# Study on Compaction Characteristics and Compaction Process of an Unsaturated Silt Based on PFC3D
## 3 Discrete Element Simulation of an Unsaturated Silt Static Triaxial Test
### Calibration of Microscopic Parameters  
In the process of discrete element simulation, the necessary test parameters are usually obtained through laboratory tests to provide a data basis for discrete element simulation. The test soil sample selected in this paper is an unsaturated silt in Pingyuan County, Dezhou Qihe River Section of the Beijing-Taizhou Expressway. Firstly, the basic physical properties of the soil sample are obtained through the basic geotechnical test, as shown in Table 1. Then, the unconsolidated undrained shear test is carried out on the TSZ-6A strain-controlled triaxial apparatus to obtain the stress-strain relationship curve of the sample under different confining pressure conditions, as shown in Figure 4. The water contents of the soil samples prepared by the triaxial test are 15%, 18%, and 21%, respectively, and the circumferential confining pressures are 100 KPa, 200 KPa, and 300 KPa, respectively.  
Based on laboratory test data, domestic and foreign scholars based the idea of inversion simulation [18] by changing the microscopic parameters of the model for a large number of static triaxial test discrete element simulations, the simulation results and laboratory test result comparative analysis through a trial and error method, to gradually determine the more reasonable discrete element model microscopic parameters. Figure 5a-d are the influence diagrams of the micro-parameters on the stress-strain curve when only the micro parameters, such as matrix suction, contact stiffness, friction coefficient, and damping coefficient, are changed. The indoor test data are the stress-strain curve obtained when the moisture content is 15% and the circumferential confining pressure is 200 kPa.  
The key to the success of the simulation is to determine the meso parameters of the discrete element model efficiently and accurately. It can be seen from Figure 5 that the matrix suction mainly affects the peak stress of the curve, which is consistent with the influence trend of the water content on the test results. The contact stiffness mainly affects the slope of the curve, which is related to the contact effect between the particles. The change in the friction coefficient has a certain influence on the peak stress, and its effect is smaller than that of the matrix suction. The change in the damping coefficient has little effect on the simulation results.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Particle Diameter/mm** & \
\begin{tabular}{c} **Relative Density** \\ **of Particles** \\ \end{tabular} & **Liquid Limit/\%** & **Plastic Limit/\%** &
\begin{tabular}{c} **Plasticity** \\ **Index/I\({}_{\text{p}}\)** \\ \end{tabular} & **Soil Properties** \\ \hline
0.002–2 & 2.70 & 32.3 & 23.6 & 8.7 & low liquid limit silt \\ \hline \hline \end{tabular}
\end{table}
Table 1: Basic physical properties of the soil samples.  
Figure 3: Discrete element model of the static triaxial test. (**a**) Rigid servo boundary. (**b**) Flexible servo boundary.  
Figure 4: Stress–strain relationship curves of samples under different confining pressures. (**a**) Water content at 15%. (**b**) Water content at 18%. (**c**) Water content at 21%.  
Figure 5: _Cont_.  
According to the influence of the microscopic parameters on the simulation results in Figure 5, a more reasonable microscopic parameter calibration step can be determined. The first parameter to be determined is the matrix suction, followed by the contact stiffness, and finally the damping coefficient and friction coefficient. Table 2 shows the calibrated Hill contact mesoscopic parameters concerning the indoor test results at 15% moisture content.