Development and analysis of micro-performance dynamics of rotary blade using discrete element method

Investigation of shale fracture behavior with different bedding properties based on discrete element method

Discrete element method reveals flow mechanism and lateral pressure characteristics of grain storage in sector-shaped silos

Discrete element method–based mechanistic investigation of rice straw disturbance and throwing by a gathering device

Regulatory role of mobile fine particles in anomalous solute transport in porous media.

This study investigates grinding media behavior and grinding efficiency in a laboratory-scale ball mill under different rotation speeds to identify energy-efficient operating conditions in ball mill grinding operations. Grinding efficiency is evaluated in terms of the effectiveness of energy transfer into particle breakage, as quantified by PBM-derived breakage-rate characteristics, rather than by conventional metrics based solely on energy consumption. Batch grinding tests were conducted at several fractions of the critical speed, and a Population Balance Model (PBM) was calibrated for each operating condition to quantify the corresponding breakage-rate characteristics. In parallel, Discrete Element Method (DEM) simulations were performed to analyze the motion of grinding media as a function of rotation speed. Media motion descriptors derived from DEM were integrated with the PBM-based breakage parameters to interpret efficiency trends. The results show that grinding efficiency does not increase monotonically with rotation speed; instead, an optimal operating region exists within the investigated range due to the balance between impact-dominated and surface-contact-dominated motion regimes. By linking DEM-quantified media behavior indicators with PBM-derived breakage-rate coefficients, the proposed integrated framework enables physics-based estimation of the optimal rotation speed region. This methodology provides a transferable basis for analyzing and improving grinding efficiency in ball mill grinding operations.

Particle size segregation is a common occurrence in sheared granular flows under gravity. Segregation of size-bidisperse grain mixtures at size ratios of three or less has been extensively studied, but comparatively little is known about segregation of grains with more widely varying sizes, despite their relevance to natural and industrial flows. At larger size ratios the segregation behaviour of bidisperse mixtures may change drastically, including reversal of the direction of segregation, which no existing continuum model accounts for. This paper investigates the segregation behaviour of bidisperse granular mixtures up to a size ratio of seven and formulates a new continuum model for size segregation that captures the observed suppression and reversal of segregation. Discrete element method (DEM) simulations of flows on an inclined plane show a reversal of behaviour as the volume fraction of small particles increases, from states where the large particles rise to the free surface to states where they sink. At intermediate small-particle volume fractions, segregation is significantly reduced or even entirely absent, leading to well-mixed flows. In addition, a striking layering effect is observed at large size ratios, where large particles organise into distinct layers one particle thick, separated by thin bands of small particles. This layering is demonstrated both in simulations and, for the first time, in laboratory experiments. The continuum segregation model introduces a new bidirectional segregation flux that accounts for the reversal in segregation. The model is in good quantitative agreement with DEM simulations across a range of small-particle volume fractions.

In this study, the settling behaviour of two cubes and two spheres released side-by-side in a quiescent fluid is investigated through both experimental and numerical simulation approaches. Particle Tracking Velocimetry (PTV) and Particle Image Velocimetry (PIV) are employed to capture particle trajectories, settling velocities, and the surrounding flow fields. Concurrently, coupled Smoothed Particle Hydrodynamics–Distributed Contact Discrete Element Method (SPH-DCDEM) simulation is performed to reveal detailed three-dimensional flow structures and pressure distributions. The results indicate that the initial particle spacing significantly affects the settling dynamics by altering the flow patterns between the two particles and influencing their rotational motion. In extreme cases, it even modifies the overall particle trajectories from the typical three-stage process to a four-stage process. Moreover, the cubic shape induces flatter streamlines, stronger recirculation zones and wake structures, and a distinct region of horizontal reverse flow. Regions of high vorticity and high pressure are alternately distributed along the edges and faces of the cubes. A strong coupling is found between the flow field structure and the particle’s motion, and the evolution of particle trajectories is elucidated by analysing the development of pressure distribution over the entire settling process. By decoupling the multiple effects driving free settling dynamics, the repulsion mechanisms are clarified and the force magnitudes quantified. These findings deepen our understanding of the settling behaviour of non-spherical particles and offer valuable insights for predicting particle dynamics in environmental and industrial applications.

ABSTRACT This article presents a comparison of various implementations of the Lattice Discrete Particle Model (LDPM) for the numerical simulation of concrete and other heterogeneous quasibrittle materials. The comparison involves the use of transient implicit and explicit solvers and steady‐state (static) solvers as well as implementations for central processing unit (CPU) and graphics processing unit (GPU). The various implementations are compared on the basis of a set of benchmarks tests describing behaviors of increasing computational complexity. They include elastic vibrations, confined strain‐hardening compressive response, tensile fracture, and unconfined strain‐softening compressive response. Metrics of interest extracted from the simulations include macroscopic stress versus strain responses, computational times, number of iterations, and energy balance error. Pairwise comparison of final crack patterns is provided through the correlation coefficient and normalized root mean square error of the crack opening vectors. Moreover, for the most numerically challenging case of unconfined compression with sliding boundary conditions, the stability of the strain‐softening response is tested by perturbing the solutions as well as changing the convergence criteria and time step size. Attached to this paper is the complete input data of the benchmark tests; this will allow researchers to run the examples and compare them with their own implementations. In addition, most of the reported implementations are publicly available in open source packages.

It is of great significance to clarify the evolution law and control mechanism of fracture conductivity in different production stages for the efficient development of coalbed methane. However, research on fracture conductivity in coal–rock remains limited, and the existing models are inadequate for predicting fracture conductivity with a consideration of staged proppant crushing. To address this gap, long-term conductivity tests were conducted on deep coal–rock under varying closure pressures and proppant gradation ratios. Within a coupled computational fluid dynamics and discrete element method (CFD-DEM) framework, a particle substitution scheme was integrated with the energy-based breakage model (Tavares breakage model) to develop a fracture conductivity predictor that incorporates proppant crushing and captures the time-dependent kinetics of proppant breakage during fracture conductivity evaluation. The model’s predictions align well with the experimental data, with an average error of less than 5%. The results indicate that fracture conductivity evolution can be delineated into three stages according to particle-breakage characteristics, (i) proppant pack compaction, (ii) the primary crushing of coarse proppant grains, and (iii) the secondary crushing of proppant fines, and the contributions of these three stages to the total conductivity loss are approximately 60%, 30%, and 10%, respectively. At a low closure pressure, fracture conductivity varies markedly among proppant packs with different particle sizes; once the closure pressure exceeds 40 MPa, the proppant pack enters the fines-breakage stage, and the conductivity differences among various particle size blends become marginal. Furthermore, a semi-empirical prediction model incorporating a composite crushing factor (CCF) was developed based on the Kozeny–Carman relationship, enabling a rapid evaluation of fracture conductivity in deep coal–rock fractures. Overall, these results provide a practical basis for fracture conductivity prediction and hydraulic fracturing parameter optimization in coal–rock reservoirs.

To address the complex dynamic mechanisms and lack of static operation data in trench-digging for transverse planting of Salix psammophila sand barriers, a transverse trench-digging device was designed. Based on the discrete element method, the Hertz–Mindlin with JKR Cohesion model was used to simulate sandy soil. The Box–Behnken experiment was adopted to optimize the single auger structure with helix angle and soil-cutting angle as factors and trench depth and working torque as indices, yielding the optimal parameters of 30° soil-cutting angle and 20.37° helix angle (5.52 cm trench depth, 2.6 N·m maximum torque). The optimized auger was integrated into the device, and a further Box–Behnken experiment was conducted under a 20 cm fixed descending depth of the lifting platform. With auger rotation speed, shaft spacing and lifting speed as factors, and trench depth, soil compaction and Salix psammophila insertion depth as indices, the optimal operating parameters were determined as 257.25 r/min, 7 cm and 9 cm/s, corresponding to 6.7 cm trench depth, 33.37 kPa soil compaction and 14.87 cm insertion depth. This study clarifies the effects of auger and operation parameters on trench-digging quality, provides a basis for the design and parameter matching of dynamic continuous operation equipment, and offers a reference for the R&D of mechanized transverse planting equipment for Salix psammophila sand barriers, which is of practical value for reducing sand control costs and improving efficiency.

