Discrete Element Method Model Research Articles

Performance analysis of vertical stirred mill based on multi-coupling method

To improve vertical mill performance, a vertical stirred mill is used as the research object. Firstly, an electromechanical multi-body dynamic model (EMBD) of the vertical stirred mill is established, followed by the establishment of a discrete element method (DEM) analysis model of the grinding media, and then the DEM-EMBD coupling model is formed. The feasibility of the DEM-EMBD coupling model is verified through experiments. On this basis, the stress distribution state of the helical agitator is analysed based on the coupling method of the discrete element method and finite element method (DEM-EMBD-FEM). The DEM-EMBD coupling model can better reflect the dynamic characteristics of the vertical stirred mill by comparing it with the DEM model and the coupling method of discrete element method and computational fluid dynamics (DEM-CFD) respectively. Finally, the effects of vertical stirred mill structural parameters, operating parameters and grinding media size on mill performance are investigated by the DEM-EMBD and DEM-EMBD-FEM coupling models. The approach then provides insights into the structural design of vertical stirred mills, motor selection, and the welding process between the helical blades and screw.

Efficient optimization parameter calibration method-based DEM simulation for compacted loess slope under dry–wet cycling

Dry–wet cycles can cause significant deterioration of compacted loess and thus affect the safety of fill slopes. The discrete element method (DEM) can take into account the non-homogeneous, discontinuous, and anisotropic nature of the geotechnical medium, which is more capable of reflecting the mechanism and process of instability in slope stability analysis. Therefore, this paper proposes to use the DEM to analyze the stability of compacted loess slopes under dry–wet cycles. Firstly, to solve the complex calibration problem between macro and mesoscopic parameters in DEM models, an efficient parameter optimization method was proposed by introducing the chaotic particle swarm optimization with sigmoid-based acceleration coefficients algorithm (CPSOS). Secondly, during the parameter calibration, a new indicator, the bonding ratio (BR), was proposed to characterize the development of pores and cracks in compacted loess during dry–wet cycles, to reflect the impact of dry–wet action on the degradation of bonding between loess aggregates. Finally, according to the results of parameter calibration, the stability analysis model of compacted loess slope under dry–wet cycling was established. The results show that the proposed optimization calibration method can accurately reflect the trend of the stress–strain curve and strength of the actual test results under dry–wet cycles, and the BR also reflects the degradation effect of dry–wet cycles on compacted loess. The slope stability analysis shows that the DEM reflects the negative effect of dry–wet cycles on the safety factor of compacted loess slopes, as well as the trend of gradual stabilization with dry–wet cycles. The comparison with the finite element analysis results verified the accuracy of the discrete element slope stability analysis.

Optimization of Discrete Element Method Model to Obtain Stable and Reliable Numerical Results of Mechanical Response of Granular Materials

The discrete element method (DEM) is largely used to simulate the geotechnical behavior of granular materials. However, numerical modeling with this type of code is expensive and time consuming, especially when fine particles are involved. This leads researchers to make use of different approaches to shorten the time of calculation without verifying the stability and reliability of numerical results, even though a compromise between the time of calculation and accuracy is commonly claimed. The particle size distribution (PSD) curve of studied granular material is completely ignored or arbitrarily cut. It is unclear if the ensued numerical results are still representative of the studied granular materials. Additionally, one can see a large number of numerical models established on a basis of calibration by ignoring the physical meaning and even measured values of some model parameters. The representativeness and reliability of the obtained numerical results are questionable. All these partly contribute to reducing the public’s confidence in numerical modeling. In this study, a methodology is illustrated to obtain an optimal DEM model, which minimizes the time of calculation and ensures stable and reliable numerical results for the mechanical behavior of a waste rock. The results indicate that the PSD curve of the studied waste rock can indeed be cut by excluding a portion of fine particles, while the Young’s modulus of the waste rock particles can also be decreased to accelerate the numerical calculations. A physical explanation of why the time of calculation can be shortened by reducing the Young’s modulus of waste rock particles is provided for the first time. Overall, the PSD cut, reduction in Young’s modulus, and time step must be determined through sensitivity analyses to ensure stable and reliable results with the shortest time of calculation. In addition, it is important to minimize the number of model parameters determined through the process of calibration, especially for those having physical meanings. In this study, the only model parameter having a clear physical meaning but difficult to measure is the rolling resistance coefficient for repose angle tests on the studied waste rock. Its value has to be obtained through a process of calibration against some experimental results. The validity and predictability of the calibrated numerical model have been successfully verified against additional experimental results.

Toward Large-Scale Simulation of Railroad Dynamics: Coupled Train–Track–Discrete Element Method Model

Toward Large-Scale Simulation of Railroad Dynamics: Coupled Train–Track–Discrete Element Method Model

A Self-Adaption Growth Model for the Burden Packing Process in a Bell-Less Blast Furnace

The burden structure directly decides the distribution of gas flow inside a blast furnace (BF). Falling, stacking, and descending bulk materials are the three main processes for burden formation, among which the stacking process plays a decisive role. The Discrete Element Method (DEM) and theoretical modelling were combined to predict stacking behavior in this study. Falling and stacking behaviors were first simulated based on DEM. The repose angle during the stacking process and mass fraction distribution in the radial direction were analyzed. Then, the upper, centroid, and lower trajectory falling lines were determined, and a polynomial relation was found between the angle and the packing height. The influences of three parameters on the repose angle were investigated. Compared with the natural repose angle and chute inclination angle, the effects of the trajectory line depth appeared trivial. The polynomial relation between the repose angle and the packing height was specified to be a function of the natural angle of repose and the chute inclination angle. A three-trajectory falling model and quadratic expression were embedded in the theoretical model, yielding a self-adaption packing model. The model was proved reliable with a low relative error, below 15%.

Discrete Element Method Simulation of Vibratory Filling of Convoluted Hot Isostatic Pressing Canisters Using Idaho Calcine Waste Simulant

This research presents a discrete element method (DEM) model for simulating the vibratory filling of the Idaho calcine waste simulant into various convoluted hot isostatic pressing canisters. The simulation closely emulates the experimental vibratory powder-filling processes, achieving accurate representations of surface profiles and powder bed heights. Notably, the model underestimates lower fill levels but demonstrates improved accuracy at higher levels due to diminished air influence. Executed on a consumer-grade desktop PC, the DEM model replicates tapped powder bed heights to within millimeters, proving its capability to efficiently simulate commercial-scale bulk material handling processes using standard computing hardware.

Experimental Investigation and Numerical Analysis Regarding the Influence of Cutting Parameters on the Asphalt Milling Process.

Abrasion wear is a significant concern for cutting tools, particularly when milling asphalt concrete due to the presence of hard mineral aggregate particles. The pressure exerted on the cutting tool by the chipped material and the resulting cutting forces directly influence tool wear. To estimate the cutting forces in asphalt milling, the authors propose using either laboratory experiments or cost-effective Discrete Element Method (DEM) modeling-by simulating the real conditions-as direct measurement under real conditions is challenging. This article presents results from an original experimental program aimed at determining the cutting forces during asphalt pavement milling. A specialized stand equipped with a moving plate and recording devices was designed to vary milling depth, rotational speed, and advance speed. The experimental results for horizontal force values were compared with numerical results from DEM modeling. It was found that both increasing the milling depth and the advance speed lead to higher cutting forces. Generally, DEM modeling trends align with experimental results, although DEM values are generally higher. The statistical analysis allowed identification of the milling depth as the most significant parameter influencing cutting force and the optimal combination of milling parameters to achieve minimum horizontal force acting on cutting tooth, namely, 15 mm milling depth and 190 mm/min advanced speed.

DEM Simulation of the Idaho Calcine Simulant for Hot Isostatic Pressing Canister Filling Process: Part 2

This paper introduces a novel approach to the bulk material handling of simulated radioactive material, focusing on the challenging Idaho calcine waste. Due to the limited availability of the simulant, virtual dynamic simulations were utilized to develop technology demonstration−scale models to assess the efficacy of the discrete element method (DEM) for process development studies. The DEM model was validated using historical experimental data, demonstrating its feasibility with affordable hardware. Acknowledging the limitations of computational analysis, the presented contact model is deemed adequate for preliminary engineering studies. This research advances bulk material handling and provides valuable insights for nuclear waste treatment processes, offering a pioneering framework for researchers working with the Idaho calcine simulant.

