Search Results (239)

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. Full article

To achieve high-speed quantitative hole sowing of rice using an unmanned aerial vehicle (UAV), this study proposes an agricultural UAV pneumatic hole sowing system suitable for high-speed quantitative hole sowing. This system is based on pelletizing rice seeds. A pneumatic seed distribution system based on the Venturi effect was designed, with a seed feeding device that employs a computational fluid dynamics–discrete element method (CFD-DEM) coupled simulation method to construct a gas–solid two-phase flow simulation model that simulates actual field sowing conditions and analyzes seed transport characteristics. Using the seed feeding device blending chamber height, expansion section cone angle, and inlet airflow velocity as experimental factors, and evaluating seed distribution statistics based on the hole formation ratio(HFR) and hole spacing coefficient of variation (HSCV), the study achieved a comprehensive statistical analysis of seed distribution patterns. The Box–Behnken orthogonal experiment optimized the structural parameters of the seed feeding device, determining the optimal airflow velocity during seeding. The optimized parameter combination yielded a blending chamber height of 15.59 mm, an expansion section cone angle of 22.20°, and an inlet airflow velocity of 19.67 m/s, corresponding to an HFR of 84.66% and an HSCV of 6.95%. Field trials validated an HFR of 86.25% and an HSCV of 6.83%. This study provides theoretical and technical support for the design of high-speed hole -sowing equipment for rice using a UAV. Full article

Air-induced separation of flexible rod-like particle mixtures in a specific separator is numerically investigated using a coupled Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD) approach. In the separator, the mixture of flexible rod-like particles of different lengths and material densities deposits under the effect of gravity, and a horizontal airflow stream intersects the particle flow, blowing lighter particles in the mixture to translate horizontally and allowing the heavier ones to fall downwards. The model particles represent flexible biomass materials, specifically tobacco and stem particles. The initial packing density of the particle mixture is 8% by volume. The physical mechanism that causes particle segregation is analyzed. Subsequently, parametric studies are performed to examine the effects of some critical parameters on the extent of segregation, including inflow air velocities, initial particle packing density, volume fraction of heavier particles, particle size distribution, and flow field geometry. Finally, a suggestion is proposed to promote particle segregation in such a type of separator. Full article

Spiral separators commonly face the issue of particle misplacement during fine particle separation, which severely limits separation accuracy. This study employs a coupled CFD-DEM numerical simulation method to systematically investigate the influence mechanism of transverse inclination angle (10°, 15°, 20°) on particle moving behavior. The results show that the separation process exhibits distinct stage characteristics, which can be divided into an initial stage (first 1/3 turn), a transition stage (1/3 to 2 turns), and a quasi-steady stage (after 2 turns). A steeper angle (20°) optimizes the flow field, reducing the inner low-velocity zone and widening the high-velocity core, which promotes inward migration of particles. This enhances the enrichment of high-density particles while effectively suppressing their mixing into the clean coal product at the outer edge. For difficult-to-separate fine particles below 0.1 mm, although complete separation is challenging, increasing the transverse inclination angle still shows a clear reduction in the misplacement of high-density particles, providing a controllable approach for improving the quality of the outer edge product. This study offers theoretical insights and design guidance for optimizing spiral separator structures and enhancing fine coal separation efficiency. Full article

The performance of the cleaning system in crop harvesters directly impacts overall operational efficiency and harvest quality. Against the background of traditional design relying on physical experiments—which is costly and provides limited mechanistic insight—Discrete Element Method (DEM), Computational Fluid Dynamics (CFD), and their coupled simulation (CFD-DEM) have become key means for in-depth study of the cleaning process, capable of revealing the complex interactions between particles and between particles and airflow. With the increasingly widespread and deep application of computer simulation technology in agricultural machinery research and development, it is particularly necessary to systematically review its research progress in cleaning systems. Therefore, this study provides a comprehensive and systematic analysis and summary of the key technologies in cleaning system simulation, aiming to address the current gap in systematic reviews of simulation technology in this field. Compared with previous studies that mostly focus on a single method or a specific crop type, this paper systematically reviews the application of three simulation technologies in cleaning systems of various crop harvesters. First, based on the working principle and core operational challenges of cleaning systems, the necessity of applying simulation technology is clarified. Second, the basic principles, modeling processes, and suitable application scenarios and key points for the cleaning simulation of each method are analyzed. Third, typical cases are reviewed to summarize their key achievements in structural innovation, parameter optimization of cleaning devices, and revealing the mechanisms of material separation. Finally, current bottlenecks in simulation applications are pointed out, and future development directions are outlined, including high-precision multi-field coupling, integration with intelligent algorithms, and the construction of digital twin systems. This study aims to provide systematic theoretical reference and methodological support for the innovative design and performance improvement of cleaning systems. Full article

