## 5 Limitations  
### Limitations of a Single Stationary Human Body Model  
This study employs static models for both CFD simulations and wind tunnel experiments, opting for simplicity over complex dynamic models. This choice is made due to the limitations of current CFDs' technology in handling the dynamic changes in athlete models effectively. Static models can furnish vital insights into aerodynamic drag and formation effects, fulfilling the requirements of research on drafting formation effects. Furthermore, static models are extensively employed in other research domains like cycling, running, swimming, and cross-country skiing to investigate drafting effects in human movement [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17]. While static models cannot completely mimic the dynamic intricacies of actual motion, a thorough analysis of combined experimental data and computational models can yield valuable insights and guidance.  
Moreover, in real competitions, athletes exhibit diverse body shapes and movements, resulting in a highly intricate scenario. To streamline research, current methodologies frequently rely on simplified models and assumptions. For instance, in wind tunnel experiments, multiple individuals are frequently tested in identical movement positions, regardless of their varying body shapes. This approach facilitates the comparison of aerodynamic properties among athletes with diverse body types. Similarly, CFD simulations often use a single human body model. This is due to the fact that accounting for variations in the  
Figure 14: Percentage increase in operating speed after the improvement in operating economy [34].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Optimal Drafting** & **Speed after Improving** & **Percentage** & **Competition** & **Time (s)** & **Percentage** \\
**Formations** & **Sports Economy (m/s)** & **Increase in Speed** & **Time (s)** & **Difference (s)** & **Improvement in** \\ \hline Race walking alone & 4 & & 5000 & & \\ Double formation & 4.144 & 3.61\% & 4826.2 & 173.8 & 3.48\% \\ Triple formation & 4.161 & 4.03\% & 4806.5 & 193.5 & 3.87\% \\ Quadruple formation & 4.187 & 4.67\% & 4776.7 & 223.3 & 4.47\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: The speed and performance of core race walker in optimal drafting formations in the 20 km race walking competition after improving sports economy.  
body shape and posture of multiple athletes would substantially elevate model complexity, demanding greater computational resources and time. Despite the limitations of these simplified methods and assumptions, they continue to offer valuable guidance.  
The study revealed that, despite variations in the postures of human models in CFD and wind tunnel experiments, the difference in drag reduction rates remained below 10%. Furthermore, a comparison with the drag reduction rate of the optimal double drafting formation after mirroring and similar formations in existing literature revealed that even with variations in model posture and body shape, the drag reduction rate error after mirroring was merely 4.6%. Moreover, the discrepancy in drag reduction rates between the optimal triple drafting formation, the optimal double drafting formation, and [PERSON]'s research results is also below 6%. These findings indicate that while a single static model possesses certain limitations, its influence on the drag reduction effect of drafting formations is minimal, rendering it suitable as a benchmark for analyzing the drag reduction effect and mechanism.