Analysis of Adhesion between Wet Clay Soil and Rotary Tillage Part in Paddy Field Based on Discrete Element Method

Cheng, Jian; Zheng, Kan; Xia, Junfang; Liu, Guoyang; Liu, Jiang; Liang, Dong

doi:10.3390/pr9050845

Cited by 12 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…5.6 it follows that a 10% decrease in water content leads to a 0.35 MPa decrease in soil compaction. This can be explained by the increasing fragility of loamy soil due to a decrease in the adhesion of the structural bonds, which was confirmed by previous research (Terfaya et al, 2018;Cheng et al, 2021).…”

Section: Resultssupporting

confidence: 83%

“…With an increase in water content to 30%, a 0.55 MPa decrease in compaction was observed, which can be explained by a decrease in adhesive bonds due to the substitution of inter-structural bonds with capillary ones. The substitution leads to a decrease in the force of internal friction when shear stresses are applied, as confirmed by Cheng et al (2021) and Nawaz et al (2013). To sum up, the study revealed, that soil, as a porous natural body, has a bearing capacity to support plant life.…”

Section: Resultsmentioning

confidence: 54%

See 1 more Smart Citation

On-Stream Soil Density Measuring

KRAVCHUK,

IVANIUTA,

BRATISHKO

et al. 2023

INMATEH

View full text Add to dashboard Cite

The article is focused on the determination of the nonlinear relationships between soil compaction, density, and water content. It was found that these properties can be described by the second-order models and used for improving devices for the on-stream soil density measuring. The models for determining the density of loamy soil (at a water content of 20%) in the range from 0.9 to 1.6 g/cm3 with an extremum of 1.35 g/cm3 were improved. A device for the on-stream soil density measuring is proposed. The device operates within the soil compaction range from 0.3 to 1.2 MPa and water content from 10 to 30% at the angle of inclination of the kinematic link  from 15 to 40 degrees. The obtained results can be used in the adaptation of the proposed device for use in precision agriculture.

show abstract

Section: Resultssupporting

confidence: 83%

Section: Resultsmentioning

confidence: 54%

On-Stream Soil Density Measuring

KRAVCHUK,

IVANIUTA,

BRATISHKO

et al. 2023

INMATEH

View full text Add to dashboard Cite

show abstract

“…By studying the interaction between the rotary blade and the soil, valuable insights can be gained to inform blade design. In a study conducted by Cheng et al [8], the rotary tillage process of a rotary tiller blade was simulated using the discrete element method. The findings indicated that the soil adhesion force primarily accumulates on the oblique long part of the rotary tillage blade.…”

Section: Introductionmentioning

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

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.

show abstract

“…Some researchers have explored altering particle trajectories by designing blades of different shapes to influence the movement of soil particles along predetermined paths [12][13][14][15]. Others have investigated the cutting and scattering processes of blades to uncover underlying patterns of particle motion [16][17][18][19][20]. Additionally, computer simulation techniques have been employed by some scholars to establish numerical models simulating blade operation processes [21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Simulation Analysis and Optimization Design of Paddy Field Mud Spreader Blades for Uniform Dispersion

Ren,

Chen,

Bao

et al. 2024

Agriculture

View full text Add to dashboard Cite

To improve the distribution of mud particles collected in the tray during the operation of paddy field mud spreader blades, the optimal combination of parameters for the blades that results in the best uniformity of mud dispersion needs to be identified. In this study, a thorough force analysis was conducted on the spreading process, and computational equations were formulated to describe the motion of mud particles. By utilizing the discrete element simulation technique, a simulation model was developed to accurately represent the intricate interaction between the blades and mud particles. Through the single-factor simulation experiments, the ranges of key parameters such as the rotation radius, bending angle, sub-blade tilt angle, forward velocity, and rotational speed of the blade were determined. A secondary orthogonal rotational combination design was employed to establish a regression prediction model between the non-uniformity of mud dispersion and the key blade parameters. Subsequently, a multivariate single-objective optimization method was used to develop an optimization model for the non-uniformity of mud dispersion. The results indicate that the hierarchical order of factors influencing the non-uniformity of mud dispersion is as follows: rotation radius > rotation speed > bending angle > forward velocity > sub-blade tilt angle. To achieve a minimum spreading non-uniformity of 29.63%, a specific configuration is required, which includes a blade rotation radius of 188 mm, a bending angle of 121°, a sub-blade tilt angle of 30°, a forward velocity of 400 mm/s, and a rotation speed of 191 r/min. Finally, the accuracy of the optimization results was verified by means of bench tests. The research results provide a crucial reference for enhancing the uniformity of mud dispersion in paddy field mud spreader blades.

show abstract

Analysis of Adhesion between Wet Clay Soil and Rotary Tillage Part in Paddy Field Based on Discrete Element Method

Cited by 12 publications

References 38 publications

On-Stream Soil Density Measuring

On-Stream Soil Density Measuring

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

Simulation Analysis and Optimization Design of Paddy Field Mud Spreader Blades for Uniform Dispersion

Contact Info

Product

Resources

About