## 4 Results and Discussion
### Results Overview  
To allow for the better and easier analysis of the results, Figure 10 shows only the averaged \(R_{\text{cond}}\) values computed using the four FEM computational tools, as well as their percentage variations. Regarding the partition LSF wall (Figure 10a), we can now even  
Figure 9: Conductive thermal resistances (\(R_{\text{cond}}\)) for different external surface thermal resistances (\(R_{\text{se}}\)) computed by different FEM softwares and their average value variations: (**a**) homogeneous partition; (**b**) homogeneous facade.  
more clearly see the increase in the conductive thermal resistance values, from 1.522 up to 1.645 m\({}^{2}\cdot\)K/W, corresponding to a percentage variation up to +8.1%.  
Observing now the results obtained for the facade LSF wall (Figure 10b), we can see that the \(R_{\text{cond}}\) averaged values are nearly constant, showing only a slight increase from 3.199 up to 3.205 m\({}^{2}\cdot\)K/W, which also means a minimal percentage variation up to +0.2%.  
The \(R_{\text{cond}}\) values for homogeneous simplified LSF walls (i.e., without the steel frame) are constant, and do not change with the increment of the external surface thermal resistances, as previously seen before in Section 4.3.  
To better understand and visualize the obtained results, Figure 11 displays the average computed conductive thermal resistances (\(R_{\text{cond}}\)) and the corresponding temperature color distribution predicted by the THERM models for the two extreme surface thermal resistances (\(R_{\text{se}}\)), these being 0.0 m\({}^{2}\cdot\)K/W for the first column and 0.20 m\({}^{2}\cdot\)K/W for the second (right one). Three different wall configurations were selected for this analysis, namely: (a) partition LSF wall; (b) facade LSF wall, and (c) facade, homogenous simplified wall.  
Looking to the partition LSF wall cross-section temperature distributions (Figure 11a), and comparing the results for both surface thermal resistances, it is clearly visible that, near the external wall surface, there are some differences, the major ones being near the flange of the steel stud, as a result of the related thermal bridge effect. In fact, for the higher \(R_{\text{se}}\) (0.20 m\({}^{2}\cdot\)K/W) the external surface temperatures are also higher, as expected, in comparison to the other \(R_{\text{se}}\) value.  
We can also observe similar results for the facade LSF wall cross-sections (Figure 11b); given the external continuous insulation layer (ETICS), the steel stud's thermal bridge effect is now more attenuated, mainly near the external wall surface, where the temperature values are almost constant for both \(R_{\text{se}}\) values. These features elucidate the reason why, in this LSF wall configuration, the conductive thermal resistances are almost the same, with an increment of only +0.2%.  
Regarding the simplified facade wall with homogenous layers, i.e., without steel studs (Figure 11c), as expected, the computed colour distribution is steady over all the layers of the wall, corresponding to a perfect unidirectional heat transfer without any thermal bridge effect. Therefore, the \(R_{\text{cond}}\) values are now fixed for all evaluated surface thermal resistances. Obviously, besides being fixed, the surface-to-surface \(R\)-value is now bigger (4.283 m\({}^{2}\cdot\)K/W) when compared with the previous LSF wall configuration (3.200 m\({}^{2}\cdot\)K/W), corresponding to an increment of 1.083 m\({}^{2}\cdot\)K/W (+33.8%).  
Figure 10: Average values of computed conductive thermal resistances (\(R_{\text{cond}}\)) for different external surface thermal resistances (\(R_{\text{se}}\)) and their percentage variation: (a) partition LSF wall, (b) facade LSF wall.