三七种植土壤离散元仿真模型参数标定

    Parameter calibration of discrete element simulation model for Panax notoginseng planting soil

    • 摘要:
      目的 获取三七Panax notoginseng种植土壤与触土部件相互作用的离散元仿真模型参数。
      方法 基于Hertz-Mindlin with JKR接触模型建立三七种植土壤离散元模型并进行参数标定。首先,以土壤颗粒间及土壤−65Mn钢板间的JKR表面能、恢复系数、静摩擦系数、动摩擦系数为试验因素,以土壤堆积角、土壤在65Mn板上的滚动距离为评价指标。其次,采用基于Box-Behnken的响应面优化方法建立土壤堆积角、滚动距离回归模型。
      结果 对回归模型进行寻优,得到仿真标定的土壤颗粒间JKR表面能、恢复系数、静摩擦系数和动摩擦系数的最优值分别为14.88 J/m2、0.53、0.46和0.150,标定的土壤−65Mn板间JKR表面能、恢复系数、静摩擦系数和动摩擦系数的最优值分别为7.02 J/m2、0.59、0.57和0.058。通过三七挖掘铲仿真试验与土槽试验对比分析得到,挖掘铲受XY轴方向平均阻力仿真值与实测值相对误差分别为9.91%、8.78%。
      结论 标定的离散元土壤模型参数准确度高,研究可为三七收获机触土部件及装备优化提供理论参考。

       

      Abstract:
      Objective To obtain the parameters of the discrete element simulation model for the interaction between Panax notoginseng planting soil and soil-engaging components.
      Method This paper established a discrete element model of P. notoginseng planting soil based on the Hertz-Mindlin with JKR contact model, and calibrated parameters. Firstly, the JKR surface energy, restitution coefficient, static friction coefficient and rolling friction coefficient between soil particles and soil-65Mn steel plate were used as experiments factors, and the soil repose angle and the rolling distance of soil on the 65Mn plate were used as evaluation indexes. Secondly, the regression model for soil repose angle and rolling distance was established through the response surface optimization method based on Box-Behnken.
      Result The regression model was optimized, and the optimal values of JKR surface energy, restitution coefficient, static friction coefficient and rolling friction coefficient between soil particles calibrated by simulation were 14.88 J/m2, 0.53, 0.46 and 0.150, respectively. The calibrated optimal values of JKR surface energy, restitution coefficient, static friction coefficient and rolling friction coefficient between soil-65Mn steel plate were 7.02 J/m2, 0.59, 0.57 and 0.058, respectively. Through the comparative analysis of the simulation test and the soil-bin test, the relative errors of the simulated and measured average resistance of the excavating shovel in the X and Y axis directions were 9.91% and 8.78%, respectively.
      Conclusion The calibrated discrete element soil model parameters have high accuracy, and the research can provide a theoretical reference for the optimization of the soil-engaging components and equipment of the P. notoginseng harvester.

       

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