Discrete Element Method Research Articles

Capturing the random mechanical behaviour of granular materials: a comprehensive stochastic discrete-element method study

This research pioneers a stochastic discrete-element method (DEM) by integrating the probability density evolution method (PDEM), offering a novel approach to connect particle-scale property uncertainties, specifically inter-particle friction coefficient (μ) and particle shear modulus (Gp), with macro-scale soil behaviour. Through 1100 DEM simulations, this study reveals that, for uniform particle size distribution, the uncertainty in μ substantially affects large-strain soil behaviour, with its effect being associated with packing density and soil state. The uncertainty effect of μ remains pronounced at the critical state, while the packing density effect diminishes. Stress distribution appears insensitive to uncertainty of μ, rather suggesting a predominant influence of particle size distributions. In contrast, the uncertainty effect of μ becomes negligible on small-strain behaviour, demonstrating a limited effect on small-strain stiffness. Uncertainty in Gp presents limited effects on large-strain behaviour, including stress ratios and dilatancy. At small strains, Gp shows a significant impact on stiffness, diverging from minimal influence identified for μ. This study presents a framework that integrates experimental techniques to study particle-scale uncertainty propagation, enhancing predictions of macro-scale soil behaviour. This approach could be beneficial for precise multi-scale simulations, incorporating particle-level uncertainties in engineering-scale models, thereby improving geotechnical practice predictability.

Design and Testing of Key Components for a Multi-Stage Crushing Device for High-Moisture Corn Ears Based on the Discrete Element Method

To improve the crushing efficiency and crushing pass rate of high-moisture corn ears (HMCEs), a multi-stage crushing scheme is proposed in this paper. A two-stage crushing device for HMCEs is designed, and the ear crushing process is analyzed. Firstly, a simulation model for HMCEs was established in EDEM software (2018), and the accuracy of the model was verified by the shear test. Subsequently, single-factor simulation experiments were conducted, with the crushing rate serving as the evaluation index. The optimal working parameter ranges for the HMCE device were identified as a primary crushing roller speed of 1200–1600 revolutions per minute (r/min), a secondary crushing roller clearance of 1.5–2.5 mm, and a secondary crushing roller speed of 2750–3750 r/min. A Box–Behnken experiment was conducted to establish a multiple regression equation. With the objective of maximizing the qualified crushing pass rate, the optimal combination of parameters was revealed: a primary crushing roller speed of 1500 r/min, a secondary crushing roller clearance of 2.5 mm, and a secondary crushing roller speed of 3280 r/min. The pass rate of corn cob crushing in the simulation test was 98.2%. The physical tests, using the optimized parameter combination, yielded a qualified crushing rate of 97.5%, which deviates by 0.7% from the simulation results, satisfying the requirement of a qualified crushing rate exceeding 95%. The experimental outcomes validate the rationality of the proposed crushing scheme and the accuracy of the model, providing a theoretical foundation for subsequent research endeavors.

Experimental evaluation of the effect of pullout velocity on the behavior of multi-plate anchors

The determination of the pullout capacity of anchors has been a key point of offshore and onshore applications, considering factors such as the shape, size, penetration velocities, and pull-out velocities of the anchors. Multi-plate expandable anchors can be considered as an alternative that exhibits higher capacity compared to single plate anchors. While previous studies have demonstrated the influence of penetration velocity, there is a lack of research investigating the pullout capacity of multi-plate expandable anchors. In the present study, experimental tests were conducted to investigate the effect of various pull-out velocities. Different soil relative densities and the distance between anchors were examined in the laboratory tests. The study also employed two analytical methods—constant control volume and movement control volume—to investigate the results of pull-out velocity. In addition, the Discrete Element Method (DEM) was used to analyze the effect of particle shape on the results. In the experimental tests, the findings suggest that increasing the pull-out velocity from 10 to 30 mm/min improved the pullout capacity of anchors and the optimal distance between plate anchors was determined to be 1B. The DEM findings showed that the sharp-cornered shape had good agreement with experimental results.