Quantifying the effects of inlet gas and collision models in direct metal deposition using a CFD-DEM approach

Simulations of the powder jet in direct metal deposition (DMD) are often made with significant simplifications such as being incompressible, steady-state, or single-component, and do not provide explanation for the choice of parameters in the collision model. This work presents a coupled Computational Fluid Dynamics–Discrete Element Method model for the powder jet in DMD that considers all of the following features: compressibility effects, particle–wall and particle–particle collisions, turbulence, gas mixing, and melt pool boundaries. The goal of the simulation is to optimize the operating conditions and to predict the outcomes of experiments. After effective validation against experimental results, the effects of inlet gas, collision models and different boundary conditions in DMD have been comprehensively studied. It is demonstrated that gases with higher diffusivities, such as helium, are less effective shielding gases than those with lower diffusivities, such as argon. The increased wall temperature arising from the melt pool and track has little influence on the particle distribution.

Simulation of flip-flow screening adhesive organic fertilizer particles based on DEM-MBD coupling method

For screening adhesive organic fertilizer particles, a Discrete Element Method (DEM) and Multi-Body Dynamics (MBD) coupling model of screening adhesive organic fertilizer particles using a flip-flow screen is established. Then, the velocity, the distribution and the trajectory of the particles during the screening process are observed. Finally, the effects of the surface energy γ, the rotational speed n, the tensional amount ∆l and the feed rate M are investigated. The results show that the flip-flow screen could provide a high velocity for depolymerization of agglomerated particles and separation of adhesive particles from the screen panels, so adhesive organic fertilizer particles can be successfully screened by using the flip-flow screen and organic fertilizer particles in an easily absorbed range are obtained. With the increase of γ, both the flow rate and the screening efficiency decrease. With the increase of n, both first increase and then slightly decrease. With the increase of ∆l, both increase at a low n, or slightly decrease at a high n. With the increase of M, the screening efficiency decreases, while the total flow rate first increases and then decreases. Through adjusting n, ∆l, M, flip-flow screen can also be used to screen other adhesive particles.

Fast predicting the trajectory of chip-like particles by integrating a discrete element method model with a computational fluid dynamics-based aerodynamic database

The accumulation of ice within aircraft engines poses a significant safety concern, necessitating effective and accessible methods to predict ice particle shedding trajectories. This study develops a novel method by integrating the discrete element method with a computational fluid dynamics (CFD)-based aerodynamic database, aiming to accurately predict the trajectories of chip-like ice particles under various conditions. The accuracy of the CFD-based aerodynamic database is validated through a quantitative comparison with experimental data, and the predicted trajectories align well with the experimental trajectories under varied conditions following a database-independence analysis. The results indicate that aerodynamic coefficients are independent of both the relative velocity and the scaling factor (k) for chip-like particles. Moreover, the initial angle of attack significantly influences the translational and rotational dynamics of chip-like particles. Furthermore, the chip-like ice particles released closer to the engine inlet exhibit a more uniform distribution of landing points, whereas those released at longer distances from the engine inlet tend to converge toward the central area of the engine. The methodology developed in this paper is expected to be a promising tool for fast predicting the trajectories of chip-like particles, thereby enhancing engine protection against ice impacts and improving overall operational safety.

Contribution to micromechanical modeling of the shear wave propagation in a sand deposit

