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The mechanism of liquefaction and the factors that cause liquefaction behavior have previously been examined and evaluated, both analytically and experimentally; construction including liquefaction countermeasures is being implemented, based on these findings. This study presents a theoretical visualization of the mechanism of liquefaction generation and evaluates the behavior of particles in the ground. Specifically, an MPSM-DEM coupled CAE system (CAES) is employed to view the events beneath the ground, modeled three-dimensionally when an external acceleration is applied to simulate seismic waves and reveals the behavior below the surface. The numerical simulation of the liquefaction phenomenon, as represented by an MPSM-DEM coupled CAES system, clearly showed the mechanism of liquefaction generation and contributed to the design and accountability of more economical and sustainable liquefaction countermeasures, regardless of the field of specialization.

The behavior of solid-liquid two-phase flow in a deep-sea slurry lifting pump is crucial to the stability and efficiency of the offshore drilling system. In this work, a hydraulic geometry model of a two-stage slurry lifting pump was established. Solid-liquid two-phase flow characteristics under clear water and drilling fluid conditions were examined through numerical simulation using the computational fluid dynamics-discrete element method. The use of Pearson correlation analysis revealed a statistical link between particle passage time and particle forces. The performance of the slurry lifting pump was also evaluated experimentally, supporting the reliability of the numerical results. Findings show that under drilling fluid conditions, the flow field and particle forces display greater complexity, accompanied by a 2.05% increase in particle volume concentration and a 0.21 s extension in average particle passage time. Among all forces, the drag force exhibits the strongest association with passage time. Reducing particle drag force can improve the transportability of particles in the slurry lifting pump. These results provide practical insight for optimizing the anti-clogging performance of deep-sea slurry lifting pumps.

The feeding shoe, which is a critical component that connects the rotary valve to the conveying pipeline, significantly influences the performance of powder conveying systems. The Computational Fluid Dynamics–Discrete Element Method (CFD-DEM) was employed to investigate particle dynamics within various feeding shoe designs under gas–solid two-phase flow conditions. Through comparative analyses of two-phase flow characteristics and particle trajectories, three feeding shoe configurations, namely, through, horn, and funnel types, were evaluated, along with the effects of varying gas velocities. Key structural parameters, including opening diameter and inclination angle, were systematically examined to assess their effect on particle transport efficiency. Results demonstrated that feeding shoes with a low inclination angle or a small opening diameter exhibited poor particle flow, while those with a large opening diameter tended to induce backflow on the left side. By contrast, through-type feeding shoes with a large inclination angle and equal opening diameter achieved optimal conveying performance, minimizing backflow and enhancing flow efficiency. These findings provide theoretical insights for optimizing feeding shoe designs, improving conveying efficiency, and reducing production costs, offering valuable guidance for advancements in powder conveying technology and fluid mechanics.

As a promising and convenient numerical calculation approach, the discrete element method (DEM) has been increasingly adopted in the research of agricultural machinery. DEM is capable of monitoring and recording the dynamic and mechanical behavior of agricultural materials in the operational process of agricultural machinery, from both a macro-perspective and micro-perspective; which has been a tremendous help for the design and optimization of agricultural machines and their components. This paper reviewed the application research status of DEM in two aspects: First is the DEM model establishment of common agricultural materials such as soil, crop seed, and straw, etc. The other is the simulation of typical operational processes of agricultural machines or their components, such as rotary tillage, subsoiling, soil compaction, furrow opening, seed and fertilizer metering, crop harvesting, and so on. Finally, we evaluate the development prospects of the application of research on the DEM in agricultural machinery, and look forward to promoting its application in the field of the optimization and design of agricultural machinery.

This study aims to systematically analyze the effects of various operational parameters on the continuous mixing process of concrete using the Discrete Element Method (DEM) combined with a wet mixing model, with the objective of optimizing mixing uniformity and material flow to improve concrete mixing quality and efficiency in practical engineering applications. The results indicate that an appropriate water addition rate (e.g., 10 m/s) and a moderate moisture content (e.g., 2:9) can significantly enhance the uniformity of concrete mixing. Additionally, a moderate rotational speed (e.g., 200 rpm) achieved good mixing effects in a short time, avoiding issues such as oversaturation and uneven mixing. This study provides theoretical support and a data foundation for optimizing concrete mixing processes, contributing to improvements in mixing quality and efficiency in engineering practice.

Seepage plays a crucial role in the mechanical behavior and damage modes of geotechnical materials. In this work, based on the unsteady seepage equation, a hydraulic coupling numerical simulation algorithm combining interpolation finite difference method (FDM) and discrete element method (DEM) is proposed to explore the intrinsic mechanism of the interaction between geotechnical materials and the seepage process. The method involves constructing an irregular fluid calculation grid around each particle and deriving the two-dimensional unsteady seepage governing equation and its stability conditions using interpolation and the FDM. The efficiency of the seepage calculation was investigated by numerically varying the parameters of the difference format. The method was applied to simulate the generation of gushing soil in a sinking area of a sunk shaft under hydraulic drive conditions. The results indicate that the improved FDM can effectively simulate the two-dimensional seepage of soil with high calculation efficiency. The hydraulic conductivity and time step positively correlate with the calculation efficiency of the difference format, whereas the spatial step has a negative correlation. The proposed method also accurately reflects the process of gushing soil damage. These results provide a solid theoretical basis to study the geotechnical seepage field and its associated damage mechanisms.

