereas for restraining bends, tensile stresses are more likely to develop on the outer edges of the fault bend. The dissimilarity in the fracturing process due to differences in the geometry of pre-existing faults demonstrates the significance of both fault geometry and fluid behaviour in controlling fracturing.

Comparison of the discrete element and finite element methods to model the interaction of soil and tool cutting edge

Soil tillage is an energy intensive operation and design improvements that reduce forces have been pursued for many different tools. Due to the high cost of prototyping and testing, computer modelling has been adopted to design tillage equipment. In order to model soil-tool interaction two methods namely; finite element method (FEM) and discrete element method (DEM) have been used. Fielke (1994 and 1996) found that for shallow working low rake angle tools the cutting edge geometry of a tillage tool has a major effect on tillage forces and soil movement. FEM modelling of the tests was also carried out in Fielke (1999) . In this paper the experimental work of Fielke (1994) was simulated using DEM techniques and the results were compared to both the measured data and FEM predicted results. The results of the study showed that better vertical force prediction was obtained using DEM whereas forward soil movements below the tillage depth were simulated more accurately using FEM. This can be attributed to the larger size of particles used in DEM simulation than needed to pass around the cutting edge. It was also shown that DEM can be used to accurately predict soil failure planes.

A three-dimensional FEM–DEM technique for predicting the evolution of fracture in geomaterials and concrete

This paper extends to three dimensions (3D), the computational technique developed by the authors in 2D for predicting the onset and evolution of fracture in a finite element mesh in a simple manner based on combining the finite element method and the discrete element method (DEM) approach (Zarate and Onate in Comput Part Mech 2(3):301–314, 2015). Once a crack is detected at an element edge, discrete elements are generated at the adjacent element vertexes and a simple DEM mechanism is considered in order to follow the evolution of the crack. The combination of the DEM with simple four-noded linear tetrahedron elements correctly captures the onset of fracture and its evolution, as shown in several 3D examples of application.

DEM analysis of acoustic wake agglomeration for mono-sized microparticles in the presence of gravitational effects

The application of the discrete element method (DEM) to numerical simulation of the acoustic agglomeration of micron-sized mono-dispersed aerosol particles is demonstrated. The conventional DEM technique used in granular dynamics is modified for the simulation of the acoustically induced attractive motion of particles in incompressible fluid. The relationship between the acoustic wake and the gravity is investigated by simulating the binary interaction of two particles for a wide range of particles’ orientations to the sound direction. The main finding obtained by simulation results shows that agglomeration time is solely predefined by the acoustic wake effect independently of gravity. On the other hand, the gravitational motion is contributed by the sound, and an increase of settling velocity due to the sound of individual particles was found. Additionally, two particles surrounded by a system of other particles are illustrated by numerical results. It was also shown that isolated particles demonstrate an overestimated increase of the agglomeration time, which was essentially reduced by the contribution of other particles in the multi-particle system.

Modeling particle sedimentation in viscous fluids with a coupled immersed boundary method and discrete element method

Numerical techniques have increasingly been used to model fluid–particle two-phase flows. Coupling the immersed boundary method (IBM) and discrete element method (DEM) is one promising approach for modeling particulate flows. In this study, IBM was coupled with DEM to improve the reliability and accuracy of IBM for determining the positions of particles during the sedimentation process within viscous fluids. The required ratio of the particle diameter to the grid size (D/dx) was determined by comparing the simulation results with the analytical solution and experimental data. A dynamic mesh refinement model was utilised in the IBM model to refine the computational fluid dynamics grid near the particles. In addition, an optimum coupling interval between the IBM and DEM models was determined based on the experimental results of a single particle sedimentation within silicon oil at a Reynolds number of 1.5. The experimental results and the analytical solution were then utilised to validate the IBM–DEM model at Reynolds numbers of 4.1, 11.6, and 31.9. Finally, the validated model was utilised to investigate the sedimentation process for more than one particle by modeling the drafting-kissing-tumbling process and the Boycott phenomenon. Benchmark tests showed that the IBM–DEM technique preserves the advantages of DEM for tracking a group of particles, while the IBM provides a reliable and accurate approach for modeling the particle–fluid interaction.

Experimental and numerical investigations into hydraulic behaviour of coir fibre drain

Over many decades, natural fibre bundles have been widely used for drainage and filtration applications because of their favourable hydraulic conductivity and abundance in Asian countries. In recent times, natural (biodegradable) coir and jute drains, which are environmentally friendly, have been considered in lieu of conventional geosynthetic wick drains for soft clay consolidation in Australian coastal regions. However, there is a lack of a computational framework to predict the hydraulic behaviour of fibre drains on the basis of micromechanical (fabric) characteristics. Employing computational fluid dynamics (CFD) coupled with the discrete element method (DEM) to model the hydraulic behaviour of fibrous materials has shown promise in an earlier 2016 study by Nguyen and Indraratna, which considered an idealized parallel arrangement of fibres for simplicity. This paper aims to broaden the application of the coupled CFD–DEM technique to real fibres (coconut coir) considering both nontwisted and twisted fibre bundles that have more complex porous structure. The hydraulic conductivity determined from the numerical approach is validated with the experimental results, and also compared with the analytical prediction based on the conventional Kozeny–Carmen (KC) approach. The current study shows that the CFD–DEM technique can capture well the fluid flow characteristics of a nonuniform fibrous structure, including dense twisted coir bundles.

Study of flow through a packed bed using discrete element method and computational fluid dynamics

Packed beds find wide applications in chemical industries. In this paper, a Discrete Element Method (DEM) – Computational Fluid Dynamics (CFD) approach has been adopted to predict the flow profile in the bed for different diameter of the bed/diameter of the particle. The randomly packed bed was created using the DEM technique. The radial voidage of the bed was calculated using the Monte Carlo integration method. The radial voidage showed an oscillating pattern up to approximately 4–5 particle diameter from the wall, which was validated with the experimental data reported by several researchers. The flow studies through these packed beds were carried using single-phase laminar flow model. The flow followed a similar oscillating pattern as the radial voidage. The numerical results were validated with experimental data. Preliminary studies to predict the residence time distribution has also been carried out using the multi-species transport model, which was also experimentally validated. The study suggests that DEM and CFD simulation can predict the flow behaviour as well as Residence Time Distribution (RTD) in a packed bed quite satisfactorily without the need to carry out experiments, which would be environmental friendly.

Discrete element simulating the hydrodynamic effects in acoustic agglomeration of micron-sized particles

ABSTRACTNumerical simulation of the acoustic agglomeration of micron-sized aerosol particles by a discrete element method (DEM) is demonstrated. The conventional DEM technique used in granular dynamics is modified for simulation of the acoustically induced attractive motion of particles in an incompressible fluid. The problem-specific orthokinetic collision, acoustic wake, and mutual radiation pressure effects yielding binary attraction and sticking of the particles are considered within the DEM approach. The acoustically induced agglomeration of two aerosol particles and 3D particles’ system is illustrated by numerical results. Numerical values of the agglomeration time of two particles obtained for a wide range of acoustic frequencies are analyzed. Comparison of various hydrodynamic effects with available experimental data indicates an overestimated contribution of the mutual radiation pressure model. The performance of the DEM technique and specific features concerning long-range interactions between particles are demonstrated by simulating 3D particles’ systems. The obtained numerical results illustrating the variation of number concentration with time are compared to available experimental data of coal-fired fly ash particles’ agglomeration; a relatively good agreement with the acoustic wake mechanism is observed.

Estimating energy in grinding using DEM modelling

The latest state of the art on Discrete Element Method (DEM) and the increased computational power are capable of incorporating and resolving complex physics in comminution devices such as tumbling mills. A full 3D simulation providing a comprehensive prediction of bulk particle dynamics in a grinding mill is now possible using the latest DEM software tools.This paper explores the breakage environment in mills using DEM techniques, and how these techniques may be expanded to provide more useful data for mill and comminution device modelling. A campaign of DEM simulations were performed by varying the mill size and charge particle size distribution to explore and understand the breakage environment in mills using DEM techniques. Analysis of each mill was conducted through consideration of the total energy dissipation and the nature of the collision environment that leads to comminution.The DEM simulations show that the mill charge particle size distribution has a strong influence on the mill input power and on the way the energy is distributed across the charge. The smaller particles experience higher energies while the larger experience less, but this variation is strongly dependent on the mill size. The results also showed that the average particle collision energy increases with increasing mill size, whereas its distribution over particle size is strongly influenced by the mill content particle size distribution. The simulations also captured the energy distribution within different regions of the tumbling charge, with the toe impact region having higher impact energies and the bulk shear region having higher tangential energies. Regardless of the mill size most of the energy is consumed by the particles in the mid-size range, which has the highest percentage mass of the total charge distribution.

Application of an enhanced discrete element method to oil and gas drilling processes

The authors present results on the use of the discrete element method (DEM) for the simulation of drilling processes typical in the oil and gas exploration industry. The numerical method uses advanced DEM techniques using a local definition of the DEM parameters and combined FEM-DEM procedures. This paper presents a step-by-step procedure to build a DEM model for analysis of the soil region coupled to a FEM model for discretizing the drilling tool that reproduces the drilling mechanics of a particular drill bit. A parametric study has been performed to determine the model parameters in order to maintain accurate solutions with reduced computational cost.

A simple FEM–DEM technique for fracture prediction in materials and structures

This paper presents a new computational technique for predicting the onset and evolution of fracture in a continuum in a simple manner combining the finite element method (FEM) and the discrete element method (DEM). Onset of cracking at a point is governed by a simple damage model. Once a crack is detected at an element side in the FE mesh, discrete elements are generated at the nodes sharing the side and a simple DEM mechanism is considered to follow the evolution of the crack. The combination of the DEM with simple 3-noded linear triangular elements correctly captures the onset of fracture and its evolution, as shown in several examples of application in two and three dimensions.

State of the art modeling of soil–tillage interaction using discrete element method

Soil–tillage interaction presents a continuous challenge for researchers, developers and manufacturers. However, modeling soil–tillage interaction is a complex process due to the following: the spatial variability of the soil media; the nonlinearity of soil material; and the contact phenomenon and flow that occur at the interface zone between the soil and the tillage tool. The need for a sound modeling technique for soil–tillage interaction is the motivation for the present work. The discrete element method (DEM) seems to be a promising approach for constructing a high-fidelity model to describe the soil–tillage interaction and may serve as a predictive simulation tool in the process of designing the tillage shape. The paper will explain, in general, the method and provide comprehensive state of the art studies of soil–tillage interaction based on 2D and 3D DEM simulations. The limitations and advantages of the method are demonstrated. The potential of the DEM to serve as an engineering tool for an optimization of soil–tillage interaction is presented by several case studies. Finally, future considerations and recommendations of improving the use of the DEM techniques are presented.

Discrete element modeling for predicting breakage behavior and fracture energy of a single particle in a jaw crusher

In the present study, Discrete Element Method (DEM) technique was applied to model the fracture behavior of a single spherical and cubic rock in a laboratory jaw crusher. The rocks studied were modeled as granular assemblies located between two jaws, and their fracture mechanism was studied. To verify the obtained results, the spherical and cubic specimens produced from Dokoohak Limestone and Dehbeed Granite were studied and the energy applied by the jaws was compared to those of the fracture energy estimated by the single particle breakage analysis. There is fairly good agreement between the energy acquired from the DEM model and the single particle fracture energy of the spherical rocks. It appears that DEM is a suitable method for predicting the crushing energy of the spherical rocks in the jaw crusher. The fracture behavior of the crushed rocks was examined and compared by the results obtained from the DEM model. The tensile mode of fracture occurring in the spherical rocks is well presented by the discrete element modeling. However, the DEM technique is not capable of modeling the delamination mode occurring in the cubic rocks.