The object of study is the vertical wave propagation in a sand deposit. This paper is aimed at analyzing the vertical wave propagation in a sand deposit through micromechanical modeling that inherently takes account of intergranular slips during deformation. Such a problem, which is part of the general framework of wave propagation in the soil, has long been analyzed using continuum models based on approximate behavior laws. For this purpose, a 2D Discrete Element Method (DEM) model is developed. The DEM model is based on molecular dynamics with the use of circular shaped elements. The intergranular normal forces at contacts are calculated through a linear viscoelastic law while the tangential forces are calculated through a perfectly plastic viscoelastic model. A model of rolling friction is incorporated in order to account for the damping of the grains rolling motion. Different boundary conditions of the profile have been implemented; a bedrock at the base, a free surface at the top and periodic boundaries in the horizontal direction. The sand deposit is subjected to a harmonic excitation at the base. Using this model, the fundamental and resonance frequencies of the deposit are first determined. The former is determined from the low-amplitude free vibration and the latter by performing a variable-frequency excitation test. It is noted that there is a significant gap between the two frequencies, this gap could be attributed to the degradation of the soil shear modulus in the vicinity of the resonance. Such degradation is well proven in classical soil dynamics. The effects of deposit height and confinement on resonance frequency and free-surface dynamic amplification factor are then investigated. The obtained results highlighted that the resonance frequency is inversely proportional to the deposit’s thickness whereas the dynamic amplification factor Rd increases with the deposit’s thickness. In the other hand, when the confinement increases the deposit becomes stiffer, which results in reducing the amplification. Such result is in accordance with theoretical knowledge which states that the most rigid profiles such as rocks do not amplify seismic movement.

Establishment and validation the DEM-MBD coupling model of flexible straw-Shajiang black soil-walking mechanism interactions

With the implementation of the conservation tillage policy, the farmland surface layer is covered with a large amount of straw, and the soil of the plowing layer is mixed with a small amount of straw, which makes it difficult for the walking mechanism of the agricultural machinery to obtain the required driving force, resulting in reduced driving stability and difficult to control. In response to the analysis of the mechanism of inter-operation with soil mixed with straw during the operation of the walking mechanism of agricultural implements, the problem is the lack of accurate and reliable discrete elemental models of flexible straw-Shajiang black soil-walking mechanism interactions. This paper takes the tracked walking mechanism as the research object and establishes the dynamics model of the tracked walking mechanism interacting with mixed straw soil based on the coupling algorithm of DEM (Discrete Element Method) and MBD (Multi-Body Dynamics). The intrinsic parameters of soil and straw were determined experimentally, and a discrete elemental model of the interaction between Shajiang black soil and flexible straw was established based on the EEPA (Edinburgh Elasto-Plastic Adhesion) model and the Bonding V2 model, which was optimally solved through in-laboratory bearing tests to obtain the following results: the soil particles surface energy, Δγ, was 12.74 J/m2, and the plastic deformation ratio, λp, was 0.45; Based on the physical test, the simulated stacking angle and slope slip test were used as evaluation indexes, which resulted in a coefficient of restitution of the upper soil and rubber of 0.501, a static friction coefficient of 0.428, and a rolling friction factor of 0.089; The coefficient of restitution of the lower soil and rubber was 0.459, the static friction coefficient was 0.478, and the rolling friction factor was 0.073; We established a DEM-MBD model of flexible straw-Shajiang black soil-walking mechanism interactions, and started a field validation test using the stress value of the soil after being crushed by a tracked vehicle as an evaluation index. The validation results show that, under the forward speed of 1 km/h, the relative error between the simulated and measured values of the stresses on the soil is 7.46 %. It indicates that this paper establishes an accurate and reliable DEM model for the interaction of flexible straw-Shajiang black soil-walking mechanism, which can provide a theoretical basis and technical reference for revealing the mechanism of interaction between the walking mechanism of agricultural machinery and the soil, the optimization of the structure of machinery and the selection of operating parameters.

3D DEM investigation of shear behavior and interaction mechanism of woven geotextile-sand interfaces

This paper presents a numerical study on the investigation of microscopic mechanism governing the interaction of woven geotextile and angular sand employing the 3D discrete element method (DEM). The surface texture and tensile properties of the geotextile were simulated using overlapping spherical particles, and the angular sand was simulated using rigid blocks. The DEM models were fully calibrated based on previous experimental data. The shear and dilation zones of sand near the interface were quantitatively determined based on particle displacement gradients. Analysis of contact forces was conducted to explain the microscopic mechanism behind the macroscopic strength evolution. The influence of geotextile surface roughness on the shear strength of the geotextile-sand interface is also discussed. The results show that the failure mode of the woven geotextile-sand interface is a combination of particle sliding failure along the geotextile surface and shear failure of the sand within the shear zone above the interface. There is a rapid redistribution of contact forces prior to reaching peak shear resistance, and the average normal contact force within the shear zone remains relatively constant after the peak shear stress is achieved. A completely developed shear zone stabilizes soil deformation, typically after achieving the peak shear resistance.