Under dynamic loading (e.g., earthquakes, extreme rainfall), multi-stage slope slumps occur as downstream slopes lose anti-sliding stability, triggering intensive lateral sediment supply that governs mountainous channel evolution. This study uses a coupled CFD-DEM model to simulate how water–sediment conditions regulate sediment transport and riverbed deformation. Results show that during the first sediment supply event, particle motion is initially slower under wet than dry conditions but accelerates due to buoyancy, with the peak average particle velocity along the gully axis decreasing by 11.5% and exhibiting negligible flow rate dependence. In the channel, higher flow rates raise particle velocity and downstream sediment flux, while a prolonged supply interval elevates peak velocity and delays its occurrence. For subsequent events, peak gully axis and vertical velocities increase with sediment supply mass, with weak dependence on flow rate or interval. Post-peak particle motion accelerates with these three factors, enhancing sediment entrainment effects. Increasing flow rate from 1.7 to 2.2 L/s, supply mass from 0.75 to 1.50 kg, and interval from 4 to 6 s significantly strengthens substrate dynamic response, with the peak average velocity rising by 78.3%, 33.3%, 67.0% and maximum displacement by 80.7%, 51.2%, 67.6%, respectively. Channel particle velocity is more sensitive to flow rate but suppressed by greater sediment mass and shorter intervals. The deposited riverbed has three zones: first-supply-dominated, mixed, and subsequent-supply-dominated. Higher flow rates restrict depositional area expansion but increase thickness, whereas greater subsequent sediment expands its dominant zone while reducing thickness, with minimal influence from supply intervals. This study offers theoretical insights for preventing water–sediment disasters in mountainous areas. Full article

Particle migration is a pore-scale process that fundamentally controls pore-structure evolution and seepage behavior in granular porous media. This study investigates fine particles migration in coarse-grained sediments and its effects on pore structure and permeability by combining low-field nuclear magnetic resonance (LF-NMR) experiments with coupled CFD–DEM simulations. The evolution of fine particles migration rate, porosity variation, and permeability was analyzed under different fluid injection velocities and fines concentrations. Higher injection velocities accelerate fines initiation and early-stage migration by increasing hydrodynamic drag forces, whereas their influence diminishes at later stages due to pore-structure confinement and localized particle retention. At a constant injection velocity, increasing fines concentration suppresses early fines mobilization owing to enhanced interparticle interactions and pore throat blockage. As seepage continues, progressive fines release and export enlarge pore space and enhance permeability. Spatial analyses reveal that fines migration is governed by localized retention and rearrangement within pore throats. Within the investigated parameter ranges and timescales, system evolution is dominated by internal erosion and pore unclogging rather than sustained macroscopic clogging. These results provide mechanistic experimental–numerical insight into fines migration and seepage stability in granular porous media, with direct relevance to hydrate-bearing sediments and other fine-sensitive geological systems. Full article

In this study, the separation performance of cyclone separators with different geometric configurations was investigated using a hybrid approach that combines Computational Fluid Dynamics, the Discrete Element Method, and Artificial Neural Networks. In the first stage, the flow field was solved using the Reynolds-Averaged Navier–Stokes equations together with the Reynolds Stress Model turbulence closure, and particle motion was evaluated in detail through DEM. To examine the effect of geometric parameters, the inlet aspect ratio, vortex finder diameter, and cylinder height were systematically assessed. The results revealed the formation of a pronounced Rankine-type vortex structure inside the cyclone and showed that secondary flow regions intensified as the vortex finder diameter and cylinder height increased, thereby reducing the separation efficiency. In the inlet section, an optimal aspect ratio was identified. In the second stage, an ANN model was developed to expand the limited dataset obtained from the CFD–DEM analyses. By optimizing the activation function and the number of neurons, the best performance was achieved with a ReLU-based neural network containing a single hidden neuron, reaching a test-set accuracy of approximately $R^2\approx 0.991$ and an overall fit of $R^2\approx 0.895$. The ANN model also captured interaction trends between flow velocity and geometry that could not be observed with the limited CFD dataset. This hybrid approach provides an effective and low-cost method for performance prediction and optimization in cyclone separator design. Full article

