# Computational Fluid Dynamics Applied to
## 5 Results
### General Overview of the Results  
In order to have a better overview, the results shown in the previous sections have been summarized in Figure 8. In particular, in Figure 8, the number of studies that achieve a specific combination of accuracy of the results and complexity of the modelling can be seen subdivided per each approach. In the figure, it is clear that different approaches tend to perform differently in terms of complexity and accuracy. For instance, the GRA tend to get the greatest levels of accuracy and complexity. The LRA usually achieve a high level of accuracy but it is applied mainly for a medium-high level of complexity. The same level of complexity that can be simulated through OG but, usually, obtaining a lower level of accuracy. RRF/MRF approaches are characterized by a medium-low level of complexity and a wide range of level of accuracy. Through RMM/MSL medium-high level of both complexity and accuracy can be usually achieved. Most of the results concerning SM were not validated and, however, this approach is characterized by a low level of complexity. Eventually, meshless approaches are able to simulate complex system but the results could be accurate only at a qualitative level.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Paper** & **Year** & **Software** & **System** & **Target** & **Validation** & **Accuracy** & **Complexity** \\ \hline
[58] & 2012 & Open & Pump & Both & Yes & 90\%–95\% & 4 \\
[59] & 2015 & Open & Pump & Fluxes & Yes & Qualitat. & 4 \\
[53] & 2016 & Open & Gears & Both & Yes & \textgreater{}95\% & 4 \\
[54] & 2016 & Open & Gears & Both & Yes & 90\%–95\% & 4 \\
[55] & 2017 & Open & Gears & Both & Yes & \textgreater{}95\% & 5 \\
[60] & 2017 & Open & Gears & Both & Yes & \textgreater{}95\% & 5 \\
[61] & 2017 & Open & Gears & Both & Yes & \textgreater{}95\% & 5 \\
[56] & 2019 & Open & Gears & Both & Yes & 90\%–95\% & 4 \\
[62] & 2019 & Open & Gears & Both & No & N.A. & 5 \\
[57] & 2020 & Open & Gears & Both & Yes & \textgreater{}95\% & 4 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Classification of the pertinent papers exploiting the global remeshing approach.  
Figure 7: Number of studies exploiting the global remeshing approach shown based on the accuracy achieved and the complexity of the modelling.  
The distribution of the exploitation of approaches among the years are reported also in graphical form in Figure 9. The trend shows a clear increase of the number of records in the years also thanks to the developments in computer science. In 2019, the number of publication (29 papers) has more than doubled the previous years. Naturally, in 2020 there is a decrease both because this is the current year and, therefore, some publications have not yet been published or indexed in Scopus.  
In Figure 9, it is possible to notice that some approaches such as RMM/MSL and MRF and, to a lesser extent, LRA have been used continuously over the last decade. Other approaches, such as GRA and meshless approaches, are increasing their widespread use, especially in the most recent years. Moreover, the SM approach is used mainly in the most recent years.  
In Figure 10, through a spider diagram, it is shown (for each approach) the number of papers studying specific mechanical system, i.e., gears, bearing or pump. In the diagram, it is possible to notice that almost all the works carried out through remeshing strategies aims at studying gears. Pumps are mainly simulated exploiting RRF/MRF and RMM/MSL approaches. Eventually, components of bearings have been studied through the SM approach or RMM/MSL approaches. In addition, as mentioned in the previous sections, RMM/MSL is the most exploited approach. Figure 10 clearly shows that OG, LRA, and GRA are almost exclusively applied in the study of gears.  
Figure 8: Overview of the number of studies exploiting specific approaches shown based on the accuracy achieved and the complexity of the modelling.  
Figure 9: Distribution of the records among years divided per approach.