In order to enhance the accuracy of discrete element numerical simulations in the processing of small-seed particles, it is essential to calibrate the parameters of seeds within the discrete element software. This study employs a series of physical tests to obtain the physical and contact parameters of red clover seeds. A discrete element model of red clover seeds is established. Plackett–Burman Design, steepest ascent, and Central Composite Design experiments are sequentially conducted. The simulation deviation of the resting angle of red clover seeds is employed as the evaluation criterion for parameter optimization. The results indicate that the coefficients of static friction between red clover seeds, the coefficients of rolling friction between red clover seeds, and the coefficients of static friction between red clover seeds and the steel plates significantly influence the resting angle. Modeling was performed using a backpropagation neural network, a genetic algorithm–optimized BP network, particle swarm optimization, and simulated annealing. It was found that GA-BP ensured both accuracy and stability. Compared to the traditional response surface methodology, GA-BP showed better fitting performance. For the optimized red clover seed simulation, the error between the angle of repose and the physical experiment was 0.98%. This research provides new insights into the calibration of small-grain seed parameters, demonstrating the value of GA-BP for precision modeling.

In order to solve the problem of the low qualification rate of the pilling and coating of small-grain forage seeds, a vibration force field is introduced to the traditional vertical disk coating machine to promote the mixing of materials and improve the qualification rate of the pilling. Using the typical small-grain forage seed red clover as an example, we used the vibration force field after adding seed powder particles to a coating pot for the theoretical analysis of the force situation, using the discrete element software EDEM to construct a red clover seed simulation model with the coefficient of discretization as the evaluation index. We studied the effects of the rotational speed of the coating pot, the vibration frequency of the pot, the amplitude of the vibration of the pot, and the other operating parameters of the pot on the uniformity of the seed powder mixing, with the pelletization of the pass rate as the physical evaluation standard, using a one-way test to study the effect of operating parameters on the pelletization pass rate. We used the qualified rate as the physical evaluation standard, through a single-factor test, to study the influence of the working parameters on the qualification rate of the pilling. The results show that the simulation test evaluation index of the discrete coefficient and the physical test evaluation index of the pilling qualification rate with the change rule of the working parameters is consistent with the discrete coefficient, and can be used as an indirect evaluation index of the quality of pilling. To further determine the optimal combination of working parameters, a quadratic regression orthogonal design test was conducted with the discrete coefficients as the evaluation index, and the second-order regression equations of the red clover seeds were established and analyzed by ANOVA using Design-Expert software. The study shows that, when the rotational speed of the coating pot is 307.204 rpm, the vibration frequency is 2.526 Hz, and the vibration amplitude of the coating pot is 5.843 mm, the predicted coefficient of dispersion at this time is 8.1%. Simulation using the best combination of parameters to obtain the average value of the dispersion coefficient of 8.4%, relative to the predicted value of 3.7%, indicated that the optimization of the experimental regression model is accurate, and the results obtained for the vibration of small seeds under the conditions of the design of the pellet granulation coating machine and the optimization of the pelletization coating process parameters have a certain degree of reference significance.

The physical and mechanical properties of the materials in the swirling fluidized-bed seed pelleting unit affect the mixing degree of the materials in the pelleting and coating process, which is of great significance to research on pelleting and coating. The problem of discrete particle model parameters affecting CFD-DEM simulation results is addressed. In this paper, red clover seeds (referred to as seeds) and pelletized coating powder (referred to as powder) were used as the research objects, and the JKR. model was selected to calibrate the contact parameters between seeds and powder based on particle amplification theory. With the powder rest angle as the response value, a simulation calibration test was conducted; the parameters with significant effects on the response value were screened based on the Plackett–Burman test, and the steepest climb test determined the range of factor levels of essential parameters. The Box–Behnken test was used to establish the curvilinear response surface and quadratic regression equation to determine the best combination of simulation parameters for the powder. The discrete element rest angle was conducted with the best combination of parameters. The error of the test compared with the physical examination was 1%. The particles calibrated by simulation were subjected to the pneumatic suspension velocity test and particle mixing test. The test results matched the physical test results, which further verified the accuracy and applicability of the established discrete element model and parameters for coated powders.

This study aimed to optimize the pelleting and coating process for red clover seeds, addressing the issue of low pelleting success rates. Through theoretical analysis and experimental research, coating pan fill rate, powder supply quantity, and pelleting time were identified as key factors influencing the pelleting success rate. Single-factor experiments were conducted to investigate the effects of these parameters on the quality of red clover seed pelleting and coating. Based on these results, orthogonal trials were carried out, and response surface analysis was employed to reveal the influence patterns and interactions of each factor. The research results indicate that the factors affecting the pelleting success rate, ranked in order of importance, are coating pan fill rate, pelleting time, and powder supply quantity. Through mathematical model optimization, the optimal combination of process parameters was determined to be coating pan fill rate of 35.9%, powder supply quantity of 160.2 g, and pelleting time of 6.9 s. Under these conditions, a pelleting success rate of 94.3% was achieved in validation experiments. This study provides a theoretical foundation and practical guidance for optimizing the pelleting and coating process of red clover seeds, which is significant for improving seed coating quality and promoting red clover cultivation.

Sand collectors play an indispensable role in the study of land desertification, with the wind–sand separator serving as a vital core component. It plays a pivotal role in researching soil wind erosion. In response to the challenge of wind–sand separation in high-wind conditions, we introduce a novel approach. We designed, optimized, and validated a double-column scrambler wind–sand separator through computational fluid dynamics (CFD) simulations and wind tunnel experiments. Our test results showcased the impressive performance of this double-column scrambler wind–sand separator. It achieved substantial reductions in wind velocities at both the exhaust and sandfall ports, with reductions of 89.56% and 89.85%, respectively. Furthermore, the wind–sand separation efficiency consistently exceeded 98% across wind speeds ranging from 6 to 15 m/s. This study establishes a robust scientific foundation for further enhancements in the performance of the double-column scrambler wind–sand separator, holding promise for advancements in the field of desertification monitoring and control.