The discrete element method has become an essential technique for examining the interaction between maize seeds and related mechanical components. Among these, precise selection of discrete element parameters is essential for accurately forecasting the motion of maize seed particles and the interaction processes between particles and mechanical components. Due to the irregular shape of maize seeds, it is difficult to directly measure particle parameters of maize seed such as coefficient of static friction between seed particles (μspp), coefficient of rolling friction between seed particles (μrpp), and coefficient of rolling friction between seed particles and working components (μrpw). As a result, these parameters necessitate calibration methods for accurate determination. Nonetheless, the presence of over two calibrated parameters can potentially result in challenges concerning ambiguous combinations of parameters. In this paper, three main plant maize varieties are utilized as research subjects. This paper investigates the necessity for accurate calibration of μspp, μrpp, and μrpw by the bulk density and “self-flow screening” tests. In addition, the sensitivity relationship between macroscopic physical phenomena and particle parameters is analyzed. The results indicate a substantial decrease in bulk density with the increase of μspp and μrpp, coupled with a significant reduction in the percentage passing of maize seeds as μrpw rises, emphasizing the critical need for the accurate calibration of these three parameters. Additionally, a network of sensitive relationships between macroscopic physical phenomena and three parameters is elucidated: the unloading time is sensitive only to μrpp, the dynamic angle of repose is influenced by both μspp and μrpp, and the percentage passing is impacted by all three parameters. Utilizing the network of sensitive relationships, a targeted calibration method is obtained for maize seed parameters. Initially, μrpp undergoes calibration using the unloading time test, enabling subsequent calibration of μspp through the dynamic angle of repose test. Subsequently, μrpw is calibrated via the screening rate test. Thus, the problem of ambiguous parameter combinations for parameter calibration is solved. The calibrated parameters undergo validation via lifting cylinder and shear angle tests. By comparing experimental results with simulation data, the effectiveness and accuracy of the parameters are confirmed, illustrating the viability and dependability of the calibration approach. Graphical abstract

Targeted calibration and validation of discrete element parameters of maize seed based on the sensitive relationship between macro-physical phenomena and particle parameters

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发表日期：

2025年6月3日

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Qiu Dong,
Kuo Sun,
Meng Jiang,
Xinnan Yu,
Chenglin He,
Hongqian Lv,
Jianqun Yu,
Wenjun Wang,
Yulong Chen,
Mingwei Li,
Jingling Song,
Long Zhou

摘要

The discrete element method has become an essential technique for examining the interaction between maize seeds and related mechanical components. Among these, precise selection of discrete element parameters is essential for accurately forecasting the motion of maize seed particles and the interaction processes between particles and mechanical components. Due to the irregular shape of maize seeds, it is difficult to directly measure particle parameters of maize seed such as coefficient of static friction between seed particles (μ_spp), coefficient of rolling friction between seed particles (μ_rpp), and coefficient of rolling friction between seed particles and working components (μ_rpw). As a result, these parameters necessitate calibration methods for accurate determination. Nonetheless, the presence of over two calibrated parameters can potentially result in challenges concerning ambiguous combinations of parameters. In this paper, three main plant maize varieties are utilized as research subjects. This paper investigates the necessity for accurate calibration of μ_spp, μ_rpp, and μ_rpw by the bulk density and “self-flow screening” tests. In addition, the sensitivity relationship between macroscopic physical phenomena and particle parameters is analyzed. The results indicate a substantial decrease in bulk density with the increase of μ_spp and μ_rpp, coupled with a significant reduction in the percentage passing of maize seeds as μ_rpw rises, emphasizing the critical need for the accurate calibration of these three parameters. Additionally, a network of sensitive relationships between macroscopic physical phenomena and three parameters is elucidated: the unloading time is sensitive only to μ_rpp, the dynamic angle of repose is influenced by both μ_spp and μ_rpp, and the percentage passing is impacted by all three parameters. Utilizing the network of sensitive relationships, a targeted calibration method is obtained for maize seed parameters. Initially, μ_rpp undergoes calibration using the unloading time test, enabling subsequent calibration of μ_spp through the dynamic angle of repose test. Subsequently, μ_rpw is calibrated via the screening rate test. Thus, the problem of ambiguous parameter combinations for parameter calibration is solved. The calibrated parameters undergo validation via lifting cylinder and shear angle tests. By comparing experimental results with simulation data, the effectiveness and accuracy of the parameters are confirmed, illustrating the viability and dependability of the calibration approach.

Graphical abstract