# Wind Tunnel Test on Windblown Sand Two-Phase Flow Characteristics in Arid Desert Regions
## 3 Experimental Results and Discussion
### Energy Distribution of Sand Particles in the Windblown Sand Flow Field  
The energy of sand particles in the windblown sand flow field, especially the kinetic energy of sand particles in the saltation layer, is an important parameter to study the characteristics of sand transport. It also determines the damage and destruction degree of the windblown sand to infrastructures and civil structures in the arid desert regions. However, there is little knowledge about the energy distribution of sand particles in the windblown sand flow field at present. To further understand the variation of particle energy with heights, we establish an energy distribution model of sand particles in the windblown sand flow field, according to the wind tunnel test data described above. To simplify the calculation for engineering applications, we assume that the speed of the sand particle is the same as the wind speed. The following formulas are used to calculate the energy of sand particles in the windblown sand flow field. \[\left\{ \begin{array}{c}E_{k}=\frac{1}{2}mU_{s}^{2}\\ E_{p}=mgz\\ E_{t}=E_{k}+E_{p}=\frac{1}{2}mU_{s}^{2}+mgz\end{array} \right. \tag{6}\]  
where \(E_{k}\), \(E_{p}\) and \(E_{t}\) are the kinetic energy, potential energy and total energy of sand particles in the windblown sand flow field, respectively, in J, \(m\) is the mass of sand particles, in kg, \(U_{s}\) and \(U_{a}\) are the sand particle speed and the wind speed in the windblown sand flow field, respectively, in m/s, in this study, \(U_{s}\approx U_{a}\), \(z\) is the height, in m, \(g\) is the gravitational acceleration, in m/s\({}^{2}\). We can obtain the kinetic energy and total energy of sand particles at different heights through Formula (6), as shown in Figure 14. The results show that the energy of sand particles is related to wind speeds, heights and particle sizes. For sands with all particle sizes and wind speeds, the kinetic energy and total energy exponentially decay with increasing heights. However, the research conducted by [PERSON] et al. showed that the variations in kinetic energy and total energy of sand particles with height accord with the pulse peak modified with power term law [PERSON] et al. (2018). In other words, the maximum kinetic energy value occurs at about 6 cm above the surface; below 6 cm, the kinetic energy value increases rapidly with increasing height, while above 6 cm, it decreases slowly. The main possible reasons for different results are as follows: (1) The energy distribution of sand particles is closely related to the concentration distribution of sand particles. However, the sand concentration profile in the wind tunnel test conducted by [PERSON] et al. deviates from our test results. (2) Based on the wind tunnel test data below 19 cm, [PERSON] et al. fitted the energy distribution model of sand particles but with fewer test data for height below 6 cm [PERSON] et al. (2018). While in this study, we fit the energy distribution model of sand particles based on the wind tunnel test data below 60 cm. As can be seen from Figure 14, the energy above 0.6 m is quite small and could be ignored, which is mainly because the sand concentration above 0.6 m is quite small. At the same indicated wind speed, the energy in the mixed sand, fine sand, and coarse sand are successively reduced, as their energy is positively correlated with their mass. For the same sand particles, because the kinetic energy is proportional to the square of the speed, the energy increases with the increasing wind speed. The variation of total energy with height is similar to that of kinetic energy with height and the proportion of potential energy to total energy is very small. Therefore, when studying the energy distribution of sand particles, we should mainly take into account the influence of kinetic energy of sand particles. Figure 14: _Cont._  
For sands with all particle sizes and wind speeds, the kinetic energy can be fitted with the least-square method.