Experimental and numerical study on the force transmission in granular packings under the hypergravity

Granular materials are ubiquitous in our environment, and their mechanical behavior is determined by particle-scale properties. The contact forces under hypergravity, which are crucial to planetary geology, remain underexplored, while extensive research has focused on behavior under surface pressure. We measured the contact forces between granular particles using a novel matrix film sensor under both hypergravity and surface pressure conditions, which were achieved in centrifugal and servo-hydraulic tests. Additionally, computations using the discrete element method were conducted to investigate the different patterns of force transmission from a microscopic perspective. We found an intriguing invariance in the contact force distribution under increased surface pressure. However, hypergravity enhances the contact forces between unjammed fine particles, causing contact forces converge to the distribution observed under surface pressure. Finally, a power-law fitted correlation was proposed to estimate the difference in contact force distributions between conditions of hypergravity and equivalent surface pressure.

Heterogeneous temperature characteristics considering rainfall effect during construction of an integrally-poured rock-filled concrete arch dam

Integrally-poured arch dam with the material of rock-filled concrete (RFC) is a new and rapid construction technology for mass concrete structures. There is still limited literature regarding the heterogeneous temperature field of RFC, especially under special weather conditions. In this study, a novel mesoscale model of heterogeneous RFC was generated through a combination of the discrete element method (DEM), the finite element method (FEM), and the background grid mapping method (BGMM). Based on the monitoring experiments at the Longdongwan project, this study greatly enhances the simulation precision and details by incorporating a two-phase material of heterogeneous RFC model, i.e. the stochastic pre-laid rocks and layered SCC (self-compacting concrete), and refining the analysis time step to an hourly basis. The results show that: (1) An infinite heat convection coefficient on the exposed RFC surfaces was effective in simulating the rainfall effect, and the mesoscopic simulation results aligned well with the monitoring data. (2)The cold wave with rainfall can cause a notable drop of around 10 °C in the placement temperatures of both rocks and SCC, and lowered the temperature rise by about 5°C for the subsequent freshly poured RFC lift. (3) The hydration temperature rise was recorded the highest (13–14°C) in the areas near the dam abutment, due to challenges of placing rocks. These findings can provide insights and advice for similar construction scenarios.

Computed Tomography-Driven Analysis of Particle Breakage Using a Coupled FDM-DEM Approach

This study proposes a refined approach for simulating the mechanical behavior of soils under high stress by integrating the Finite Difference Method-Discrete Element Method (FDM-DEM) with in-situ experiment. This novel framework incorporates advanced technologies such as flexible membrane and X-ray computed tomography (CT) to enhance the predictive capabilities of the simulation with physical insight. The FDM-DEM model adeptly simulates irregular particle shapes, capturing their interactions and the dynamics of particle breakage. The use of flexible membrane within the model further enriches this approach by enabling the capture of deformation responses in granular materials during shearing. Moreover, the adoption of CT technology facilitates continuous optimization of the simulation process. Validation through in-situ experiments has confirmed the model's effectiveness. The ability of the model to predict areas of high stress concentration—and their correlation with observed particle breakage patterns—underscores the utility of the enhanced FDM-DEM framework as a robust predictive tool for understanding the behavior of granular materials under shearing.

Effect of aggregate size on the slump and uniaxial compressive strength of concrete: a DEM study

The aggregate size and particle-size distribution (PSD) can change the packing density, slump, and strength of concrete. The micromechanical effects of aggregate size on the slump and strength remain unclear. The current numerical study examined concrete behavior using slump and uniaxial compressive strength (UCS) tests considering the aggregate size distribution using the discrete element method. The effect of the aggregate size on the packing density, UCS, and slump of the concrete was analyzed. To accomplish this, we evaluated how variations in the uniformity and curvature coefficients of the PSD, as well as the specific surface area of the samples, were affected by changes in aggregate size. Although the simulations were based on standard specimens from the laboratory, the results showed good agreement with the documented experimental results. Briefly, at a 40–60% fine aggregate content, the packing density and compressive strength of the concrete reached their peaks and caused a decrease in the height of the slump. The uniformity and curvature coefficients did not influence the slump height. The induced shear band could be tracked during the UCS tests and the crack angles could be measured. At the optimum fine content (40–60%), the shear bands were primarily localized and propagated through the samples having different fine contents.

