Zhang X Y, Hu X, Zhang L X, Kheiry A N O. Simulation and structural parameter optimization of rotary blade cutting soil based on SPH method. Int J Agric & Biol Eng, 2024; 17(3): 82–90. DOI: 10.25165/j.ijabe.20241703.8470
Citation: Zhang X Y, Hu X, Zhang L X, Kheiry A N O. Simulation and structural parameter optimization of rotary blade cutting soil based on SPH method. Int J Agric & Biol Eng, 2024; 17(3): 82–90. DOI: 10.25165/j.ijabe.20241703.8470

Simulation and structural parameter optimization of rotary blade cutting soil based on SPH method

  • Pre-sowing mechanical tillage in crop fields is a primary task and important aspect of crop production. The interaction between the tillage components and the soil plays a crucial role in determining the energy consumption of tillage machinery. Therefore, it is essential to investigate soil-tool interaction mechanisms and optimize tool design for energy savings in soil cutting. The study employed the Smoothed Particle Hydrodynamics (SPH) method to investigate the soil cutting process of a typical rotary blade. The article describes the principles and modeling process of the SPH method in detail. It includes the selection of constitutive models, boundary treatments, and particle conversion. A high-precision soil-tool interaction model was established to analyze the deformation zone of the soil, cutting energy, cutting resistance, and soil particle movement. Orthogonal simulation experiments and response surface methodology were used to optimize key design parameters of the rotary blade considering both the reduction in cutting power consumption and the impact on the structural performance of the tool. The optimal parameters were determined as follows: a bending point included angle of 30°, a side cutting edge bending line direction angle of 51°, and a bending angle of 120°. These parameters resulted in a minimum power consumption of 0.181 kW while meeting the required structural performance. Finally, experiments were conducted on field rotary tillage, and the measured power consumption showed a deviation of 7.1% from the simulated power consumption. The optimized power consumption was reduced by 9.52% compared to the initial power consumption, validating the accuracy of the simulation process and the effectiveness of energy savings.
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