This paper reveals improved models for soil tool interactions, enhancing tillage efficiency in black soil, indicating sustainable agricultural practices.
In support of sustainable agricultural practices and soil conservation in black soil regions, the accurate modeling of soil–machine interactions is essential for optimizing tillage operations and minimizing environmental impacts. To achieve the precise calibration of interaction parameters between black soil and soil-engaging components, this paper proposes an innovative segmented calibration method to determine the discrete element parameters for interactions between black soil and agricultural machinery parts. The Hertz–Mindlin with Johnson–Kendall–Roberts (JKR) Cohesion contact model in the discrete element method (DEM) software was employed, using a two-stage calibration process. In the first stage, soil particle contact parameters were optimized by combining physical pile angle tests with multi-factor simulations guided by Design-Expert, resulting in the optimal parameter set (JKR surface energy 0.46 J/m2, restitution coefficient 0.51, static friction coefficient 0.65, rolling friction coefficient 0.13). In the second stage, based on validated soil parameters, the soil–65Mn steel interaction parameters were precisely calibrated (JKR surface energy 0.29 J/m2, restitution coefficient 0.55, static friction coefficient 0.64, rolling friction coefficient 0.07). Simulation results showed that the error between simulated and measured pile angles was less than 0.5%. Additionally, verification through rotary tillage operation tests comparing simulated and measured power consumption demonstrated that within the cutter roller speed range of 150–350 r·min−1, the power error remained below 0.5 kW. Ground surface flatness was introduced as a supplementary validation indicator, and the differences between simulated and measured values were small, further confirming the accuracy of the DEM model in capturing soil–tool interaction and predicting tillage quality. This paper not only enhances the accuracy of DEM-based modeling in agricultural engineering but also contributes to the development of eco-efficient tillage tools, promoting sustainable land management and soil resource protection.
No takes yet. Share an insight, caveat, or question.
Qi et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: