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Discrete Element Model of Oil Peony Seeds and the Calibration of Its Parameters

Author

Listed:
  • Hao Zhou

    (College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China
    Longmen Laboratory, Luoyang 471003, China
    Henan Collaborative Creation Center for Advanced Manufacturing of Machinery and Equipment, Luoyang 471003, China)

  • Kangtai Li

    (College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China)

  • Zhiyu Qin

    (College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China)

  • Shengsheng Wang

    (College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China
    Longmen Laboratory, Luoyang 471003, China
    Henan Collaborative Creation Center for Advanced Manufacturing of Machinery and Equipment, Luoyang 471003, China)

  • Xuezhen Wang

    (College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China
    Longmen Laboratory, Luoyang 471003, China
    Henan Collaborative Creation Center for Advanced Manufacturing of Machinery and Equipment, Luoyang 471003, China)

  • Fengyun Sun

    (College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China)

Abstract

Oil peony is an important oil crop that is primarily sown by using artificial methods at present. Its seeder encounters the problems of low efficiency of seeding that significantly limits the highly efficient mechanized production of high-quality peony oil. In this study, Fengdan white oil peony seeds were used as the research object and repose angle as the response value to establish a discrete element model (DEM) and parameter calibration. The range of parameters of oil peony seeds was first obtained through an experiment, and their repose angle was obtained by an inclinometer. A three-dimensional DEM of oil peony seeds was then established. The Plackett–Burman (PB) test was utilized to screen the parameters that had a significant influence on the repose angle, and the steepest ascent (SA) test was applied to determine their optimum range of testing. Following this, based on Box–Behnken (BBD) test results, a second-order regression model between the important parameters and the repose angle was constructed. Finally, the absolute minimum difference between simulated and measured repose angles was utilized as the objective of optimization to obtain the following optimum combination of parameters: The values of the seed–steel collision recovery coefficient (CRC), seed–seed static friction coefficient (SFC), seed–steel SFC, and seed–seed rolling friction coefficient (RFC) were 0.704, 0.324, 0.335, and 0.045, respectively. This optimal combination of parameters was confirmed through simulations, and the error between simulated and measured repose angles was only 0.67%, indicating that the calibrated DEM of oil peony seeds was reliable.

Suggested Citation

  • Hao Zhou & Kangtai Li & Zhiyu Qin & Shengsheng Wang & Xuezhen Wang & Fengyun Sun, 2024. "Discrete Element Model of Oil Peony Seeds and the Calibration of Its Parameters," Agriculture, MDPI, vol. 14(7), pages 1-13, July.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:7:p:1092-:d:1430190
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    References listed on IDEAS

    as
    1. Guichuan Li & Haiyu Li & Xuan Li & Zhichao Gong & Qinghua Yang & Yuxiang Huang & Zuoli Fu, 2023. "Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test," Agriculture, MDPI, vol. 13(5), pages 1-15, May.
    2. Jinming Zheng & Lin Wang & Xiaochan Wang & Yinyan Shi & Zhenyu Yang, 2023. "Parameter Calibration of Cabbages ( Brassica oleracea L.) Based on the Discrete Element Method," Agriculture, MDPI, vol. 13(3), pages 1-17, February.
    3. Yan Liu & Guopeng Mi & Shilin Zhang & Peng Li & Yuxiang Huang, 2022. "Determination of Discrete Element Modelling Parameters of Adzuki Bean Seeds," Agriculture, MDPI, vol. 12(5), pages 1-13, April.
    4. Xinping Li & Wantong Zhang & Shendi Xu & Fuli Ma & Zhe Du & Yidong Ma & Jing Liu, 2023. "Calibration of Collision Recovery Coefficient of Corn Seeds Based on High-Speed Photography and Sound Waveform Analysis," Agriculture, MDPI, vol. 13(9), pages 1-19, August.
    5. Kojo Atta Aikins & Mustafa Ucgul & James B. Barr & Emmanuel Awuah & Diogenes L. Antille & Troy A. Jensen & Jacky M. A. Desbiolles, 2023. "Review of Discrete Element Method Simulations of Soil Tillage and Furrow Opening," Agriculture, MDPI, vol. 13(3), pages 1-29, February.
    6. Binnan Zhou & Yi Zuo & Lixia Hou, 2023. "Parameter Calibration of Xinjiang Paperbark Walnut Kernels by Discrete Element Simulation," Agriculture, MDPI, vol. 13(2), pages 1-13, January.
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