Establishment and Calibration of Discrete Element Model of King Grass Stalk Based on Throwing Test

Huan, Xiaolong; Wang, Decheng; Ma, Wenfeng; Zhu, Lu; LI, Sibiao

doi:10.35633/inmateh-66-02

Cited by 8 publications

(7 citation statements)

References 14 publications

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“…Cutting is an important part of mechanized harvesting of KG, and the cutting device is the core working component of harvester. The existing KG cutting devices often refer to silage corn harvesters, which causes problems such as high cutting force and high power consumption [3]. Therefore, it is necessary to study the mechanical cutting characteristics of KG under different physical properties and mechanical parameters, to reduce cutting power consumption and improve mechanical reliability.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Cutting Characteristics of King Grass Stalk under Different Physical Properties and Mechanical Parameters

Huan,

Pang,

et al. 2024

Preprint

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To guide the design and optimization of King Grass (KG) harvesting machinery, this paper studied the cutting characteristics of KG stalks under different physical properties and mechanical parameters. A cutting device that can achieve different parameter adjustments was designed, and indoor cutting experiments were conducted. The results of the single factor experiment show that with the increase of moisture content and stalk height, the ultimate shear stress (USS) and unit-area cutting energy consumption (UCEC) gradually decrease. The optimal range of blade clearance for cutting KG stalks is 2.0-4.0 mm. The optimal value range for oblique cutting angle is 10 ° -40 °. The reasonable range of skew cutting angle is 10 °-20 °. The optimal range for sliding cutting angle is 20 ° - 40 °. The response surface methodology was used to conduct parameter optimization experiments. The regression models were established for various factors and the USS, as well as the UCEC. The optimal combination of cutting parameters has been determined. Under this parameter setting, the USS is 0.4 MPa and UCEC is 3.5 mJ/mm2. The average relative errors between the predicted and experimental values of USS and UCEC were 6.34% and 4.71%, respectively. This indicates that the model can correct reflect the mathematical relationship between various factors and USS and UCEC. This study provides theoretical support for the design of KG harvesting machinery.

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Section: Introductionmentioning

confidence: 99%

Experimental Study on the Cutting Characteristics of King Grass Stalk under Different Physical Properties and Mechanical Parameters

Huan,

Pang,

et al. 2024

Preprint

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show abstract

“…In recent years, with the advance of science and technology, the finite element method has been increasingly applied to the research field of agricultural science (Bai et al 2013). Foreign scholars have applied the finite element method to study the mechanical properties of agricultural materials and achieved many scientific results (Lu et al 2006;Onder et al 2008;Liu et al 2020;Huan et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Discrete elemental parameter calibration of stacking behavior of sugarcane tail leaf sieved material

Lei

Liu

Ren

et al. 2023

BioRes

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To improve the accuracy of discrete element simulation parameters of sugarcane tail-leaf (STL) feed during dust removal and crushing, this study used a combination of physical tests and EDEM software simulations to calibrate the discrete element simulation parameters of crumbs and dust in the feed. Taking the experimental physical stacking angle (SA) as the response value, the second-order regression models of SA and significant factors were established by Plackett-Burman test, steepest climb test, and Box-Behnken test. Variance analysis and interaction effect analysis were conducted. Taking the accumulation angle of 41.27° obtained by physical experiments as the target value, the significant parameters were optimized. The optimal combination of the following parameters was obtained: tail stem-dust static friction coefficient (SFC) of 0.46, tail leaf-dust coefficient of sliding friction (COSF) of 0.205, JKR surface energy of 0.26, and dust-steel collision recovery coefficient (CRC) of 0.338. Through software simulation verification, the average value was 40.81°, and the relative error of the SA with the physical experiment was 1.13%. The results showed that the calibrated parameters are real and reliable, which can provide a theoretical reference for the design optimization of the straw crushing device, feed processing device, and other related components.

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“…Mu et al, (2021), studied the discrete element model parameters of the stem and leaf of smashed sweet potatoes by combining physical experiments and virtual calibration. Huan et al, (2022), measured the intrinsic parameters of king grass stalks by physical experiments, using the index of AoR, the discrete element parameters of king grass stalks were calibrated using response surface optimization method, and the calibration results were verified by throwing trajectory tests; Wang et al, (2021), conducted parameter calibration tests using straw powder as homogeneous material in the mechanical properties test of corn straw powder. However, there is no study on calibration for discrete element parameterization of the crushed corn stalk (CCS).…”

Section: Introductionmentioning

confidence: 99%

Parameters Calibration of Discrete Element Model for Crushed Corn Stalks

Chen

Gao

et al. 2023

INMATEH

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For the problem of lacking reliable parameters during simulation analysis of the crushed corn stalk (CCS) micro-comminution process with gas-solid coupling method, the simulation parameters are calibrated using a combination of physical measurements and virtual experiments with CCS as the research object. The intrinsic parameters of CCS are obtained by physical experiment, and the stacking test is carried out by cylinder lifting method, and the actual angle of repose(AoR) is obtained as 44.12° by fitting the boundary line with Matlab software; the discrete element model of CCS is established, and the virtual stacking test is carried out by EDEM software; CCS-CCS dynamic friction coefficient, CCS-CCS static friction coefficient and JKR (Johnson-Kendall-Roberts) surface energy are identified as the parameters with significant effects on the AoR by Plackett-Burman test; the steepest climb test is leveraged to determine the center of response surface analysis; the quadratic polynomial regression model of the simulation parameters and the AoR is established by the Box-Behnken test using the AoR as the evaluation index, and the optimal combination of the significant parameters are obtained as follows: the CCS-CCS dynamic friction coefficient is 0.55, the CCS-CCS static friction coefficient is 0.14, and the JKR surface energy is 0.12; the AoR verification test is conducted based on the optimal combination of the significant parameters The results show that the AoR of the CCS is 43.82°, which is 0.68% of the actual AoR, indicating that the parameter combination is reliable. The data obtained in this research can provide corresponding simulation parameters for CCS discrete element simulation and the development of straw micro-crushing equipment.

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Establishment and Calibration of Discrete Element Model of King Grass Stalk Based on Throwing Test

Cited by 8 publications

References 14 publications

Experimental Study on the Cutting Characteristics of King Grass Stalk under Different Physical Properties and Mechanical Parameters

Experimental Study on the Cutting Characteristics of King Grass Stalk under Different Physical Properties and Mechanical Parameters

Discrete elemental parameter calibration of stacking behavior of sugarcane tail leaf sieved material

Parameters Calibration of Discrete Element Model for Crushed Corn Stalks

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