## 6 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Segment**} & \multicolumn{2}{c}{**Diameter Using Traditional**} & \multirow{2}{*}{**Diameter with Automation (mm)**} & \multicolumn{2}{c}{**Final Pressure with Traditional (ma)**} & \multicolumn{2}{c}{**Final Pressure with Automation (ma)**} & \multicolumn{2}{c}{**Error between Pressure Results (\%)**} \\  & & & & & & \\ \hline MAP & RAP & 25 & 25 & 13.72 & 13.24 & 3.50\% \\ RAP & A & 25 & 25 & 12.57 & 13.03 & 3.66\% \\ A & B & 25 & 25 & 11.19 & 11.27 & 0.71\% \\ B & C & 19 & 19 & 10.69 & 10.68 & 0.09\% \\ C & D & 19 & 19 & 10.52 & 10.39 & 1.24\% \\ D & BOLL & 13 & 13 & 8.05 & 8.24 & 2.36\% \\ D & E & 19 & 19 & 10.35 & 10.13 & 2.13\% \\ E & CAL & 19 & 19 & 8.98 & 8.54 & 4.90\% \\ E & LO & 13 & 13 & 9.05 & 9.11 & 0.66\% \\ C & WC & 13 & 13 & 9.80 & 10.11 & 3.16\% \\ B & LP & 13 & 13 & 8.97 & 9.61 & 7.12\% \\ \hline \hline \end{tabular}
\end{table} 
Table 22: Comparison of diameters and final cold water pressure for type 1 retail store. presented algorithm performed the calculations based on exact numerical information, implying more reliable and accurate results. It can thus be assumed that relative errors with high values suggest an inaccurate interpretation of the two-dimensional plans of the structure. As shown in Table 18, and in comparison to the previous results, the maximum daily consumption was optimised, obtaining a head loss of 0.78 mca for a sub-meter of 25 mm. Finally, a comparison of the actual values and calculated values for pressure losses and diameters is shown in Table 25.  
When looking at the diameters in Table 25, a clear difference in the first and third segments is evident. Again, this involved the use of larger diameters in the sections that lead to a fixture, as was the case for the \"H-BOLL\" section. As explained above, this difference was a result of the use of specific criteria for automation. Furthermore, in the case of the \"CAL-G\" segment, it can be inferred that the designer used a larger diameter in order to increase the pressure in the final segments of the network. However, the automated method shows that the accuracy in the calculation allows diameters to be reduced, as the value of the losses is known with greater reliability. Finally, the relative error with the highest value (22.87%) corresponded precisely to the increase in the load resulting from the use of larger diameters. For sanitary drainage, the algorithm developed was able to realise the piping design correctly with regard to calculations, modifications and verifications; the performance of the software resulted in a reduction in the time taken to process information and display outcomes. Using programming to create verification tools requires more manual iterations, thus simplifying the project review process and reducing errors. The scenarios described here assume a properly structured algorithm workflow; although Dynamo provides predefined nodes and simplified actions, building computational programming requires prior knowledge--not only about Dynamo itself but also about code --model interactions. Some of the difficulties found here are largely related to this factor. In