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<p>Accurately simulating the interaction between trenching devices and river sand substrates is crucial for optimizing agricultural practices in Gobi Desert facility agriculture. This study calibrates Discrete Element Method (DEM) parameters for river sand substrate in the Gobi Desert of Northwest China, utilizing the Hertz-Mindlin contact model coupled with the Johnson-Kendall-Roberts (JKR) contact model in EDEM software. Key parameters, including stacking angle, particle size distribution, and morphology of the river sand, were measured using various methods and tools, such as an image acquisition system, vibration grading device, and stacking angle test apparatus. A model was developed to simulate the interaction between the river sand substrate and trenching device. The river sand matrix exhibited a stacking angle of 31.91°, with 9.85% of particles smaller than 0.25&#xa0;mm, 52.60% ranging from 0.25 to 0.6&#xa0;mm, and 37.55% exceeding 0.6&#xa0;mm. A Plackett-Burman experimental design was employed to identify the sensitive parameters, including the static friction coefficient between river sand particles, the rolling friction coefficient of river sand and steel, and the restitution coefficient between river sands. The steepest ascent approach established the parameter ranges, and the Box-Behnken design (BBD) was used for optimization, resulting in the following parameter values: 0.533 for the static friction coefficient between river sand particles, 0.209 for the rolling friction coefficient of river sand and steel, and 0.213 for the coefficient of restitution between the river sand particles. A DEM model was developed based on these optimized parameters. Validation through experiments demonstrated that the simulation closely matched field test results, with errors in trench depth, surface width, and bottom width, all within a 9% margin of 8.8%, 4.8%, and 7.9%, respectively. These findings confirmed the accuracy and applicability of the DEM model for stimulating the interaction between river sand substrate and trenching equipment in Gobi Desert facility agriculture. This study provides a theoretical framework for optimizing trenching devices and rapidly constructing DEM models for river sand in sand farming systems.</p>

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Modeling of sand-cultivated substrate for Gobi facility agriculture and validation of trenching test

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月19日

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  • Yalong Song,
  • Jiahui Xu,
  • Shuo Zhang,
  • Jianfei Xing,
  • Long Wang,
  • Xufeng Wang,
  • Can Hu,
  • Wentao Li

摘要

Accurately simulating the interaction between trenching devices and river sand substrates is crucial for optimizing agricultural practices in Gobi Desert facility agriculture. This study calibrates Discrete Element Method (DEM) parameters for river sand substrate in the Gobi Desert of Northwest China, utilizing the Hertz-Mindlin contact model coupled with the Johnson-Kendall-Roberts (JKR) contact model in EDEM software. Key parameters, including stacking angle, particle size distribution, and morphology of the river sand, were measured using various methods and tools, such as an image acquisition system, vibration grading device, and stacking angle test apparatus. A model was developed to simulate the interaction between the river sand substrate and trenching device. The river sand matrix exhibited a stacking angle of 31.91°, with 9.85% of particles smaller than 0.25 mm, 52.60% ranging from 0.25 to 0.6 mm, and 37.55% exceeding 0.6 mm. A Plackett-Burman experimental design was employed to identify the sensitive parameters, including the static friction coefficient between river sand particles, the rolling friction coefficient of river sand and steel, and the restitution coefficient between river sands. The steepest ascent approach established the parameter ranges, and the Box-Behnken design (BBD) was used for optimization, resulting in the following parameter values: 0.533 for the static friction coefficient between river sand particles, 0.209 for the rolling friction coefficient of river sand and steel, and 0.213 for the coefficient of restitution between the river sand particles. A DEM model was developed based on these optimized parameters. Validation through experiments demonstrated that the simulation closely matched field test results, with errors in trench depth, surface width, and bottom width, all within a 9% margin of 8.8%, 4.8%, and 7.9%, respectively. These findings confirmed the accuracy and applicability of the DEM model for stimulating the interaction between river sand substrate and trenching equipment in Gobi Desert facility agriculture. This study provides a theoretical framework for optimizing trenching devices and rapidly constructing DEM models for river sand in sand farming systems.