Measuring and modelling of soil displacement from a horizontal penetrometer and a sweep using an IMU sensor fusion and DEM

When simulating soil tillage processes using the discrete element method (DEM), it is essential to know the discrete element micromechanical parameters that describe the soil model, and this requires calibration. The formulation of a model that accurately reflects the behaviour of the soil from several perspectives is only possible by employing several different measurement procedures and DEM simulations. For this reason, four different measurements were used in this study for the purpose of calibrating the DEM model’s micromechanical parameters for sandy soil with a dry based moisture content of 4.1 %. The cone penetration resistance was measured with a horizontal penetrometer that was developed in-house and a vertical penetrometer, while a displacement sensor placed in the soil provided information on the internal movement of the soil, and the draught force of a sweep tool was also monitored. The DEM models of the measurements were defined in Altair EDEM® software using the hysteretic spring contact model. To model the soil, spherical elements and clump elements were examined. The displacement sensor was modelled with a clump element, whereas the sweep tool and the horizontal and vertical penetrometers were taken into account as rigid surface models. Based on the simulations, it was determined that the clump elements examined are not suitable for proper calibration with the hysteretic-spring contact model, because, as a consequence of the large coordination number, they excessively increased the draught force by getting stuck in front of the tools and measuring devices. By studying sweep tool simulations, it was observed that, in terms of the particle sizes used, particles with a higher density and higher bulk density resulted in a higher draught force, but at the same time, they moved at a lower speed. Finally, by taking vertical penetrometer measurements and running simulations, the soil model created with spherical elements was validated with a relative error of 8.7 % which can describe the sandy soil with sufficient accuracy in all the examined aspects.

Optimisation of calibration parameters for a discrete element method (DEM) model of plant-origin grains with a low elasticity modulus

This paper presents the application of the Discrete Element Method (DEM) to describe the physical properties of plant-origin grains with a low elasticity modulus for the needs of numerical simulation of processing processes. The study proposes the modelling of maize grains based on 3D scanning of real grains and further use of the multi-sphere method to fill the numerical model with a conglomerate of elementary spheres. The main aim of the paper is to develop a calibration method based on exploring parameter spaces at points selected using Sobol's grids. As criteria and functional limitations for the calibration, the following were proposed: the slope angle of repose (AoR), the radius of the heaped cone's vertex (Rad), the number of grains, and the slope height. The study results show that for the calibration of the DEM model describing maize grains, test points with a set of the following nine parameters should be used: Poisson's Ratio for grain, Density of grain, Shear Modulus, Coefficient of Restitution for grain-grain, Coefficient of Restitution for grain-material, Coefficient of static friction for grain- grain, Coefficient of static friction for grain-material, Coefficient of rolling friction for grain-grain, and Coefficient of rolling friction for grain-material.

Atmospheric entry and strewn fields estimation for rubble-pile meteoroids

One of the potentially catastrophic risks to human survival is the impact of a meteorite on Earth. When a meteoroid enters the atmosphere at an ultra-high speed, a series of complex evolution processes occur, mainly including ablation, fragmentation, airburst, and ground impact. This paper proposes a new systematic dynamical method for simulating the entire process of a meteoroid entering the atmosphere. In the new method, the DEM (Discrete Element Method) model is utilized to describe the initial structure and shape of a rubble-pile meteoroid. A combination of an aerodynamic trajectory model, a thermal ablation model, and an airburst model is introduced to simulate the entry process. Particularly, the Jone-Wilkins-Lee state equation is employed to characterize the large-scale airburst phenomenon caused by the internal expansion of the meteoroid. Referring to the observational data of the Chelyabinsk meteorite event, this paper parametrically simulates the trajectories, ablation, fragmentation, and airburst, and predicts the strewn field of different-shaped meteoroids. Compared with existing debris cloud models, this method considers the shape effect of rubble-pile meteoroids and can obtain the strewn field as a side effect. Numerical validation is carried out, indicating the result of the new method is more in line with the actual scenarios.

