Determination and interpretation of parameters of double-bud sugarcane model based on discrete element

Zhong, Jia-Qin; Tao, Li-Min; Li, Shangping; Zhang, Biao; Wang, Jingyun; He, Yong-Ling

doi:10.1016/j.compag.2022.107428

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…The flow and frictional characteristics of fertilizer particles, which are connected to the physical and mechanical characteristics of fertilizer particles and contact materials, are reflected in the resting angle [14]. In this study, parameters of the discrete element of compound fertilizer are calibrated using a mix of physical and simulation experiments [15][16].…”

Section: Methodsmentioning

confidence: 99%

Calibration and test of discrete element model (DEM) for compound fertilizer particles in mechanized variable-rate application

Yuan

Wang³

et al. 2023

Preprint

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Background In order to obtain accurate discrete element simulation model (DEM) parameters of compound fertilizer and solve the problem of measuring parameters of contact mechanical properties of fertilizer particles, this study measured the intrinsic parameters and contact parameters of compound fertilizer particles through physical tests and established a simulation model that corresponds with the actual to solve the problem of challenging measurement of contact parameters of compound fertilizer particle. Results By using the Blackett-Burman test, the parameters that had a significant impact on the compound fertilizer's resting angle were determined to be the fertilizer-fertilizer collision recovery coefficient, fertilizer-fertilizer rolling friction coefficient, and fertilizer-steel static friction coefficient. Utilizing the steepest ascent test, the ideal value intervals for the three key parameters were identified. The Box-Burman response surface analysis was used to establish and optimize the regression model of the rest angle and significant parameters. With the actual rest angle as the target value, the best combination of significance parameters was found, which was used for the simulation verification test. The simulated rest angle is 20.61°, whereas the real rest angle was 19.95°, with a relative error of 3.31%. Conclusion The results demonstrate that the calibration parameters are essentially accurate representations of the real characteristics, which can serve as a reference point for simulation research and optimization design of variable fertilizer spreader.

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Section: Methodsmentioning

confidence: 99%

Calibration and test of discrete element model (DEM) for compound fertilizer particles in mechanized variable-rate application

Yuan

Wang³

et al. 2023

Preprint

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“…The modification results of characteristic dimensions of corn seeds are shown in Table 2. The static friction coefficient is measured using the inclined plane sliding method [24,25], and the measurement principle is shown in Figure 5. Place the corn seed on a test plate in a horizontal position, slowly increase the angle between the test plate and the horizontal plane and record the angle when the corn seed appears to slide.…”

Section: Determination Of Characteristic Dimensions Of Corn Seedsmentioning

confidence: 99%

Calibration of Collision Recovery Coefficient of Corn Seeds Based on High-Speed Photography and Sound Waveform Analysis

Li,

Zhang,

et al. 2023

Agriculture

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Compared with the movement of corn seeds in the sowing machine, the movement in the threshing machine is more intense. The collision between corn seeds and threshing parts and other corn seeds will not only change the movement path of corn seeds in the threshing clearance but also cause damage to corn seeds. Therefore, when using discrete element simulation technology to optimize the critical components of corn threshing machinery, it is necessary to measure corn seeds’ accurate collision recovery coefficient. However, when measuring the collision recovery coefficient between corn seeds, there will be multi-point collisions between corn seeds, affecting the measurement results’ accuracy. In order to solve this problem, this study combined high-speed photography and the sound waveform of corn seed collision to eliminate the interference of the multi-point collision phenomenon and improve the accuracy of measurement results. According to the above test method, the contact parameters of corn seeds were measured. Finally, the corn–corn rolling friction coefficient and corn–PMMA rolling friction coefficient were 0.0784 and 0.0934, respectively. The corn–corn static friction coefficient was 0.32, and the corn–PMMA static friction coefficient was 0.445. The corn–corn collision recovery and corn–PMMA collision recovery coefficients were 0.28 and 0.62, respectively. After that, the method’s reliability and the measurement results’ accuracy were verified by the plane collision test and repose angle test.

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“…The coefficient of rolling friction of particles is a basic and computationally significant property for simulation [15]. The accuracy of discrete element simulation depends on the input parameters and the shape model [16]. Particle shapes are usually made by combining spherical particles, which is referred to as sphere aggregation [17,18].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Typically Shaped Corn Seeds and Calibration of the Coefficient of Rolling Friction

et al. 2023

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The shape of corn seeds not being spherical affects their mobility. This study focuses on modeling the typically shaped corn seeds and calibrating the coefficient of rolling friction for different shape types to improve simulation reliability. By analyzing the corn seed shape characteristics and size statistics, this study establishes a classification system that enables the determination of the average value and quantity of different types of corn seed using the spherical granule cluster method. The discrete element method is used to model simplified corn models, and contact parameters are validated through two types of repose angle and a seed metering experiment. In the collapse repose experiment, the relative error between the simulation and the experiment was only 0.72%, while the relative error in another repose experiment was 0.2%. The verification experiment for the metering of seeds showed that the relative error between the simulation and the experiment was below 15% at both low and high speeds, and the multi-grain rate error was less than 10%. This shows that the method proposed in this paper is somewhat accurate.

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Determination and interpretation of parameters of double-bud sugarcane model based on discrete element

Cited by 7 publications

References 15 publications

Calibration and test of discrete element model (DEM) for compound fertilizer particles in mechanized variable-rate application

Calibration and test of discrete element model (DEM) for compound fertilizer particles in mechanized variable-rate application

Calibration of Collision Recovery Coefficient of Corn Seeds Based on High-Speed Photography and Sound Waveform Analysis

Modeling of Typically Shaped Corn Seeds and Calibration of the Coefficient of Rolling Friction

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