Numerical Simulation and Analysis of the Impurity Removal Process of a Sugarcane Chopper Harvester Based on a CFD–DEM Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Structure and Working Principle of the Extractor Test Bench
2.2. Simulation of the Airflow Field of the Extractor
2.2.1. Model and Meshing
2.2.2. Verification of Mesh Independence
2.2.3. Boundary Conditions and Data Calculation
2.2.4. Validation of Airflow Simulation Model
2.3. Material Discrete Element Simulation Model Construction and Parameter Setting
2.3.1. Determination of Basic Physical Parameters of Billets and Leaves
2.3.2. Discrete Meta-Simulation Model Construction for Billets and Leaves
2.3.3. Discrete Element Simulation Parameter Setting
2.4. Modelling of Gas–Solid Coupling for Extractor
2.4.1. Coupling Parameter Setting
2.4.2. Validation of the Gas–Solid Coupling Model
2.4.3. Model Validation Results
3. Results and Analysis
3.1. Simulation Analysis of the Airflow Field of the Extractor
3.2. Analysis of Gas–Solid Coupling Simulation Results
3.3. Analysis of the Relationship among Parameters
3.3.1. Simulation Test Design
3.3.2. Simulation Test Results
4. Discussion
5. Conclusions
- (1)
- An airflow field model of the extractor is established. Simulation shows fan speed variation only affects values not distribution. A fan speed increase raises velocity and pressure. Near the fan blades, velocity and pressure values are higher. The area beneath the fan is the main separation zone.
- (2)
- The gas–solid coupling simulation model of the extractor was constructed, and the impurity removal process was simulated. The movement state of sugarcane material in the extractor at different times was analyzed, which lays a foundation for further exploring the impurity removal mechanism.
- (3)
- A simulation test was conducted to address the issues of the high-power consumption and high impurity rate of the extractor. The relationship between the impurity rate and the fan speed, leaf–stalk ratio, and feed rate was determined.
- (4)
- The parameter combinations under different impurity rates were obtained. The fan speed was adjusted according to the feed rate and leaf–stalk ratio, and these models can guide the intelligent harvesting of sugarcane in the future.
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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Parameters | Value |
---|---|
Impeller diameter/mm | 954 |
Impeller width/mm | 124 |
Number of leaves | 3 |
Blade installation angle/° | 38.04 |
Incoming trending area/m2 | 0.386 |
The trending area/m2 | 0.344 |
Speed range/(rev/min) | 0–1200 |
Material | Property | Mean | Standard Deviation |
---|---|---|---|
Billet | Geometric dimensions/ (L × Φ)/mm × mm | 250.3 × 32.04 | 3.20 × 2.41 |
Density/g·cm−3 | 1.03 | 0.03 | |
Moisture content/% | 72.50 | 5.01 | |
Suspension speed/(m/s) | 9.92 | 0.473 | |
Leaf | Geometric dimensions/ (L × W × H) /mm × mm × mm | 250.30 × 36.89 × 0.40 | 10.23 × 12.66 × 1.20 |