Two‐dimensional discrete element models of debris avalanches: Parameterization and the reproducibility of experimental results

Application of the discrete element method (DEM) to model avalanches of granular materials requires determining the correct geometric and rheological parameters for and between the particles as well as for the basal surface. The use of spherical (circular in 2‐D) particles enhances particle rolling, yielding excessive runout values. The solution usually adopted to correct this effect is to introduce a drag force which artificially slows down the particle velocities. The aim of this study is to test the capability of the DEM to simulate well‐controlled unsteady channelized granular flows, considering the measured properties of the particles and of the basal surface which naturally contribute to dissipate energy. We first performed a parametrical analysis on a simple 2‐D model in order to estimate the influence of particle shape, friction parameters, and restitution coefficients on the dynamics of the flow and on the deposit geometry. We then simulated three channelized laboratory experiments performed with two materials and two bed linings. Using the geometrical layout and the values of the mechanical parameters provided by the authors, we obtained a remarkable agreement between the observed and 2‐D simulated deposit shapes for the three experiments. Also, the computed mass evolution with time was very consistent with the experimental snapshots in all cases. These results highlight the capability of the DEM technique for modeling avalanche of granular material when the particle shape as well as the friction and restitution coefficients are properly considered.

Modelling the solids inflow and solids conveying of single-screw extruders using the discrete element method

A new solids-conveying model for the single-screw extruder based on the Discrete Element Method (DEM) is proposed in this work. The polymer solids are treated as spherical particles moving in a 3-D environment which includes the feed hopper, the solids-inflow zone, and the solids-conveying region of an extruder, without inclusion of the plug flow assumption common to continuum models. Normal and tangential forces resulting from inelastic collisions with neighboring particles and surfaces dictate how each polymer pellet is conveyed through the model extruder. The DEM technique was implemented in this work to allow fundamental study of the local transport phenomena within the screw channel. Reported in this paper are results examining the cross- and down-channel velocity profile of solids in the screw; the residence time distribution; the cross-channel temperature profile; and the coordination number distribution. Two exit conditions were evaluated by the model: i) the open-discharge case where no compaction of the solids occurred; and ii) the restricted case where the axial pressure increased as the solids flowed towards the barrel exit. The predictions of the DEM simulations allowed for detailed observations of the solids movement in the screw, providing insight into the inherent flow fluctuations of extrusion systems.

Validation tests on a distinct element model of vibrating cohesive particle systems

The discrete element method (DEM) is becoming widely used to simulate granular flows. This method simulates the individual dynamics of all particles in an assembly by numerically integrating their acceleration resulting from all the contact forces. It is generally recognised that such a complex model must be validated by comparison with experimental results. Indeed the authors have addressed this in earlier publications given in the references. However, one important aspect is often given little attention, and that is testing the code to ensure that the computer program executes the model specification correctly. This paper describes in detail a DEM program for cohesive particle vibration and shows some simple simulations that have helped to verify the code. It is concluded that these ‘mathematical tests’ on artificial situations can uncover bugs in programs that appear to be running correctly, even if they appear to simulate real experiments reasonably well. These tests are published with the aim of helping others validate their programs in similar applications. The paper also discusses the widely used simplification of particle–particle interactions by Hooke's law and suggests that its validity depends upon the application. The main limitation of the DEM technique is the computational (CPU) time required. Techniques to minimise this are described, in particular in relation to particle referencing and array sizes. The runtimes shown illustrate the importance of optimising array sizes for the neighbourhood lists.