The discrete element method (DEM) is the most dominant method for the numerical prediction of dynamic behaviour at grain or particle scale. Nevertheless, due to its discontinuous nature, the DEM is inherently unable to describe microscopic features of individual bodies which can be considered as continuous bodies. To incorporate microscopic features, efficient numerical coupling of the DEM with a continuous method is generally necessary. Thus, a generalised multi-scale PD–DEM framework is developed in this work. In the developed framework, meshfree discretised Peridynamics (PD) is used to describe intra-particle forces within bodies to capture microscopic features. The inter-particle forces of rigid bodies are defined by the DEM whereas a hybrid approach is applied at the PD–DEM interface. In addition, a staggered multi-scale time integration scheme is formulated to allow for an efficient numerical treatment of both methods. Validation examples are presented and the applicability of the developed framework to capture the characteristics mixtures with rigid and deformable bodies is shown.

Laser powder bed fusion (LPBF) additive manufacturing (AM) has been adopted by various industries as a novel manufacturing technology. Powder spreading is a crucial part of the LPBF AM process that defines the quality of the fabricated objects. In this study, the impacts of various input parameters on the spread of powder density and particle distribution during the powder spreading process are investigated using the DEM (discrete element method) simulation tool. The DEM simulations extend over several powder layers and are used to analyze the powder particle packing density variation in different layers and at different points along the longitudinal spreading direction. Additionally, this research covers experimental measurements of the density of the powder packing and the powder particle size distribution on the construction plate.

Granular mixing with bladed mixers is widely used across various industries. This study employed the Discrete Element Method (DEM) to explore the effects of rake angles (30° (150°), 45° (135°), 60° (120°), and 90°), rotational speeds (25, 50, 75, 100, and 150 rpm), and fill levels (1, 2 and 3) on the flow and mixing efficiency of 2- and 3-bladed impellers. The Lacey mixing index, granular temperature, circumferential velocity, diffusion coefficient, and void percentage were used to evaluate mixer performance. Results showed that for rake angles ≥ 90°, the highest values for the Lacey mixing index, granular temperature, and diffusion coefficient were achieved, although particle circumferential velocity decreased. The mixing efficiency improved significantly with 2-bladed impellers at rake angles of 135° and 150° and 3-bladed impellers at 120° and 135° rake angles. The void percentage increased linearly with rake angle. Rotational speed and fill levels were found to strongly affected the Lacey mixing index, with optimal rotational speeds < 100 rpm. Increasing rotational speed raised particle granular temperature, circumferential velocity, diffusion coefficient, and void percentage. For 3-bladed impellers, performance improved at fill levels where H/h > 1, although granular temperature and diffusion coefficient decreased with increasing fill levels. Granular temperature and diffusion coefficient were found to be reliable indicators of pre-mixing performance. It is recommended to use 3-bladed impellers at H/h > 1 and rotational speeds < 100 rpm, while 2-bladed impellers perform better at lower fill levels.

Due to the lack of an exact simulation model for spinach seeds, existing seed-metering devices exhibit poor seeding performance and struggle to achieve precise seeding of two seeds per seed-metering hole. This study proposes a method for calibrating discrete element parameters of spinach seeds and develops a seed-metering device with rectangular seed-metering holes tailored to the two-seeds-per-hole requirement. Firstly, a spinach seed discrete element model was constructed. Based on the Box-Behnken Design experimental scheme, simulations of angle of repose and fluidity, combined with physical of angle of repose (38.27°) and physical mass flow rate (18.60 g/s), were used to calibrate contact parameters: (1) between spinach seed models (coefficient of restitution: 0.385; coefficient of static friction: 0.481; coefficient of rolling friction: 0.042); and (2) between seed models and PVC plate (coefficient of restitution: 0.339; coefficient of static friction: 0.600; coefficient of rolling friction: 0.408). Subsequently, simulated and physical bulk density tests were conducted to verify the validity of the established spinach seed model. Guided by the agronomic requirements for spinach seed planting, the range of dimensional parameters for the seed-metering holes was defined. Using the Box-Behnken Design, simulated seeding tests were performed to optimize the device’s structural parameters (hole depth, hole length, hole width, and seed-filling angle), resulting in optimal values of 2.52 mm, 3.67 mm, 5.15 mm, and 37.99°, respectively. Finally, physical seeding tests were conducted, achieving a qualified seeding rate of 92.23% at a seeding speed of 10 r/min. These results confirm the design accuracy and high operational efficiency of the device. This study lays a foundation for the overall design of future spinach planters.