During the discharge process of a salt cavern compressed air energy storage (CAES) system, high-speed air flow may entrain salt slag from the cavern floor, posing a threat to pipeline safety. Currently, there is a lack of in-depth research into the transient mechanisms of the entrainment process, particularly the influence of particle shape. This study employs a CFD-DEM coupling approach to conduct, for the first time, a high-fidelity simulation of slag entrainment dynamics during the initial discharge phase of a salt cavern CAES system, with a focus on the motion patterns of three particle shapes: spherical, conical, and square. Results show that: (1) during the initial discharge stage, the flow field rapidly forms vortex structures that migrate toward the wellhead, which is the core mechanism driving particle mobilization; (2) particle shape significantly affects entrainment efficiency through frictional characteristics—spherical particles are most easily entrained (maximum entrainment rate of 0.42 kg/h), while non-spherical particles tend to accumulate below the wellhead; and (3) the entrainment process exhibits strong transient characteristics: the entrainment rate peaks rapidly (approximately 0.82 kg/h) within a short time and then declines sharply, and it is sensitive to particle size, with the most entrainable particle size being around 5 mm. This study reveals the coupling mechanism between transient vortices and multi-shape particle entrainment during discharge, providing a theoretical basis for the design of filtration systems, operational risk prevention, and slag removal strategies in salt cavern CAES power plants. Full article

As global energy demand rises, developing unconventional oil and gas resources has become a strategic priority, with horizontal well technology playing a key role. However, wellbore instability during drilling often leads to irregular geometries, such as enlargement or elliptical deformation, causing issues like increased friction and stuck-pipe incidents. Most studies rely on idealized, regular wellbore models, leaving a gap in understanding cuttings transport in irregular wellbore conditions. To address this limitation, this study employs a coupled CFD-DEM approach to investigate cuttings transport in enlarged wellbores by modeling the two-way interactions between drilling fluid and cuttings. The study analyzes the impact of various factors, including drilling-fluid flow rate, drill pipe rotational speed, rheological parameters, wellbore enlargement ratio, and ellipticity, on wellbore cleaning efficiency. The result indicates that increasing the flow rate in conventional wellbores reduces cuttings volume by 75%, while in wellbores with a 0.7 enlargement ratio, the same flow rate only reduces it by 37.8%, highlighting the limitations of geometric complexity. In conventional wellbores, increasing drill pipe rotation reduces cuttings volume by 42.6%, but in enlarged wellbores, only a 13% reduction is observed, indicating that rotation alone is insufficient in large wellbores. Optimizing drilling fluid rheology, such as by increasing the consistency coefficient from 0.3 to 1.2, reduces cuttings volume by 58.78%, while increasing the flow behavior index from 0.4 to 0.7 results in a 38.17% reduction. Although higher enlargement ratios worsen cuttings deposition, a moderate increase in ellipticity improves annular velocity and enhances transport efficiency. This study offers valuable insights for optimizing drilling parameters in irregular wellbores. Full article

Understanding particle transport in rough-walled fractures is essential for predicting flow behavior, clogging, and permeability evolution in natural and engineered subsurface systems. This study develops a fully coupled CFD–DEM framework to investigate how self-affine fractal roughness, represented by the Joint Roughness Coefficient (JRC), governs fluid–particle interactions across multiple scales. Nine fracture geometries with controlled roughness were generated using a fractal-based surface model, enabling systematic isolation of roughness effects. The results show that increasing JRC introduces a hierarchy of geometric perturbations that reorganize the flow field, amplify shear and velocity-gradient fluctuations, and enhance particle–wall interactions. Particle migration exhibits a nonlinear response to roughness due to the competing influences of disturbance amplification and the formation of preferential high-velocity pathways. Furthermore, roughness-controlled scaling relations are identified for mean particle velocity, residence time, and energy dissipation, revealing JRC as a fundamental parameter linking geometric complexity to transport efficiency. Based on these findings, a unified mechanistic framework is established that conceptualizes fractal roughness as a multiscale geometric forcing mechanism governing hydrodynamic heterogeneity, particle dynamics, and dissipative processes. This framework provides new physical insight into transport behavior in rough fractures and offers a scientific basis for improved prediction of clogging, proppant placement, and transmissivity evolution in subsurface engineering applications. Full article