Solid–fluid force modeling: Insights from comparing a reduced order model for a pair of particles with resolved CFD-DEM

Solid–fluid force models are essential to efficiently model multiple industrial apparatuses such as fluidized beds, spouted beds, and slurry transport. They are generally built using strong hypotheses (e.g. fully developed flow and no relative motion between particles) that affect their accuracy. We study the effect of these hypotheses on particle dynamics using the sedimentation of a pair of particles. We develop new induced drag, lift and torque models for pairs of particles based on an artificial neural network (ANN) regression. The fluid force model covers a range of Reynolds numbers of 0.1 to 100 and particle centroid distance of up to 9 particle diameters. The ANN model uses 3475 computational fluid dynamics (CFD) simulation results as the training data set. Using this fluid force model, we develop a reduced-order model (ROM), which includes the virtual mass force, the Meshchersky force, the history force, the lubrication force, and the Magnus force. Using the results of a resolved computational fluid dynamics coupled with a discrete element method (CFD-DEM) model as a reference, we analyze the discrepancies between the ROM and CFD-DEM results for a series of sedimentation cases that cover particle Archimedes number from 20 to 2930 and particle to fluid density ratio of 1.5 to 1000. The errors primarily stem from particle history interactions that are not accounted for by the fully developed flow hypothesis. The importance of this effect on the dynamic of two particles is isolated and it is shown that it is more pronounced in cases with a lower particle-to-fluid density ratio (such as solid–liquid cases). This work underscores the need for more research on these effects to increase the precision of solid–fluid force models for small particle-to-fluid density ratios (1.5).

Modeling Mechanochemical Depolymerization of PET in Ball-Mill Reactors Using DEM Simulations.

Developing efficient and sustainable chemical recycling pathways for consumer plastics is critical for mitigating the negative environmental implications associated with their end-of-life management. Mechanochemical depolymerization reactions have recently garnered great attention, as they are recognized as a promising solution for solvent-free transformation of polymers to monomers in the solid state. To this end, physics-based models that accurately describe the phenomena within ball mills are necessary to facilitate the exploration of operating conditions that would lead to optimal performance. Motivated by this, in this paper we develop a mathematical model that couples results from discrete element method (DEM) simulations and experiments to study mechanically-induced depolymerization. The DEM model was calibrated and validated via video experimental data and computer vision algorithms. A systematic study on the influence of the ball-mill operating parameters revealed a direct relationship between the operating conditions of the vibrating milling vessel and the total energy supplied to the system. Moreover, we propose a linear correlation between the high-fidelity DEM simulation results and experimental monomer yield data for poly(ethylene terephthalate) depolymerization, linking mechanical and energetic variables. Finally, we train a reduced-order model to address the high computational cost associated with DEM simulations. The predicted working variables are used as inputs to the proposed mathematical expression which allows for the fast estimation of monomer yields.

Micromechanical analysis of contact erosion under cyclic loads using the coupled CFD‒DEM method

Different layers of soil often have distinct particle sizes. When exposed to the natural environment, soil is easily affected by natural rainfall, rising groundwater levels, and human activities, leading to particle contact erosion, which reduces the safety and service performance of the soil structure. In this paper, a coupled computational fluid dynamics–discrete element method (CFD–DEM) model was employed to investigate the particle migration phenomena, mechanical response of contact interfaces, variations in flow fields, and macroscopic deformation during the contact erosion process under cyclic loads at different frequencies and amplitudes. The conclusions are presented as follows: (1) Within one cycle of cyclic loading, both compression during loading and stress relaxation during unloading are the main factors triggering the migration of fine particles. (2) The migration and loss of fine particles mainly occur in the early stages of cyclic loading, where strong contact force chains are formed within the fine particle layer, leading to significant plastic deformation of the soil at the macroscopic level. (3) Under cyclic loading, changes in the soil pore structure cause an upwards hydraulic gradient in the initial quiescent water flow field. This hydraulic gradient can rupture weak contact force chains and cause particle pumping. (4) Increasing the frequency and amplitude of cyclic loading intensifies the erosion of fine particles, causing greater axial deformation of the soil. Compared to cyclic loading frequency, the amplitude of cyclic loading has a greater impact on contact erosion.