Traditional fluted roller seed metering devices exhibit unstable seeding rates during forage seed mixed sowing. To address this issue, a new seed metering device was designed based on the agronomic requirements of forage seed mixing and the structural characteristics of fluted roller mechanisms. The discrete element method (DEM) was employed to numerically simulate the movement of particles within the seed metering device. Single-factor experiments identified optimal parameter ranges for the seed metering device: a metering shaft speed of 10–20 r/min, a seed inlet width of 8–24 mm, and a seed outlet height of 10–20 mm. A response surface methodology (RSM) experiment was then designed using Design-Expert 13 software. The results yielded optimal operating parameters: a metering shaft speed of 18.9 r/min, a seed inlet width of 9.3 mm, and a seed outlet height of 14.4 mm. The field experiment validated the seeding performance with the optimal parameter combination. The coefficient of variation (CV) for the first-class seed (CV₁) was 4.16%, and for the second-class seed (CV₂) it was 2.98%, both of which met the requirements for mixed sowing of forage.

The study of Leymus chinensis seed cleaning has been hindered by the lack of accurate discrete-element contact parameters for seed–straw interactions, thereby limiting, to some extent, the optimization of cleaning equipment. To address this issue, the present study analyzed a mixture of L. chinensis seeds and straw, and determined their fundamental physical and contact parameters via laboratory experiments. The Hertz–Mindlin (no slip) discrete element simulation model was employed to calibrate the parameters of the seed–straw mixture. A Plackett–Burman test was used to identify key factors significantly affecting the repose angle, including the seed–seed static friction coefficient and the seed–straw static and dynamic friction coefficients. These factors’ optimal ranges were further refined using steepest ascent experiments. A Box–Behnken design was used to optimize contact parameters, resulting in the following values: a seed–seed static friction coefficient of 0.709, a seed–straw static friction coefficient of 0.281, and a seed–straw dynamic friction coefficient of 0.085. Validation experiments demonstrated an error of less than 2.14%, confirming the reliability of the calibrated parameters. This study offers a theoretical foundation for discrete element simulations in L. chinensis seed cleaning applications.

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.