To investigate the influence of particle characteristics on wear in slurry pump flow-through components, this study established a computational fluid dynamics-discrete element method (CFD-DEM) coupled with the Archard wear model for numerical simulation of solid-liquid two-phase flow characteristics and wear mechanisms within the pump. Focusing on the correlation between wear contour distribution and particle collision frequency, the study systematically analyzed the influence mechanisms of particle concentration, size distribution, and shape on wear patterns within the pump. The reliability of the coupled model was validated through external characteristic tests. Results indicate that wear severity on both the impeller and volute increases significantly with rising particle concentration, while wall particle collision frequency exhibits a positive correlation with concentration. Particles of 1.5 mm diameter cause the most severe localized wear on the impeller, whereas the presence of mixed particles partially mitigates the wear effect of larger particles. Both total and localized wear on the volute peak at a particle diameter of 1 mm. Low-sphericity particles intensified overall wear on both the impeller and volute; while high-sphericity particles reduced overall wear, they induced more severe localized wear on the impeller. Volute localized wear was most pronounced at a sphericity of 0.84. This study elucidates the mechanism by which particle characteristics influence wear on slurry pump flow-through components, providing a theoretical basis for optimizing slurry pump design. Full article

Energetic powder processing includes comminution, sieving, drying, conveying, mixing, and packaging, all of which determine product performance and safety. With growing requirements for efficiency and reliability, numerical simulation has become essential for analyzing mechanisms, optimizing parameters, and supporting equipment design. This review summarizes recent progress in simulation techniques such as the discrete element method (DEM), computational fluid dynamics (CFD), and multi-scale coupling while also evaluating their predictive capabilities and limitations across various unit operations and safety concerns such as electrostatic hazards. It, thus, establishes the core “property–parameter–performance” relationships and clarifies mechanisms in multiphase flow, energy transfer, and charge accumulation, and highlights the role of symmetry in improving simulation efficiency. By highlighting persistent challenges, this work lays a foundation for future research, guiding the development of theoretical frameworks and practical solutions for advanced powder processing. Full article

Offshore unconsolidated sandstone reservoirs suffer from severe sand production, which impairs wellbore stability and productivity. This study evaluates gravel packing in light-oil unconsolidated sandstone reservoirs in the Weizhou field. This paper conducts visual sand-control experiments to compare screens and gravel packs, and to quantify the effects of gravel size, packing thickness, packing density, and clay content on sand-retention behavior. On this basis, a coupled CFD–DEM model was developed to simulate sand transport and plugging within the gravel pack. Results show that gravel packing rapidly forms a stable bridging structure, reaching stabilized production 38.1% earlier than the screen and reducing sand production by 74.4%, while maintaining a stable pressure difference and limiting fine-sand breakthrough. Low-viscosity oil enhances sand carrying, increasing the stabilized pressure difference by 12% relative to water. For the low-clay fine reservoir, gravel sizes of 3–6 times the median sand size, packing thickness ≥ 25 mm, and packing density of 90–95% provide a balance between permeability and sand control. Numerical simulations identify a four-stage plugging process—initiation, surface accumulation, deep filling, and equilibrium—offering pore-scale support for the experimental observations. This study offers technical and theoretical guidance for the optimization of gravel-pack sand control in offshore light-oil unconsolidated sandstone reservoirs. Full article

Efficient cutting transport is crucial in challenging drilling environments such as ultra-short-radius horizontal wells. Flexible drill pipes, designed for complex wellbore geometries, offer a potential solution. However, the cutting transport behavior within them remains poorly understood. To improve wellbore cleaning and drilling efficiency, this study investigates the underlying transport mechanisms. The investigation employs a coupled CFD-DEM approach to model cutting transport in flexible drill pipes. This method combines fluid dynamics and particle motion simulations to analyze the interaction between drilling fluid and cuttings, evaluating the impact of factors such as rotational speed, flow rate, and fluid properties on cleaning efficiency. The results indicate that increasing the flow rate at a constant rotational speed significantly reduces the cutting concentration. Nevertheless, beyond a critical flow rate of 1.5 m/s, further increases yield diminishing returns in cleaning efficiency due to transport capacity saturation. In contrast, increasing the rotational speed at a fixed flow rate of 1.42 m/s has a less pronounced effect on cutting transport and increases frictional torque, thereby reducing energy efficiency. Higher rotational speeds primarily enhance the suspension of fine cuttings, with minimal impact on larger particles. Additionally, the rheological properties of the drilling fluid play a key role. A higher flow behavior index increases viscosity near the wellbore, improving transport performance. Conversely, a higher consistency index enhances the fluid’s carrying capacity but increases annular pressure drop, which imposes greater demands on pump capacity. Thus, optimal drilling performance requires balancing pressure losses and cleaning efficiency through comprehensive parameter optimization. Full article