UAV-based rice direct seeding offers high operational efficiency and reduced labor demand, yet seed distribution uniformity remains a major limitation for centrifugal spreading devices. This study aims to design and optimize a novel centrifugal drone rice direct seeding device to improve seed lateral distribution uniformity. In this study, a centrifugal drone rice direct seeding device was developed with a concave perforated disc and double-arc seed-pushing blades to regulate seed motion and improve lateral distribution uniformity. Discrete element method (DEM) simulations were conducted to examine the effects of disc tilt angle, blade type, and blade number. Single-factor and response-surface simulation results identified an optimal parameter combination of a 29.0° disc tilt angle, double-arc blades with a 110° arc angle, and six blades. Based on these results, the disc structure was further refined, and the simulated lateral coefficient of variation (CV) of seed distribution reached 18.22%. Bench tests yielded a minimum CV of 16.34%, an average CV of 19.36%, and a total discharge coefficient of variation of 0.276%, which agrees with the simulation outcomes and supports the validity of the DEM model. Overall, the proposed device demonstrates improved seeding uniformity and meets agronomic requirements for rice cultivation, offering farmers a high-efficiency planting solution and providing UAV manufacturers with a validated double-arc disc design for equipment optimization.

The traditional Discrete Element Method (DEM) can track the motion details of individual particles, but its computational cost becomes excessively high when simulating large-scale systems involving millions or even billions of particles. In this study, a coarse-grained DEM approach was employed to analyze the flow behavior of mixed particles in a coal powder silo. This method maintains reasonable simulation accuracy while effectively reducing the total number of computational particles and significantly improving computational efficiency. After conducting investigations on the mesh-to-particle size ratio and model validation, this paper focuses on examining the effects of coal particle size distribution and mixing ratio on the characteristics of particle motion. The results indicate that during the discharge process of mixed particles, the downward velocity of particles in the central axis region near the outlet is significantly higher than that in the wall region, exhibiting typical funnel flow characteristics. The particle size distribution has a notable impact on the particle descent velocity. The uniform distribution case shows the highest descent velocity, the linear distribution case the lowest, while the normal distribution case falls between the two. Notably, in the normal distribution case, the descent velocity in the central axis region is similar to that of the uniform distribution, while the descent velocity in the wall region approaches that of the linear distribution. This presents a combined characteristic of the two extreme distributions rather than a simple transitional state. In contrast, the particle mixing ratio has a relatively minor influence on the overall motion characteristics. The mass flow rate of particles and the cross-sectional velocity distribution remain largely consistent, with only slight differences observed in the velocity within the central axis region.

Accurate prediction of excavation forces is critical for the design reliability and operational safety of Mars surface sampling systems. This study establishes an analytical modeling framework to describe the excavation mechanics of Martian soil, focusing on the formation mechanism and evolution of resistance. Soil deformation and failure processes are qualitatively identified using particle image velocimetry (PIV) and discrete element method (DEM) simulations. Based on limit equilibrium theory, the passive earth pressure is derived, and the scoop is divided into seven force-bearing regions for three-dimensional force decomposition. The analytical model is validated against multibody dynamics–discrete element method (MBD–DEM) co-simulation. The results indicate that excavation resistance exhibits a distinct single-peak evolution, maximizing near the maximum excavation depth. Notably, the inner bottom surface and cutting edge dominate resistance during penetration, contributing approximately 56% and 30% of the total force, respectively. The resistance mechanism transitions after soil emergence due to the gravitational effect of retained soil. Consequently, this framework provides a physically interpretable and quantitatively validated approach for force prediction, offering theoretical support for sampling scoop design and optimization in future Mars missions.

Abstract Anisotropic shrinkage during sintering is limiting the widespread adoption of Binder Jet Additive Manufacturing (BJAM) by undermining its ability to produce complex, near-net-shape parts. Prior studies often attribute sintering anisotropy in BJAM-printed samples to factors such as gravity or heterogeneities in packing density. While emerging evidence indicates that powder segregation during printing induces particle-size heterogeneities, its influence on the anisotropic sintering of BJAM-printed samples has not been explored. This study investigates the relative effect of density and particle size heterogeneities on anisotropic sintering by developing a digital twin model to simulate the BJAM process. The model captures the dynamics of particles during the powder spreading process, including particle segregation, using the Discrete Element Method (DEM), enabling spatially resolved representations of packing density and particle-size heterogeneities. It also simulates the sintering response of the samples using the continuum theory of sintering (CTS) implemented in finite element (FE) code. Capability of the developed model is verified and validated using experimentally measured results for BJAM-printed samples from literature. It is revealed that particle-size heterogeneities, caused by powder segregation during printing, govern anisotropic shrinkage during sintering of binder-jet-printed samples. Furthermore, it is also shown that mismatches in lateral shrinkage rates, arising from particle size and density heterogeneities, can lead to surface roughness. The work highlights the need for optimizing feedstock particle size distributions and powder spreading parameters to control anisotropic shrinkage in BJAM process. Graphical abstract

Effect of ground loss on seismic performance of shield tunnel using discrete element method

A 2D Fully Coupled, Thermo-hydro-mechanical Modeling for Fault Activation Using the Combined Finite–Discrete Element Method (FDEM)

This study presents a novel pneumatic seed-metering device for precision soybean breeding, engineered to deliver two seeds per hill with high operational reliability. Its design features a compartmentalized structure and an integrated seed-clearing mechanism, explicitly addressing the key limitations of conventional seeders, such as low automation levels and intervarietal contamination during seed switching. The seed-metering and clearing processes were analyzed using coupled discrete element method–computational fluid dynamics (DEM–CFD) simulations. The exploratory DEM–CFD analysis identified distinct operational thresholds for seeding failures: miss-seeding occurred at disc rotational speeds exceeding 2.55 rad s−1, while multiple-seeding issues were frequent at applied vacuum pressures above 5.6 kPa. Following this, a Central Composite Design (CCD) experiment was conducted in a controlled laboratory setting to examine the effects of operational speed and vacuum pressure on seeding quality indices. A multi-objective numerical optimization identified an optimal operational compromise with a seed-metering disc speed of 2.65 rad s−1 (approximately 1.82 km h−1) and an applied negative pressure of 5.80 kPa. This operating point effectively balances the competing failure modes of multiple seeding and miss-seeding, resulting in rates of 2.95% and 0.85% respectively. Field validation in saline–alkali soil conditions confirmed the device’s high precision, with actual multiple and miss-seeding rates maintained below 2% and 0.5%, respectively. Overall, this device significantly enhances seeding efficiency and operational reliability, providing a practical and effective solution for high-throughput soybean breeding programmes.

Hydrodynamic erosion is widespread in colluvial and reservoir-bank deposits, where gap-graded soil–rock mixtures (SRMs) are highly susceptible to erosion under hydraulic conditions. However, the mechanisms governing hydrodynamic erosion in gap-graded SRMs remain unclear. In this study, a coupled discrete element method and computational fluid dynamics framework is developed to investigate the hydrodynamic erosion of gap-graded SRMs, in which the discrete element method tracks particle motion and contact forces, while the computational fluid dynamics module computes pore-scale fluid flow based on Darcy's law. Two-way coupling is achieved by exchanging porosity and fluid drag forces at each time step, allowing the fluid field and particle dynamics to be updated. The numerical approach is validated through two laboratory tests for simulating hydrodynamic erosion. A series of numerical simulations are conducted to investigate the influence of rock content (RC), rock particle shape, and hydraulic gradient on hydrodynamic erosion behavior. The results indicate that higher RC generally leads to greater cumulative fine particle loss, accompanied by highly heterogeneous flow fields with preferential erosion near boundaries. Irregular rock particles further restrict pore connectivity, suppressing continuous seepage channels while enhancing localized clogging.

Investigation on micromechanical behavior of rutting damage of water-immersed asphalt mixtures based on the discrete element method