Discrete Element Method Simulation Results Research Articles

A Multiscale Method to Develop Three-Dimensional Anisotropic Constitutive Model for Soils

A multiscale method is presented to develop a constitutive model for anisotropic soils in a three-dimensional (3D) stress state. A fabric tensor and its evolution, which quantify the particle arrangement at the microscale, are adopted to describe the effects of the inherent and induced anisotropy on the mechanical behaviors at the macroscale. Using two steps of stress mapping, the deformation and failure of anisotropic soil under the 3D stress state are equivalent to those of isotropic soil under the triaxial compression stress state. A series of discrete element method (DEM) simulations are conducted to preliminarily verify this equivalence. Based on the above method, the obtained anisotropic yield surface is continuous and smooth. Then, a fabric evolution law is established according to the DEM simulation results. Compared with the rotational hardening law, the fabric evolution law can also make the yield surface rotate during the loading process, and it can grasp the microscopic mechanism of soil deformation. As an example, an anisotropic modified Cam-clay model is developed, and its performance validates the ability of the proposed method to account for the effect of soil anisotropy.

A coda wave interferometry to characterize and evaluate the powder debonding damage of solid propellant: Experimental investigation and discrete element simulation

The debonding of solid filler powder and binder matrix is the main form of damage for composite solid propellant. This study proposes a coda wave interference (CWI) analysis method to quantitatively characterize and evaluate the internal powder debonding damage of composite solid propellant by experiment and discrete element simulation. In order to verify the validity of numerical simulation, the discrete element method (DEM) samples to simulate the powder debonding damage of solid propellant are established, and the DEM simulation and micro-CT scanning experiment are carried out. The micro-experimental and DEM results prove the efficiency and accuracy of DEM samples in modeling the damage behaviors of solid propellant specimens. Furthermore, in order to quantitatively characterize and evaluate powder debonding damage of solid propellant, using CWI method to analyze the damage states of solid propellants in the experiment and DEM simulation of tension. Two coda evaluation parameters based on different damage states are proposed, and the relationship curves of coda evaluation parameters and tensile strain are obtained. Though the analysis of the curve results of experiment and DEM simulation, the validity of CWI is demonstrated. The coda evaluation parameters can quantitatively identify and judge the accumulation process of initial damage, the appearance of micro holes and the failure point of propellant.

A DEM Investigation on the Influence of Cyclic and Static Stress Ratios and State Variables on the Pore Water Pressure Generation in Granular Materials

A granular soil may undergo liquefaction failure due to excess pore water pressure (Δu) generation when subjected to cyclic loading such as an earthquake. Several past studies indicated Δu generation may be independent of cyclic stress ratio (CSR), whereas others contradicted this observation. A soil element in its natural state often remains in K0 consolidation state, i.e., subjected to nonzero static shear stress ratio (SSR). Using the discrete element method (DEM), this study performs a large number of cyclic triaxial tests and evaluates various factors influencing the magnitude and rate of Δu generation under symmetric and nonsymmetric cyclic loading conditions. The study also evaluates the capabilities of several existing Δu generation models to predict the development of Δu under different failure scenarios. It was observed that the generation of Δu can be influenced by CSR for specimens subjected to symmetrical cyclic loading and by both CSR and SSR for nonsymmetric cyclic loading conditions. A new prediction model for Δu generation was developed along with an objective framework to estimate its input parameters. The model showed good agreement with the DEM simulation results.

Study on Pulling Dynamic Characteristics of White Radish and the Optimal Design of a Harvesting Device

The loss rate is an important index to evaluate the harvesting performance of white radish. To reduce the loss rate, it is necessary to analyze the pulling dynamic characteristics of white radish and then optimize the structure and operating parameters of the harvesting device. In this paper, according to the growth characteristics of white radish in the field, the discrete element method (DEM) was used to simulate the pulling process. The pulling force was calculated using the Edinburgh elasto-plastic adhesion model (EEPA), and the effects of soil bed compactness, pulling speed and angle on the pulling force were analyzed. The tests on pulling mechanics were carried out in the laboratory to verify the accuracy of DEM simulation results. The results showed that in the soft soil bed with compactness less than 2.8 MPa, the pulling force of radish is generally smaller than the leaf breaking force, and it is feasible to pull the radish out directly. While in a soil bed with high compactness, it is necessary to install a loosening shovel to reduce the pulling force thus reducing the loss rate due to leaf breakage. The structure and operating parameters of the harvesting device were designed according to the pulling dynamic characteristics, and the white radish harvesting tests were carried out in different fields. Statistical results show that when the soil compaction was increased from 1.47 MPa to 2.21 MPa, the average loss rate increased from 0.68% to 1.75%, and the average damage rate increased from 2.41% to 2.70%. Similarly, when the forward speed was increased from 0.18 to 0.47 m/s, the average loss rate increased from 1.08% to 1.30%, and the average damage rate increased from 2.34% to 2.74%. Overall, the maximum loss rate and the maximum damage rate could be controlled below 2.0% and 3.0%, respectively. In the hard soil bed, the loss rate can be effectively reduced from 15% to 2.5% by installing a loosening shovel.