Research on the Influence of Particles and Blade Tip Clearance on the Wear Characteristics of a Submersible Sewage Pump

A submersible sewage pump is designed for conveying solid–liquid two-phase media containing sewage, waste, and fiber components, through its small and compact design and its excellent anti-winding and anti-clogging capabilities. In this paper, the computational fluid dynamics–discrete element method (CFD-DEM) coupling model is used to study the influence of different conveying conditions and particle parameters on the wear of the flow components in a submersible sewage pump. At the same time, the energy balance equation is used to explore the influence mechanism of different tip clearance sizes on the internal flow pattern, wear, and energy conversion mechanism of the pump. This study demonstrates that increasing the particle volume fraction decreases the inlet particle velocity and intensifies wear in critical areas. When enlarging the tip clearance thickness from 0.4 mm to 1.0 mm, the leakage vortex formation at the inlet is enhanced, leading to increased wear rates in terms of the blade and volute. Consequently, the total energy loss and turbulent kinetic energy generation increased by 3.57% and 2.25%, respectively, while the local loss coefficient in regard to the impeller channel cross-section increased significantly. The findings in this study offer essential knowledge for enhancing the performance and ensuring the stable operation of pumps under solid–liquid two-phase flow conditions.

A novel freemium code SAND (v1.0) for generation of randomly packed beds

The main current approaches for generation of the packed bed models are based on rigid body dynamics (RBD) and Newton's laws (discrete element methods - DEM). This paper deals with the development and analysis of a novel code based on analytical geometry approach for the packed bed generation. The architecture and main algorithms of the novel code are described and clarified. The parameters of the packed bed generated via the novel code are compared with experimental data and packed beds generated via Blender (RBD), Yade (DEM). The novel code demonstrates many advantages, such as good correlation with experimental data, no overlaps between pellets in the packed bed, and a low computational time for packed bed generation. The packed bed model can be directly exported in .step format. Other advantages are also demonstrated and clarified. The novel code is attached to this paper and can be freely used by engineers and scientists.

Simulation of special-shaped graded particulate hydraulic transport in deep-sea mining scenarios

Hydrodynamic transport is crucial in deep-sea mining engineering for conveying materials. This study investigates the impact of various particle shapes on slurry transport efficiency and flow characteristics at higher concentrations. A numerical method combining computational fluid dynamics (CFD) and the discrete element method (DEM) within the Euler-Lagrange framework is employed to simulate the flow and hydrodynamic properties of graded heterogeneous coarse particles in a deep-sea hydraulic lift pipe. The reliability of the simulations is verified through comparisons, focusing on feed concentration and particle gradation effects on dynamic characteristics and flow patterns. The study quantitatively analyzes concentration distributions under various flow regimes for different particle shapes and conveying concentrations in a vertical pipeline system. Flow characteristics under clogging conditions are described, considering flow transition and concentration distribution. Additionally, conditions for stable transportation are discussed concerning particle forces and transport reliability.

CFD–DEM comparison of slurry infiltration in laboratory column tests and in real-world tunnelling

Slurry infiltration and filter cake formation are critical for excavation surface stability in slurry shield tunnelling. Laboratory column tests are frequently adopted to study macroscopic infiltration. However, these tests, in a vertical orientation and confined by an impermeable cylindrical boundary, may not be a good representation of horizontal infiltration into an unbounded stratum in real-world tunnelling. In this paper, a more realistic slurry pressure balance (SPB) tunnelling model was created to overcome the limitations of simulated laboratory column tests. Coupled computational fluid dynamics (CFD)–discrete element method (DEM) numerical simulations were carried out to study the slurry infiltration into sand for this model and compare the results with the conventional laboratory column test model. Both models produced the same types of filter cakes. The SPB tunnelling model yielded larger infiltration distances and ranges, but a lower normalised permeability in the sand region in front of the tunnel face. The fluid pressure within this region dissipated much faster in the SPB tunnelling model, resulting in rapid velocity decreases and a faster infiltration process. Although the SPB tunnelling model is more representative of real-world tunnelling, the conventional laboratory column test is conservative, producing similar types of filter cakes over a longer timeframe.

