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<p>To determine the discrete element simulation parameters for the walnut kernel grading process, the stacking angle response of walnut kernels obtained from bench tests and simulation tests was used. The discrete element simulation parameters were calibrated using response surface optimization. The physical parameters required for the simulation test of the walnut kernel grading process were measured through bench testing. Discrete element simulation models of walnut kernels with varying degrees of completeness were established using 3D scanning technology and EDEM software. The walnut stacking angle was measured as 23.55° using the injection method, combined with MATLAB image processing for boundary fitting. The Plackett–Burman test, the steepest ascent test, and the Box–Behnken test were designed using Design–Expert software, with the stacking angle as the response value, to construct the regression model and optimize the parameters. The optimal combination of significant parameters is as follows: walnut kernel–walnut kernel rolling friction coefficient of 0.03, walnut kernel–walnut kernel static friction coefficient of 0.136, and walnut kernel–walnut kernel collision recovery coefficient of 0.26. The simulated and measured values of the natural angle of repose for walnut kernels under the optimal parameter combinations were compared. A two-sample <i>t</i> test (<i>p</i> &gt; 0.05) confirmed that there was no significant difference between the two, verifying the reliability of the simulation parameters for walnut kernels. Using the Dalton plate-based loading device and the intermittent ladder loading device for walnut kernel discrete effect testing, the relative errors between the simulated and measured values of walnut kernel discrete rates for the two loading devices were 1.69 and 1.81%, respectively. These results indicate that the walnut kernel discrete meta-model and simulation parameters are reliable, providing a solid reference for the design and optimization of walnut kernel grading and sorting devices.</p>

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Parameter calibration and testing for discrete element simulation of walnut kernels

  • 期刊论文

  • 发表日期：

    2025年6月9日

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  • Jianian Li,
  • Wanghan Zhang,
  • Daoran Li,
  • Yingjie Yu

摘要

To determine the discrete element simulation parameters for the walnut kernel grading process, the stacking angle response of walnut kernels obtained from bench tests and simulation tests was used. The discrete element simulation parameters were calibrated using response surface optimization. The physical parameters required for the simulation test of the walnut kernel grading process were measured through bench testing. Discrete element simulation models of walnut kernels with varying degrees of completeness were established using 3D scanning technology and EDEM software. The walnut stacking angle was measured as 23.55° using the injection method, combined with MATLAB image processing for boundary fitting. The Plackett–Burman test, the steepest ascent test, and the Box–Behnken test were designed using Design–Expert software, with the stacking angle as the response value, to construct the regression model and optimize the parameters. The optimal combination of significant parameters is as follows: walnut kernel–walnut kernel rolling friction coefficient of 0.03, walnut kernel–walnut kernel static friction coefficient of 0.136, and walnut kernel–walnut kernel collision recovery coefficient of 0.26. The simulated and measured values of the natural angle of repose for walnut kernels under the optimal parameter combinations were compared. A two-sample t test (p > 0.05) confirmed that there was no significant difference between the two, verifying the reliability of the simulation parameters for walnut kernels. Using the Dalton plate-based loading device and the intermittent ladder loading device for walnut kernel discrete effect testing, the relative errors between the simulated and measured values of walnut kernel discrete rates for the two loading devices were 1.69 and 1.81%, respectively. These results indicate that the walnut kernel discrete meta-model and simulation parameters are reliable, providing a solid reference for the design and optimization of walnut kernel grading and sorting devices.