Understanding of penetrating resistance on an inclined plate to cohesive soil using two-dimensional discrete element method

In order to know the effect of varied grousers on the reaction of soil, the reaction of soil by a plate at different angles of inclination using the two-dimensional discrete element method (DEM) has been investigated. Either the simulation or the experiment, a flat iron plate with 5 × 77 × 100 (mm) was used, and the inclination angle between the plate and the soil surface ranged from 0 to 60 degrees with 15-degree intervals. According to the result, the cohesive soil model introduced in the 2D DEM could successfully replicate the experimental results considering the effects of different inclination angles of the plate and the values of the root mean square error between the simulation and the experiment were found as 6.62, 36.60, 58.63, 60.84, and 66.25 N for inclination angles from 0 to 60 degrees in the horizontal direction. Moreover, the RMSE values of 127.91, 216.06, 75.88, 110.40, and 25.49 N were obtained for the vertical direction. Overall, a minimal discrepancy was observed between the results of DEM simulation and those of experiments in the vertical component of reaction force when the inclination angle of the plate was increased.

Calibration of DEM simulations for dynamic particulate systems

Calibration and validation represent crucial but often-overlooked ingredients in the successful application of discrete element method (DEM) simulations. Without rigorous calibration/validation protocols, the results of DEM simulations can be imprecise or even unphysical, yet all too often the methods used by practitioners are at best cursory, and at worst entirely absent. As the particle-handling industries show an increasing interest in DEM, it is vital that this issue be resolved lest a potentially powerful tool be written off by industry as unreliable. In this work, we provide a concise overview of contemporary methods used in the calibration and validation of DEM simulations of powder flows, providing practical insights into their strengths and weaknesses, and ideas for manners in which they may be improved and/or rendered more easily adoptable in the future.

Simulation of bubble–particle attachment process and estimation of attachment probability using a coupled smoothed particle hydrodynamics–discrete element method model

The bubble–particle attachment is an important step in determining the success of recovery in froth flotation. In this study, the bubble–particle attachment process was investigated using a coupled smoothed particle hydrodynamics (SPH)–discrete element method (DEM) model. The effects of particle inertia and the drag of fluid flow on the particle motion were examined. The sliding time was determined for different particle sizes, densities, and bubble sizes, and the simulated sliding time was compared with the analytical solution and our own experimental results using a high-speed camera. As the particle size and density increased, the sliding time decreased. However, this value was independent of the bubble size. The induction time was calculated as a function of the particle size and contact angle from an empirical model, and it was used to determine the attachment and net probabilities in a dynamic simulation. Based on the SPH–DEM simulation results, novel probability models were developed for bubble–particle interactions. Both attachment and net probabilities could be decoupled into hydrodynamic and thermodynamic effects, given that the collision probability was also derived as a single function of the particle Stokes number. The developed probability models embodying the mutual influence of bubbles and particles can be extended to macroscopically describe flotation cells and evaluate cell performance including particle recovery.

Fabric response to stress probing in granular materials: Two-dimensional, anisotropic systems

The microstructure of granular materials has a significant influence on their macroscopic quasi-static strength and deformational behaviour. This microstructure is often quantified by a second-order fabric tensor that describes the primary orientational statistics of interparticle contacts. Here, it is investigated how the fabric tensor changes when samples are subjected to small (strain) loadings with different ‘directions’, i.e. probes. This is accomplished by the analysis of extensive sets of Discrete Element Method (DEM) simulations for various anisotropic, pre-peak two-dimensional samples, where both in-plane (i.e. coaxial with the current stress and fabric tensor) and out-of-plane, noncoaxial probes are considered. The results of DEM simulations show that the in-plane and out-of-plane fabric responses are effectively decoupled, i.e. they are only dependent on the in-plane and out-of-plane strain increment, respectively. The out-of-plane fabric increment is proportional to the out-of-plane strain increment whereas the in-plane fabric increment is linearly dependent on the in-plane strain increment. An accurate theoretical description (with a modest number of model parameters) has been developed that describes the fabric response to the imposed, in-plane as well out-of-plane, strain increments for the considered systems.

Investigation on the ultimate uplift capacity for asteroid exploration in drilling anchoring process: Numerical modelling and DEM simulation

Due to the microgravity environment on the asteroid surface, the asteroid probe can not stay on the asteroid surface for a long time for in situ exploration. Therefore, an anchoring device is required to provide enough ultimate uplift capacity to hold the asteroid probe on the asteroid’s surface. In this work, based on the circular arc failure surface hypothesis, a numerical model is proposed to predict the ultimate uplift capacity of the anchor rod of the anchoring devices during the anchoring process. The discrete element method (DEM) simulation is adopted to calculate the ultimate uplift capacity and analyze the geomaterial behavior. To accurately simulate material properties, the parameters of three typical geomaterials are calibrated by the calibration tests. The anchoring experiment verifies the DEM simulation results, and the error between the anchoring experiment results and DEM simulation results is less than 14%. The distribution of loaded particle forces in the geomaterials under various anchoring angles(30°–60°) and the anchoring depths(20 mm–40 mm) in the simulation are compared and analyzed. Compared with the DEM simulation results, the ultimate uplift capacity’s numerical model prediction results have an error of 5%. This work provides a new approach to predict the ultimate uplift capacity of the anchor rod of the anchoring devices during the asteroid exploration process.

A novel Markov chain method for predicting granular mixing process in rotary drums under different rotation speeds

The granular mixing in rotary drums has been intensively studied using discrete element method (DEM). However, DEM is computationally intensive. When the operating condition (such as rotation speed) of the drum is changed, a new round of time-consuming DEM simulation must be performed, whereas the data generated in previous rounds are not utilized. In order to solve this problem, we propose a Hermite interpolation-based Markov chain method (HI-MCM) to replace DEM simulation, so that granular mixing process under new drum speeds can be quickly predicted. HI-MCM utilizes the data generated by only several DEM simulations to establish Markov chain models, with which the granular mixing process at new rotation speeds can be then quickly predicted by Hermite interpolated Markov chain models. Tests demonstrate that the particle spatial distribution and mixing degree predicted by HI-MCM agrees well with DEM simulation results, while the computing time is less than 1% of that needed by DEM and current Markov chain methods. Moreover, the proposed HI-MCM shows good robustness to the change of Markov chain parameter (learning time step). The proposed method has potential usages in online prediction of granular mixing in rotary drums.

Influence of grain size on strength of polymineralic crystalline rock: New insights from DEM grain-based modeling

Grain size effect on rock strength is a topic of great interest in geotechnical engineering. A consensus obtained from earlier laboratory tests is that rock strength generally decreases with the increase of grain size for both silicate and carbonate rocks; however, some recent numerical results conflict with such laboratory test results. To address this intriguing issue, the effect of grain size on strength of polymineralic crystalline rock with low porosity is investigated numerically using the grain-based modeling (GBM) approach in discrete element method (DEM) by interpreting micro-cracking process in response to loading. In agreement with some previous DEM simulation results, the simulated rock strength is found to increase with increasing grain size for both homogeneous and heterogeneous models, even when the number of assembled disks in one mineral grain changes. The mechanism of strength increase with increasing grain size is mainly associated with the number of assembled smooth-joint contacts along grain interfaces and the generation of grain boundary cracks in response to loading. The grain interfaces significantly weaken the integrity of the rock model, which is similar to effects of inherent defects in real rock. As the grain size increases, fewer grain interfaces are built in the model and the rock strength becomes much higher. Hence, by solely changing the mineral grain size in a model, the mechanism of grain size effect as observed in laboratory tests cannot be replicated. To address this issue, a method of degradation of grain boundary strength parameters is used to mimic the possible mechanism of grain size effect. The simulated strength using the method becomes comparable with those obtained from laboratory tests when the heterogeneity in the rock is considered. Degradation of grain boundary parameters with increasing grain size provides a plausible explanation for the grain size effect on rock strength.

Calibration of discrete-element-method model parameters of bulk wheat for storage

The discrete element method (DEM) parameters of wheat were calibrated for the modelling of a grain storage system. In addition, the effects of material parameters on the accuracy of DEM modelling of the oedometric compaction and unloading of bulk wheat were analysed. The bi-stiffness Hertz-like contact model was applied to incorporate the hysteretic behaviour of individual grains. The parameters of the contact model were calibrated based on experimental data of the loading–unloading cycle of a single wheat grain. The results of DEM simulations of the bulk behaviour of grain were validated using experimental data from oedometric tests. The observed trends indicate good correspondence between the experimental data and DEM simulations using the calibrated parameters. Simulations performed assuming spherical particles provide the best approximation of the loading–unloading cycle. The application of a special procedure for performing DEM simulations allows for the accurate reproduction of experimental values of the initial, compacted, and unloaded porosities of bulk wheat grains in the considered moisture-content range considered. • Bi-stiffness contact model is positively verified for the storage of wheat. • Calibration of the DEM parameters of wheat for storage is performed. • Bulk properties of wheat grain are modelled and verified experimentally. • The effect of moisture content on bulk properties is examined.

Investigation of the force evolution in aggregate blend compaction process and the effect of elongated and flat particles using DEM

Aggregate particles play an essential role in the load transfer of asphalt pavement. This paper documents an investigation into the force evolution in the compaction process of aggregate blend and the influence of the elongated and flat particles using discrete element method (DEM). Three typical aggregate particles, including a regular particle (RP), an elongated particle (EP), and a flat particle (FP), were selected and scanned by a 3-D laser scanner to get the 3-D images, based on which the virtual particles were generated in DEM software. Six gradations, three stone matrix asphalt (SMA) gradations and three dense asphalt concrete (AC) gradations, were selected and various contents of RP, EP and FP were considered in the investigation. The force evolution and the effect of elongated and flat particles were quantified using the DEM simulation results. It is found that particles of different sizes contribute differently to load bearing. The size of 4.75 mm might be a transition point for distinguishing the load transfer function of particles in the investigated gradations. Though the EP and FP have no effect on the evolution trends of contact force and contact number of each size particles in the compaction process, they have remarkable effect on the increased value of contact force, which increases with the increasing proportions of EP and FP, and some effect on that of the contact number with no fixed pattern. The FP exhibits more negative influence on the force evolution of aggregate blend than the EP.

Micro-mechanical analysis of caisson foundation in sand using DEM

Caisson foundation has been widely used for offshore structures. The micro-mechanical analysis of the behaviors of a caisson foundation during its installation, operation and failure is important but not currently available. The goal of this study is to improve the understanding of the micro-mechanisms in the installation, operation and progressive failure processes of caisson foundation and provide guidance on the design. For this, the discrete element method (DEM) is adopted to investigate the interaction of caisson foundation and sand. The DEM model is first validated by comparing the results of DEM simulations and experiments, in which similar trends are found in various load-displacement curves. With the validated model, the micro-mechanical response of soils induced by the installation process is studied firstly. Then the behavior of soils during the failure of the caisson foundation, including particle displacement, rotation, and stress distribution, are investigated for cases of different loading combinations. In addition, the fabric, including contact orientation, normal contact force, and shear contact force, and its evolution are studied by dividing the soils into four different zones based on their positions and failure mechanisms. At last, the effect of dimensionally homogenous moment to horizontal load ratio (M/(DH)) is discussed.

Deformation of 3D printed agglomerates: Multiscale experimental tests and DEM simulation

Agglomerates are widely used in industry, and their mechanical properties are of great interest. In this work, we propose a new concept of using a coordinated multiscale approach to match the physical and digital agglomerate structures and properties. By using a multi-material 3D printing technology, the inter-particle bond properties and agglomerate structures could be precisely controlled and replicated. Quasi-static compression tests have been carried out for the 3D printed samples at different scales. A Timoshenko Beam Bond Model (TBBM) with bond properties matching those of the 3D printed agglomerates is used to describe bond deformations. Discrete Element Method (DEM) is then employed to simulate the agglomerate crushing process. The results show that for both agglomerate structures, the DEM simulation and experimental results show good agreement at the initial elastic deformation stage. This work opens up the chance for significant advances in agglomerate deformation and breakage modelling in future.

Numerical modeling of granular flow in star valve type cryogenic precooler

AbstractCryogenic precooler/precooler is the essential component of a cryogenic grinding system that removes the desired amount of heat from a sample with the aid of a cryogen such that brittle type of failure occurs during grinding. Nevertheless, the understanding of particle dynamics, heat transfer phenomena, and optimal cryo‐grinding condition are obligatory to lower the operational cost and scaling up the findings. Therefore, the present study aims to model three‐dimensional dynamic flow behavior of black pepper seeds in star valve type precooler using discrete element method (DEM). The Hertz‐Mindlin contact model was utilized to simulate the granular flow profile of the seeds. The DEM simulation results of flow pattern and volumetric fill level of bulk granules in different sections (feed, mid, and discharge) of precooler were in line with the results of the experimental approach. Overall, DEM modeling provided a better insight into particle‐scale flow dynamics in precooler.Practical applicationsCryogenic grinding technique is widely preferred to obtain high‐quality spices powder owing to maximal retention of thermo‐sensitive flavoring components compared to conventional counterpart. The inefficient utilization of cryogen and granular flow issues results in higher operational cost of cryo‐ground spices powder. Thus, the finding of granular flow characteristics of black pepper in cryogenic precooler may aid in improving the design of precooler as well as efficient utilization of the costly cryogen. Overall, these would help in producing high‐quality of spices powder at an affordable cost.

