In China, especially in Xinjiang Region, mulch film remaining in the soil has severely jeopardized the safety of soil resources. To numerically simulate the residual film-soil-recovery implementation system, a virtual mulch film model with consistent physical and mechanical properties with real mulch film needs to be established. In this study, a flexible deformable virtual mulch film model was constructed using YADE software based on the Minkowski Sum principle and the ball-ball force-displacement constitutive rule, as well as the contact failure rule were established. The deformation behaviors of cylinders and PFacet elements, such as stretching, bending, and torsion, were described. By splicing the basic PFacet elements, a virtual mulch model was established. The mechanical model of a virtual mulch film under tension was established and the axial tensile stiffness coefficient k n was determined to be 43.30 N• m. To verify the physical and mechanical properties of this virtual mulch film, both real and virtual stretching and tearing tests were conducted. The experimental results showed that: in the process of stretching and tearing of real and virtual films, the properties of morphological features of both are basically identical; however, they clearly differ in force-displacement. The viscoelastic constitutive model between balls and yield judgment conditions requires further study.

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In the current paper, a coated cotton-seed discrete element model was established. Furthermore, we designed a device for the simultaneous determination of the repose and accumulation angles, and Plackett–Burman and central composite design (CCD) tests were performed with the repose and accumulation angles as the test indexes. The static friction coefficient between seeds (SFCC) and the dynamic friction coefficient between seeds (DFCC) were observed to have a significant influence on the indexes and were thus selected for the subsequent analysis (P < 0.05). Analysis of variance revealed the terms of these two parameters to have a significant effect on the relative error of the repose angle (RERA) and the relative error of accumulation angles (REAA) (P < 0.05). A solution to the proposed mathematical model was determined via the NSGA-Ⅱ genetic algorithm and the Pareto optimal solution set was obtained. Based on multi-objective optimization, the SFCC and DFCC were determined as 0.174 and 0.068, for RERA and REAA values of 1.715% and 1.712%, respectively. Simulations were then performed using the optimal parameters. Results of the T-test demonstrated that there were no significant differences between the simulated and physical test results.

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