## 3 Results  
The delta P and UI values of the suggested designs were calculated using the Star CCM+ CFD program as seen in Figure 14, and these results have been added to the table for optimization calculations. Variance analyses have been conducted using the CFD experimental results of the designs. The average values of delta P, representing pressure drop, based on the levels of the factors, are provided in Figure 15. Factors influencing the difference in uniformity index values on the geometry exhibit an inverse relationship with pressure drop. The objective is to maintain a high uniformity index value in the optimum model to minimize the pressure drop. In this context, the significance of geometric parameters can vary significantly in these two areas. The signal-to-noise ratios indicate that the pressure drop response is influenced by factors R1, R2, L1, R11, R22, L2, L3, and L4. Examining the pressure loss, the optimal condition is observed when considering the lowest value, with variations of R1 = 1000 mm, R2 = 3000 mm, L1 = 50 mm, R11 = 1000 mm, R22 = 1500 mm, L2 = 170 mm, L3 = 50 mm, and L4 = 150 mm. It is noted that the pressure drop decreases significantly with an increase in the lengths of L1 and L3. Conversely, an increase in the radii R11 and R22 leads to an increase in pressure drop. The signal-to-noise ratios of factors influencing the pressure drop for channel geometry designs are provided in Figure 15. It is observed that the most influential factor affecting pressure drop is L1. As this parameter increases, the pressure drop decreases significantly. Figure 14: CFD results. The graphs more clearly illustrate the impact of dimensionless coefficients on the pressure drop. The most significant effects are determined to be in the order of L1, R11, R22, and L3. The results of the regression analysis for factors influencing the pressure drop are provided in Table 3.  
The Pareto chart of standardized effects for pressure drop is presented in Figure 16. It is observed that the factor L1 length has the highest impact on the pressure drop. The average values of the uniformity index for different levels of factors are presented in Figure 17. Factors influencing the difference in uniformity index values on the geometry  
Figure 16: The Pareto chart of standardized effects for pressure drop. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**S** & **R-sq** & **R-sq (adj)** & **R-sq (pred)** \\ \hline
2.27504 & 87.64\% & 83.28\% & 81.77\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Model summary for pressure drop values. Figure 15: Graph depicting the signal-to-noise ratio of the pressure drop response based on factors and levels, obtained using the Minitab program (Version 22.2.0) (unit of \(X\)-axis is [mm]). exhibit an inverse relationship with pressure drop. The objective is to maintain a high uniformity index value in the optimum model to reduce the pressure drop as much as possible. The signal-to-noise ratios indicate that the uniformity index response is influenced by factors R1, R2, L1, R11, R22, L2, L3, and L4. In Figure 17, the average values of pressure drop corresponding to factors and levels are presented. When examining the uniformity index (UI), the optimal condition is observed when considering the lowest value, with variations of R1 = 1000 mm, R2 = 3000 mm, L1 = 110 mm, R11 = 1000 mm, R22 = 1500 mm, L2 = 170 mm, L3 = 50 mm, and L4 = 150 mm. The UI increases with the increase in the radius R2 and length L4, while it decreases with the increase in the radius L3. The signal-to-noise ratios of factors influencing the pressure drop for channel geometry designs are provided in Figure 17. It is observed that the most influential factor affecting UI is R11. As this parameter increases, the UI decreases significantly. The graphs more clearly illustrate the impact of dimensionless coefficients on the pressure drop.