## 3 Analysis of Wind Field Results over the Hill
### Comparison of Mean Wind Fields with Different Turbulence Models  
Figure 7 shows the mean wind velocity near the hill model computed by different turbulence models and the corresponding experimental data. From the figure, it can be seen that the simulated wind velocity obtained from each turbulence model follows the same trend as the experimental wind velocity distribution. At the front of the hill on the windward side, the simulated wind velocity obtained from each turbulence model is consistent with the experimental wind velocity, because they are not influenced by the hill model. However, the simulated wind velocity obtained from the DES-SA model decays faster than the experimental wind velocity and those obtained from other turbulence models. At the foot of the hill on the windward side, each turbulence model underestimates the experimental wind velocity near the wall. On the hillside on the windward side, each turbulence model overestimates the wind velocity near the wall, with those from the DES-SA, SST, and RNG models decaying faster at higher positions. At the hilltop, there is a significant increase in wind velocity near the wall, which tends to exacerbate its disaster-causing properties. To better compare the wind velocity at the hilltop, the mean wind velocity profile is shown in Figure 7b. It can be seen that the simulated wind velocity obtained from the LES and DES-RK models is generally consistent with the experimental wind velocity overall. In the near-wall region, the simulated wind velocity of the DES-SST and DDES-SST models is lower than the experimental wind velocity, while those of the DES-SA, SST, and RNG models overestimate the wind velocity and decay faster with increasing vertical height. The simulated wind velocity of the IDEES-SST model at the near-wall position matches well with the experimental wind velocity but underestimates it at higher vertical positions. On the hillside on the leeward side, the simulated wind velocity differs significantly from the experimental wind velocity, likely due to Cobra's inability to measure reverse flow values. At the foot of the hill on the leeward side, the simulated wind velocity obtained from the SST, RNG, and REA models agrees well with the experimental wind velocity near the wall, while those obtained from other turbulence  
Figure 6: Impinging jet simulator of Beijing Jiaotong University. models underestimate it. Behind the hill on the leeward side, the simulated wind velocity obtained from the DES-SA, DES-SST, DDES-SST, and IDDES-SST models all underestimate the experimental wind velocity, while those obtained from RNG and SST overestimate it. In general, the simulated wind velocity obtained from LES and DES-RK are in good agreement with the experimental wind velocity. To further analyze the accuracy of the simulated wind field of each turbulence model, Figure 8 shows a scatterplot between the experimental and simulated wind velocities. From the figure, it can be seen that the error of some simulation results obtained by each turbulence model is greater than 30%, with the experimental wind velocity is more underestimated. This is consistent with the phenomenon observed in Figure 7a, where the simulated wind velocity away from the wall region is less than the experimental wind velocity. Comparing wind velocity values of different SST turbulence models in Figure 8b-d,i, it can be seen that overall, the results of the IDDES-SST model are more accurate than those of DES-SST, DDES-SST, and SST. At positions with a large wind velocity (\(u/u_{j}>0.8\)), the results of IDDES-SST are better than those of DES-SST, DDES-SST, and SST, with an error range concentrated within 10%. In the wind velocity range of \(0.4<u/u_{j}\leq 0.8\), there are more points distributed when the error range of the DES-SST and DDES-SST  
Figure 7: (**a**) Comparison of wind velocity across the basin between different turbulence models and the experiment; (**b**) comparison of wind velocity at the hilltop between different turbulence models and the experiment.