Density/g·cm−3 | 0.38 | 0.07 | |
Moisture content/% | 10.33 | 0.97 | |
Suspension speed/(m/s) | 3.655 | 0.34 | |
Whole cane | Leaf–stalk ratio/% | 25 | 3.00 |
(a) | |||
Material | Poisson’s Ratio | Shear Modulus /MPa | Density /g·cm−3 |
Billet | 0.35 | 10.8×104 | 1.03 |
Leaf | 0.30 | 300 | 0.38 |
Steel | 0.30 | 7.9×104 | 7.85 |
(b) | |||
Material | Recovery Coefficient | Static Friction Coefficient | Dynamic Friction Coefficient |
Billet–billet | 0.45 | 0.53 | 0.04 |
Billet–steel | 0.45 | 0.35 | 0.03 |
Leaf–leaf | 0.002 | 0.21 | 0.05 |
Leaf–steel | 0.003 | 0.3 | 0.03 |
Levels | Test Factors | ||
---|---|---|---|
A/(rev/min) | B/(kg/s) | C/% | |
−1 | 700 | 10 | 20 |
0 | 900 | 15 | 25 |
1 | 1100 | 20 | 30 |
NO. | Test Factors | Test Indicators | ||
---|---|---|---|---|
A/(rev/min) | B/(kg/s) | C/% | Y/% | |
1 | −1 | −1 | −1 | 9.2 |
2 | −1 | −1 | 0 | 9.6 |
3 | −1 | −1 | 1 | 10 |
4 | −1 | 0 | −1 | 11.1 |
5 | −1 | 0 | 0 | 13.3 |
6 | −1 | 0 | 1 | 12.5 |
7 | −1 | 1 | −1 | 13.2 |
8 | −1 | 1 | 0 | 13.4 |
9 | −1 | 1 | 1 | 12.7 |
10 | 0 | −1 | −1 | 7.6 |
11 | 0 | −1 | 0 | 8.4 |
12 | 0 | −1 | 1 | 7.5 |
13 | 0 | 0 | −1 | 9.3 |
14 | 0 | 0 | 0 | 10.4 |
15 | 0 | 0 | 1 | 8.9 |
16 | 0 | 1 | −1 | 10.3 |
17 | 0 | 1 | 0 | 12.4 |
18 | 0 | 1 | 1 | 11.5 |
19 | 1 | −1 | −1 | 5.3 |
20 | 1 | −1 | 0 | 4.1 |
21 | 1 | −1 | 1 | 3.7 |
22 | 1 | 0 | −1 | 6.3 |
23 | 1 | 0 | 0 | 6.5 |
24 | 1 | 0 | 1 | 5.5 |
25 | 1 | 1 | −1 | 6.7 |
26 | 1 | 1 | 0 | 7.1 |
27 | 1 | 1 | 1 | 6.7 |
Source of Variance | Sum of Squares | Degrees of Freedom | Mean Square | F | p |
---|---|---|---|---|---|
Model | 213.16 | 9 | 23.68 | 67.34 | <0.0001 ** |
A | 156.64 | 1 | 156.64 | 445.38 | <0.0001 ** |
B | 45.44 | 1 | 45.44 | 129.2 | <0.0001 ** |
C | 0 | 1 | 0 | 0 | 1 |
AB | 0.8008 | 1 | 0.8008 | 2.28 | 0.1497 |
AC | 1.4 | 1 | 1.4 | 3.98 | 0.0622 |
BC | 0.2133 | 1 | 0.2133 | 0.6066 | 0.4468 |
A2 | 4.56 | 1 | 4.56 | 12.98 | 0.0022 ** |
B2 | 1.25 | 1 | 1.25 | 3.54 | 0.0771 |
C2 | 2.85 | 1 | 2.85 | 8.1 | 0.0112 * |
Residual | 5.98 | 17 | 0.3517 | − | − |
Sum | 219.14 | 26 | − | − | − |
R2 = 0.9727 | R2adj = 0.9583 | CV = 6.58% | Adequate Precision = 28.3766 |
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Wu, T.; Li, F.; Liu, Q.; Ren, J.; Huang, J.; Qin, Z. Numerical Simulation and Analysis of the Impurity Removal Process of a Sugarcane Chopper Harvester Based on a CFD–DEM Model. Agriculture 2024, 14, 1392. https://doi.org/10.3390/agriculture14081392
Wu T, Li F, Liu Q, Ren J, Huang J, Qin Z. Numerical Simulation and Analysis of the Impurity Removal Process of a Sugarcane Chopper Harvester Based on a CFD–DEM Model. Agriculture. 2024; 14(8):1392. https://doi.org/10.3390/agriculture14081392
Chicago/Turabian StyleWu, Tao, Fatang Li, Qingting Liu, Jiahui Ren, Jibai Huang, and Zhanji Qin. 2024. "Numerical Simulation and Analysis of the Impurity Removal Process of a Sugarcane Chopper Harvester Based on a CFD–DEM Model" Agriculture 14, no. 8: 1392. https://doi.org/10.3390/agriculture14081392