Simulation Analysis of Cement-Stabilized Macadam Compaction Processing Based on the Discrete Element Method
Abstract
:1. Introduction
2. Raw Materials and Experimental Methods
2.1. Raw Material and Test Gradation
2.2. Experimental Scheme
2.2.1. Experimental Scheme for Compaction Molding
2.2.2. Experimental Scheme for Vibration Molding
3. Discrete Element Model Building and Verification
3.1. Basic Theory of Discrete Elements
3.2. Modeling Process
3.3. Molding Simulation Process
3.3.1. Experimental Process of Compaction Molding
- (1)
- A ramming hammer was generated directly above the specimen. To save computing time, the initial velocity of the hammer replaced free-fall motion at a fixed height while ensuring constant kinetic energy and momentum.
- (2)
- After each ramming, specimen porosity, hammer displacement time range and other key parameters were monitored. When the hammer speed dropped to 0, the basically unchanged amount of sink was rammed to terminate the compaction test, and the hammer model was removed.
- (3)
- When the next compaction test was performed, the specimen after the last compaction test was called, the hammer was regenerated, and given its initial speed.
- (4)
- Calculation results were exported and analyzed.
3.3.2. Vibration Molding Process
3.4. Experimental Validation of Numerical Model
4. Results and Discussion
4.1. Specimen Porosity Variation
4.2. Specimen Force Chain Variation
4.3. Variation in Average Coordination Number
4.4. Displacement Variation in Specimen Particles
5. Conclusions
- (1)
- The DEM numerical simulation of the cement-stabilized macadam forming test effectively simulated CSM’s porosity and specimen height variation trends during the forming process.
- (2)
- The specimen height and porosity changes in the compaction molding process illustrate that the first 10 compactions had the most significant influence on the compaction effect. During the first 10 compactions specimen height and porosity fell fastest, accounting for approximately 80% of the compaction effect, indicating that real-world construction must pay attention to the initial compaction link.
- (3)
- The discrete element method simulation can explain the CSM forming process from the perspective of particle motion and interaction. The DEM simulation illustrates that during the initial compaction molding action, impact force was transmitted slowly from top to bottom and the compaction load’s transmission speed increased as the mixture was continuously squeezed and compacted. During its initial state, the vibration molding simulation’s force showed a bottom-to-top transmission, presented a trend of transfer from the top and bottom ends towards the middle at approximately 30 s, and finally reached an equilibrium state.
- (4)
- Particle distribution in the vibration molding specimen was more uniform, whereas particles in the compaction molding specimens showed a dense distribution at the top of the specimen and sparse distribution at the bottom. The porosity of the vibration molding specimen was 2.5% lower than that of the compaction molding specimen, which showed that vibration molding was more effective.
- (5)
- In the simulation experiments, the average coordination number of particles in the vibration molding specimen was 2.3% higher than that of the compaction molding specimen, implying that the vibration forming specimen had higher load-bearing capacity and stability.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Index | Fineness (%) | Initial Setting Time (min) | Final Setting Time (min) | Stability | 28 d Strength (MPa) | |
---|---|---|---|---|---|---|
Compression | Flexural | |||||
Experimental results | 0.63 | 245 | 365 | eligible | 48.6 | 10.4 |
Specification requirements | ≤10 | ≥180 | ≥360 | ≥42.5 | ≥6.5 |
Performance Indicators | Test Results | Technical Requirements (High Speed and Primary Roads) | |
---|---|---|---|
Coarse aggregates | Crushing value (%) | 18.8 | ≤22 |
Content of needle-like particles (%) | 11.5 | ≤18 | |
Dust content below 0.075 mm (%) | 0.5 | ≤1.2 | |
Soft stone content (%) | 1.1 | ≤3 | |
Fine aggregates | Particle analysis | Qualified | Meet grading requirements |
Plasticity Index | 12 | ≤17 | |
Organic matter content (%) | 0.6 | ≤2 | |
Sulfate content (%) | 0.12 | ≤0.25 |
Mass Passing Percentage of Each SIEVE Aperture (%) | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Sieve size | 0.075 | 0.15 | 0.3 | 0.6 | 1.18 | 2.36 | 4.75 | 9.5 | 13.2 | 16 | 19 | 26.5 |
Gradation | 3.6 | 6.8 | 10 | 14.3 | 18.3 | 23.6 | 36.1 | 59.9 | 68.3 | 75.3 | 83.5 | 100.0 |
Operating Frequency (HZ) | Nominal Amplitude (mm) | Working Mass (Kg) | ||
---|---|---|---|---|
30 | 1.2 | Upper system | Lower system | Total mass |
180 | 120 | 300 |
Molding Method | Upper Porosity (%) | Lower Porosity (%) |
---|---|---|
Compaction molding | 8.23 | 8.36 |
Vibration molding | 8.08 | 8.11 |
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Liang, C.; Zhang, H.; Liu, F.; Yan, X.; Bi, H. Simulation Analysis of Cement-Stabilized Macadam Compaction Processing Based on the Discrete Element Method. Appl. Sci. 2022, 12, 8505. https://doi.org/10.3390/app12178505
Liang C, Zhang H, Liu F, Yan X, Bi H. Simulation Analysis of Cement-Stabilized Macadam Compaction Processing Based on the Discrete Element Method. Applied Sciences. 2022; 12(17):8505. https://doi.org/10.3390/app12178505
Chicago/Turabian StyleLiang, Chunyu, Hao Zhang, Feng Liu, Xili Yan, and Haipeng Bi. 2022. "Simulation Analysis of Cement-Stabilized Macadam Compaction Processing Based on the Discrete Element Method" Applied Sciences 12, no. 17: 8505. https://doi.org/10.3390/app12178505
APA StyleLiang, C., Zhang, H., Liu, F., Yan, X., & Bi, H. (2022). Simulation Analysis of Cement-Stabilized Macadam Compaction Processing Based on the Discrete Element Method. Applied Sciences, 12(17), 8505. https://doi.org/10.3390/app12178505