Deviation of continuum formulation for solid-solid momentum transfer rate in terms of spatial averaging in mixtures with large particle size ratios

In a fluidized bed system, mean trajectories of fuel particles within the bed of fluidized inert particles are governed by the associated drag forces and characterize hydrodynamic, chemical and thermal processes taken place in the system. A large particle size ratio between the bed material and the fuel particles affects the hydrodynamics of gas-solid multiphase flows via influencing the drag forces between solid phases. The present work focuses on the analysis of forces between the two solid phases with large size ratios using the Lagrangian simulations of discrete element method (DEM). The results are spatially averaged over variable control volume size for comparison to the continuum interphase momentum transfer model. Using our DEM simulation results, a correction factor of drag force is presented versus the size of averaging control volume usable in continuum models. In addition, the role of inhomogeneity of particles distribution within the averaging box is discussed.

Comparison of computational fluid dynamics–discrete element method and discrete element method simulations for a screw conveyor

AbstractFlow behavior of particles is simulated by means of discrete element method (DEM) in a screw conveyor. The gas flow is considered by the Euler model. The subgrid scale model turbulence model is applied to solve gas turbulence. A detailed description of the model equations applied has been presented. The comparison between computational fluid dynamics (CFD)‐DEM (i.e., considering gas flow) and DEM (i.e., not considering gas flow) simulation results is performed. Predicted mass flow rate with CFD‐DEM model is in better agreement with experiments by Roberts and Wills comparing with DEM results. The effects of incline angle and filling rate on the flow behavior of particles are predicted. The simulation results show that the gas flow has a major impact on particle flow behavior at a high rotation speed, whereas the velocity of particles increases with an increase of rotation speed. As the filling rate rises, both the translational granular temperature and the rotational granular particle temperature decline, which means that the particles fluctuation turns weak. While with an increase of incline angle, from the horizontal to vertical, the translational granular temperature is increased, but the rotational granular temperature reduces and then goes up. In brief, translational motion is a main mode of motion in a screw conveyor.

Diffuse instability of granular material under various drainage conditions: discrete element simulation and constitutive modeling

Diffuse instability is a typical failure mode of sand that occurs before the perfect plastic flow condition is attained. Whereas extensive laboratory experiments have demonstrated the macro-scale responses associated with such a failure mode, its underlying microscopic mechanism remains unclear. Therefore, no effective predictions can be made incorporating sophisticated constitutive models of sand, particularly when various drainage conditions are considered. In the present study, diffuse instability is first investigated using the discrete element method (DEM). Herein, partially drained and fully drained conditions are imposed to investigate the instability failure in proportional strain loading and constant shear drained tests, respectively. Then, both macro- and micro-scale second-order work criteria are applied to identify the occurrence of instability. Furthermore, the main features associated with the onset of diffuse instability are presented. The diffuse instability behavior of sand is observed to be closely related to its fabric evolution. Eventually, independent criteria for diffuse instability under various drainage conditions are determined considering the DEM results. In addition, a newly developed anisotropic constitutive model with a fabric evolution law is applied to simulate the mechanical behavior of sand and the instability that ensues. The model exhibits satisfactory agreement with the DEM simulation results. Overall, this study is aimed at elucidating why diffuse instability occurs prior to the plastic limit and how to predict it under various drainage conditions.

Combination of Discrete Element Method and Artificial Neural Network for Predicting Porosity of Gravel-Bed River

In gravel-bed rivers, monitoring porosity is vital for fluvial geomorphology assessment as well as in r ecosystem management. Conventional porosity prediction methods are restricting in terms of the number of considered factors and are also time-consuming. We present a framework, the combination of the Discrete Element Method (DEM) and Artificial Neural Network (ANN), to study the relationship between porosity and the grain size distribution. DEM was applied to simulate the 3D structure of the packing gravel-bed and fine sediment infiltration processes under various forces. The results of the DEM simulations were verified with the experimental data of porosity and fine sediment distribution. Further, an algorithm was developed for calculating high-resolution results of porosity and grain size distribution in vertical and horizontal directions from the DEM results, which were applied to develop a Feed Forward Neural Network (FNN) to predict bed porosity based on grain size distribution. The reliable results of DEM simulation and FNN prediction confirm that our framework is successful in predicting porosity change of gravel-bed.