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Investigating the interactions of granular fertilizers with various types of equipment is an essential part of agricultural research. A numerical technique simulating the mechanical behavior of granular assemblies has the advantage of data trackings, such as the trajectories, velocities, and transient forces of the particles at any stage of the test. The interaction parameters were calibrated to simulate responses of granular fertilizers in EDEM, a discrete element method (DEM) software. Without a proper calibration of the interaction parameters between the granular fertilizers and various materials, the simulations may not represent the real behavior of the granular fertilizers. Therefore, in this study, a strategy is presented to identify and select a set of DEM input parameters of granular fertilizers using the central composite design (CCD) to establish the nonlinear relationship between the dynamic macroscopic granular fertilizer properties and the DEM parameters. The determined interaction properties can be used to simulate granular fertilizers in EDEM.
Sugirbay Adilet; Jian Zhao; Nukeshev Sayakhat; Jun Chen; Zagainov Nikolay; Lingxin Bu; Zhanar Sugirbayeva; Guangrui Hu; Muratkhan Marat; Zhiwei Wang. Calibration Strategy to Determine the Interaction Properties of Fertilizer Particles Using Two Laboratory Tests and DEM. Agriculture 2021, 11, 592 .
AMA StyleSugirbay Adilet, Jian Zhao, Nukeshev Sayakhat, Jun Chen, Zagainov Nikolay, Lingxin Bu, Zhanar Sugirbayeva, Guangrui Hu, Muratkhan Marat, Zhiwei Wang. Calibration Strategy to Determine the Interaction Properties of Fertilizer Particles Using Two Laboratory Tests and DEM. Agriculture. 2021; 11 (7):592.
Chicago/Turabian StyleSugirbay Adilet; Jian Zhao; Nukeshev Sayakhat; Jun Chen; Zagainov Nikolay; Lingxin Bu; Zhanar Sugirbayeva; Guangrui Hu; Muratkhan Marat; Zhiwei Wang. 2021. "Calibration Strategy to Determine the Interaction Properties of Fertilizer Particles Using Two Laboratory Tests and DEM." Agriculture 11, no. 7: 592.
With the increase of labor cost and the development of agricultural mechanization, standardized orchards suitable for autonomous operations of agricultural machinery will be a future development trend of the fruit-planting industry. For field-planting processes of standardized orchards, autonomous navigation of orchard vehicles in complex environments is the foundation of mechanized and intelligent field operations. In order to realize autonomous driving and path-tracking of vehicles in complex standardized orchards that involve much noise and interference between rows of fruit trees, an automatic navigation system was designed for orchard vehicles, based on 2D lasers. First, considering the agronomic requirements for orchard planting such as plant spacing, row spacing and trunk diameter, different filtering thresholds were established to eliminate discrete points of 2D laser point cloud data effectively. Euclidean clustering algorithm and the important geometric theorems of three points collinearity was used to extract the central feature points of the trunk, as the same time, navigation path was fitted based on the least square method. Secondly, an automatic navigation control algorithm was designed, and the fuzzy control was used to realize the dynamic adjustment of the apparent distance of the pure pursuit model. Finally, the reliability of the proposed approach was verified by simulation using MATLAB/Simulink, and field tests were carried out based on electric agricultural vehicle. Experimental results show that the method proposed in this study can effectively improve the precision of automatic navigation in complex orchard environment and realize the autonomous operation of orchard vehicles.
Shuo Zhang; Chengyang Guo; Zening Gao; Adilet Sugirbay; Jun Chen; Yu Chen. Research on 2D Laser Automatic Navigation Control for Standardized Orchard. Applied Sciences 2020, 10, 2763 .
AMA StyleShuo Zhang, Chengyang Guo, Zening Gao, Adilet Sugirbay, Jun Chen, Yu Chen. Research on 2D Laser Automatic Navigation Control for Standardized Orchard. Applied Sciences. 2020; 10 (8):2763.
Chicago/Turabian StyleShuo Zhang; Chengyang Guo; Zening Gao; Adilet Sugirbay; Jun Chen; Yu Chen. 2020. "Research on 2D Laser Automatic Navigation Control for Standardized Orchard." Applied Sciences 10, no. 8: 2763.