Calibration of parameters for discrete element simulation model for alfalfa with different moisture contents based on angle of repose test

Wang, Haoyi; Wu, P.D.; He, Hongkai; Ma, Yanhua; Bu, Ku; Xue, Jing

doi:10.15376/biores.17.1.1467-1484

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…The index of the test results was the ratio of the difference between the measured repose angle and the simulated repose angle to the measured repose angle, which was calculated as shown in Equation ( 1). Taking the above parameters as influencing factors, a second-order regression model of the repose angle and significance parameters was obtained through the Plackett-Burman test, steepest climb test, and Box-Behnken test design, and finally, the best combination of the significance parameters was determined [18,19].…”

Section: Methodsmentioning

confidence: 99%

Calibration and Verification of Discrete Element Parameters of Surface Soil in Camellia Oleifera Forest

Ma,

You,

Yang

et al. 2024

Agronomy

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To analyze the interaction between the surface soil and the soil-contacting component (65 Mn) in the camellia oleifera forest planting area in Changsha City, Hunan, China, in this study, we conducted discrete element calibration using physical and simulation tests. The chosen contact model was Hertz–Mindlin with JKR cohesion, with the soil repose angle as the response variable. The repose angle of the soil was determined to be 36.03° based on the physical tests. The significant influencing factors of the repose angle determined based on the Plackett–Burman test were the soil–soil recovery coefficient, soil–soil rolling friction coefficient, soil-65 Mn static friction coefficient, and surface energy of soil for the JKR model. A regression model for the repose angle was developed using the Box–Behnken response surface optimization method to identify the best parameter combination. The optimal parameter combination for the JKR model was determined as follows: surface energy of soil: 0.400, soil–soil rolling friction coefficient: 0.040, soil-65 Mn static friction coefficient: 0.404, and soil–soil recovery coefficient: 0.522. The calibrated discrete element parameters were validated through experiments on the repose angle and steel rod insertion. The results indicated that the relative errors obtained from the two verification methods were 2.44% and 1.71%, respectively. This research offers fundamental insights for understanding the interaction between soil and soil-contacting components and optimizing their design.

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Section: Methodsmentioning

confidence: 99%

Calibration and Verification of Discrete Element Parameters of Surface Soil in Camellia Oleifera Forest

Ma,

You,

Yang

et al. 2024

Agronomy

View full text Add to dashboard Cite

show abstract

“…The contact parameters were calibrated by combining the two-level factor experiment and the response surface experiment. Wang et al (2022) used the Plackett-Burman and the Box-Behnken Design experiments to calibrate the parameters of alfalfa based on the angle of repose. Zhang et al (2020) calibrated the key parameters of the corn stalks crushing process based on the Hertz-Mindlin with bonding contact model.…”

Section: Introductionmentioning

confidence: 99%

Discrete element method for simulation and calibration of cotton stalk contact parameters

YongTao

Peng

et al. 2022

BioRes

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To improve the accuracy of the discrete element research, physical and simulation experiments were used to calibrate the cotton stalk contact parameters. Based on the stalk-stalk and stalk-steel contact mechanics, the parameters were measured in physical experiments, and the discrete element simulation software was used to build the stalk model. In the simulation process, the Plackett-Burman experiment was used to screen three significant factors from six initial factors. The steepest Plackett-Burman experiment was used to determine the optimal interval of the significant factors. A second-order regression model of the significant factors and the angle of repose was established according to the Central Composite design experiment. The best parameter combination of the significant factors was then obtained: the coefficient of static friction on stalk-steel contact was 0.31, the coefficient of static friction on stalk-stalk contact was 0.62, and the coefficient of rolling friction on stalk-stalk contact was 0.02. The relative error between the physical angle of repose and the simulated angle was 3.27%, indicating that it is feasible to apply the simulation experiment instead of the physical one. It offers insights into cotton stalk contact parameter settings and film-stalk separation in the simulation.

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“…Furthermore, the influence of the assisted-vibration frequency, moisture content, and particle size of the alfalfa on heat transfer should be studied. These three factors affect the alfalfa compression (Wang et al 2022). In this paper, the temperature for compressing the alfalfa with assisted vibration was studied to reveal the mechanism of vibration-assisted compression and to explain the effect of vibration frequency, moisture content, and particle size on temperature variation during alfalfa compression.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on heat transfer of alfalfa during the vibration-assisted compression

Wang

et al. 2022

BioRes

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Compression alfalfa into briquettes is an effective way to solve the problem of storage and transportation. In the process of compression, heat is generated, which raises the temperature in the material. The appropriate temperature can improve the quality of alfalfa briquettes. In this paper, the effect of assisted vibration frequency, moisture content, and particle size on the compression temperature were tested. The results showed that when the vibration was applied, the material particle temperature in the mold rose significantly, and the core particle temperature rose faster than the edge temperature. The vibration frequency was the most significant factor affecting heat transfer in the three studied factors. When the moisture content and particle size were constant, the heat transfer effect increased first and then decreased with the vibration frequency, and it had an optimal value at 17 Hz. When the vibration frequency and particle size were constant, the heat transfer effect increased first and then decreased with the moisture content. It had an optimal value of 20%. The experimental results explained the effect of vibration frequency, moisture content, and particle size on temperature variation during alfalfa compression and provided a basis for reasonable process parameters.

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Calibration of parameters for discrete element simulation model for alfalfa with different moisture contents based on angle of repose test

Cited by 7 publications

References 8 publications

Calibration and Verification of Discrete Element Parameters of Surface Soil in Camellia Oleifera Forest

Calibration and Verification of Discrete Element Parameters of Surface Soil in Camellia Oleifera Forest

Discrete element method for simulation and calibration of cotton stalk contact parameters

Experimental study on heat transfer of alfalfa during the vibration-assisted compression

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