## 5 Conclusions  
In this paper, we focus on how to apply suitable renumbering algorithms to enhance the performance of large-scale nuclear reactor fuel rod technology in a CFD numerical simulation framework. We do this by further integrating the meshing and mesh renumbering framework of YHACT, a general-purpose CFD software. The RCM algorithm is easily implemented by relying on the modular nature of the software. In this paper, we first perform parallel meshing of the model using **Parmetis** to ensure that each process obtains a similar size of mesh blocks and thus try to ensure that the computation time of each process is not significantly different. In addition, then, through rigorous experiments, we use MDMP as the discriminative index of sparse matrix quality to select a more suitable renumbering algorithm for the experimental case of this paper. Through the MDMP metric, it is easy to select the RCM algorithm is what we need. In addition, by plotting the contour clouds at the bar bundle and at the shelf, it is concluded in detail that our renumbering algorithm has a strong scalability in YHACT. This is also due to the modular development of YHACT, and the easy setup of the API. By observing the three contour plots of temperature, pressure, and velocity, it can be seen that the renumbered grid does not have any effect on the final solution results. The solution accuracy is well within the acceptable range. Therefore, \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**No. of Nodes**} & \multirow{2}{*}{**No. of Processes**} & \multicolumn{3}{c}{**Time**} & \multirow{2}{*}{**Speedup Rate**} \\ \cline{3-3} \cline{5-5}  & & **Original(s)** & & **RCM(s)** \\ \hline
2 & 96 & 19,731.4 & 13,682.5 & 30.66\% \\ \hline
4 & 192 & 8635.3 & 6727.38 & 22.09\% \\ \hline
8 & 384 & 3761.11 & 3342.41 & 11.13\% \\ \hline
16 & 768 & 1794.29 & 1568.07 & 12.6\% \\ \hline
32 & 1536 & 1618.58 & 700.528 & 56.72\% \\ \hline
64 & 3072 & 748.43 & 716.175 & 4.31\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The degree of enhancement of the RCM algorithm for numerical simulation of fuel rod bundles at different parallel scales. The first column represents the number of nodes. The second column represents the amount of processes. The third and fourth columns indicate the total simulation time for the original grid and the grid renumbered by RCM. The fifth column indicates the numerical simulation speedup of the renumbered grid compared to the original grid. we boldly and confidently conducted a large-scale parallel test. In the end, the number of processes for the 3*3 fuel rod bundle problem reached 3072, and the most significant speedup of 56.72% was achieved when the number of processes reached 1536. Meanwhile, the overall speedup increases to 56.72% when the speedup efficiency is gradually increased from 96 to 1536 threads. The acceleration efficiency does not decrease with the increase of parallelism size. Thus, the goodness of the strong scalability of parallelism was tested and proved. As industry develops and advances, the complexity of CFD numerical simulations will gradually increase. The gradual development of supercomputers will inevitably lead to an increasing parallel scale. It is necessary to improve the efficiency of numerical simulation through renumbering strategy. It is also necessary to select a suitable renumbering algorithm without affecting the scalability of the numerical simulation. It can be seen that the final test results of this paper have good scalability and obvious acceleration effect.The difficulty lies in the easy combination of different acceleration methods. In addition, the best way to do this is to continuously enrich the functionality of the general CFD software through modular development. The significance of this is that it does have a strong acceleration effect on real engineering cases. Continuously increasing the complexity and parallel scale of numerical simulations is the only way to better identify problems in the development process.