Accelerating Laser Powder Bed Fusion: The Influence of Roller-Spreading Speed on Powder Spreading Performance

The powder spreading process is a fundamental element within the laser powder bed fusion (PBF-LP) framework given its pivotal role in configuring the powder bed. This configuration significantly influences subsequent processing steps and ultimately determines the quality of the final manufactured part. This research paper presents a comprehensive analysis of the impacts of varying spreading speeds, which are enabled by different roller configurations, on powder distribution in PBF-LP. By utilizing extensive Discrete Element Method (DEM) modelling, we systematically examine how spreading speed affects vital parameters within the spreading process, including packing density, mass fraction, and actual layer thickness. Our exploration of various roller configurations has revealed that increasing spreading speed generally decreases packing density and layer thickness for non-rotating, counter-rotating, and forward-rotating rollers with low clockwise rotational speeds (sub-rolling) due to powder dragging. However, a forward-rotating roller with a high clockwise rotational speed (super-rolling) balances momentum transfer, enhancing packing density and layer thickness while increasing surface roughness. This configuration significantly improves the uniformity and density of the powder bed, providing a technique to accelerate the spreading process while maintaining and not reducing packing density. Furthermore, this configuration offers crucial insights into optimizing additive manufacturing processes by considering the complex relationships between spreading speed, roller configuration, and powder spreading quality.

Analysing the flow of wet iron ore in an industrial transfer chute using discrete element method

Analysing the flow of wet iron ore in an industrial transfer chute using discrete element method

Reconstruction of geometrical structure of claw of Marmota and research of soil-claw interaction

The Himalayan marmot can excavate soil efficiently, and the geometric structure of its claw and its movement during excavation can provide a reference for the design of soil tillage components. In this paper, the geometric model of the claw is reconstructed using reverse engineering methods, and its contour curves are fitted and curvature analyzed. It is found that the marmot's claw can break the soil with high efficiency and excellent sliding-cutting action. The interaction relationship between the soil and claw was simulated using the discrete element method, and the effects of working depth and rake angle on the horizontal force, soil disturbance area, and soil particle velocity were analyzed. The results showed that the horizontal force increased with the increase of working depth, and first increased and then decreased with the increase of rake angle. The optimal working effect was achieved when the rake angle was 75°.

Analysis of thixotropy of cement grout based on a virtual bond model

Thixotropy of cementitious materials is a crucial intrinsic property that determines the flowability and workability of cement-based grout. A novel virtual bond model of cement particles is developed in this paper to depict the thixotropy of cement grout. A particulate description of the reversible and erasable interparticle bonds is established based on experimental observations with a focus on the non-contact interactions mainly contributed in practice by calcium silicate hydrates (C–S–H). The structural breakdown of the cement network is realized through bonds breakage under applied motion, and the bonding network recovers with regeneration of interparticle connections that involve reversible hydrate reactions in the mixture. The balance between bond rupture and rebuilding can be tuned by assigning different strength limits for bond breakage. We have implemented this model in the open-source code Yade to carry out 3D discrete element method simulations of a rotational vane system filled with spherical particles, and the results show good agreement with experimental data. The modelling results reveal the transition from a solid-like structure to a fluid-like medium within cement suspensions caused by the evolution of broken interparticle bonds. The results also provide a distinct view of thixotropic variation upon disturbance. This model is extendable to other cohesive materials providing an explicit physical definition of the interparticle interactions. It also provides a theoretical explanation for the empirical estimations of thixotropy common in engineering industries and a potential means of measuring cementitious granular flow that may be useful in future studies.

Non-smooth discrete element method analysis of channel width's effect on ice resistance in broken ice field

A numerical model based on NDEM is used to investigate the effect of channel width on broken-ice resistance in the channel. The model incorporates a limited impulse method to simulate the ice crushing failure. The accuracy of the numerical model is benchmarked against experimental data from model tests conducted on the Araon icebreaker at KRISO. The simulations successfully capture the characteristic effects of channel width on broken-ice resistance observed in the experiment. Beyond benchmarking of the numerical model, this study analyses the force chain characteristics in the broken ice field, revealing the crucial role of force chains in the resistance increase caused by channel width constraints. Building upon the established numerical model, further sensitivity analyses are conducted to investigate the correlation between channel width effect and other relevant factors such as ice concentration, ship velocity and ice thickness. Among these factors, it is found that ice concentration emerges as the predominant determinant of the critical channel width. The increase in ice resistance attributable to the channel width is exacerbated under the condition of thicker ice floes and lower ship velocity, where the occurrence of ice floe rotation is less frequent and the corresponding force chains are stronger and more stable.

Development of a high-fidelity digital twin using the discrete element method for a continuous direct compression process. Part 2. Validation of calibration workflow

This paper is the second in a series of two that describes the application of discrete element method (DEM) and reduced order modeling to predict the effect of disturbances in the concentration of drug substance at the inlet of a continuous powder mixer on the concentration of the drug substance at the outlet of the mixer. In the companion publication, small-scale material characterization tests, a careful DEM parameter calibration and DEM simulations of the manufacturing process were used to develop a reliable RTD models. In the current work, the same calibration workflow was employed to evaluate the predictive ability of the resulting reduced-order model for an extended design space. DEM simulations were extrapolated using a relay race method and the cumulative RTD was accurately parameterized using the n-CSTR model. By performing experiments and simulations, a calibrated DEM model predicted the response of a continuous powder mixer to step changes in the inlet concentration of an API. Thus, carefully calibrated DEM models was used to guide and reduce experimental work and to establish an adequate control strategy. In addition, a further reduction in the computational effort was obtained by using the relay race method to extrapolate results. The predicted RTD curves were then parameterized to develop reduced order models and used to simulate the process in a matter of seconds. Overall, a control strategy evaluation tool based on high-fidelity DEM simulations was developed using material-sparing small-scale characterization tests.

Discrete element model of nanoparticle deposition during electrospraying

Electrospraying is a technique for the production and deposition of nanoparticles. However, deposited layer morphology is strongly dependent on the operating conditions and hard to predict. Here, we present a spatially 3D model based on the Discrete Element Method (DEM) with the analytical evaluation of interparticle forces and drag force and the numerical evaluation of electric force. The developed connection between mesh-free DEM and mesh-based Finite Volume Method (FVM) used for the evaluation of electric potential field enables to lower the computational time while maintaining accuracy of the predictions We focus on modelling the influence of interparticle forces on particle deposition and deposited layer morphology, which are phenomena usually neglected in the literature so far. Preferential landing of particles is indicated to be a consequence of both electric force and Van der Waals forces. Contact particle interactions allow particle stacking (creating thus fractal-like structure) or allow falling down of particles and their rearrangement (leading to compact layers).

Development of a high-fidelity digital twin using the discrete element method for a continuous direct compression process. Part 1. Calibration workflow

In this work, a high-fidelity digital twin was developed to support the design and testing of control strategies for drug product manufacturing via direct compression. The high-fidelity digital twin platform was based on typical pharmaceutical equipment, materials, and direct compression continuous processes. The paper describes in detail the material characterization, the Discrete Element Method (DEM) model and the DEM model parameter calibration approach and provides a comparison of the system’s response to the experimental results for stepwise changes in the API concentration at the mixer inlet. A calibration method for a cohesive DEM contact model parameter estimation was introduced. To assure a correct prediction for a wide range of processes, the calibration approach contained four characterization experiments using different stress states and different measurement principles, namely the bulk density test, compression with elastic recovery, the shear cell, and the rotating drum. To demonstrate the sensitivity of the DEM contact parameters to the process response, two powder characterization data sets with different powder flowability were applied. The results showed that the calibration method could differentiate between the different material batches of the same blend and that small-scale material characterization tests could be used to predict the residence time distribution in a continuous manufacturing process.

High-resolution regional sea-ice model based on the discrete element method with boundary conditions from a large-scale model for ice drift

Abstract Understanding sea-ice dynamics at the floe scale is crucial to comprehend polar climate systems. While continuum models are commonly used to simulate large-scale sea-ice dynamics, they have limitations in accurately representing sea-ice behaviour at small scales. DEMs, on the other hand, are well-suited for modelling the behaviour of individual ice floes but face limitations due to computational constraints. To address the limitations of both approaches while combining their strengths, we explored the feasibility of using a DEM within a continuum model, where the latter provides boundary conditions for a rectangular high-resolution DEM domain. This paper presents a feasibility study where a discrete model of a 100 × 100 km2 icefield was created using high-resolution optical satellite imagery. Sea-ice dynamics were simulated in the DEM considering environmental forces and integrating large-scale ice-drift velocities as boundary conditions. Model predictions were compared with satellite observations for ice drift and deformation parameters. This numerical approach showed potential for offering accurate, high-resolution predictions of sea ice, particularly in coastal areas and near islands, and may find applications in ice navigation and climate studies. However, further development of the DEM, along with upgrades to the coupled ocean models providing data for the ice component, may be necessary. Additionally, challenges remain to develop a two-way coupling between the DEM and a continuum model, which may be needed to improve the accuracy of large-scale simulations.