## 3 Simulation Results and Discussion
### Overall Results  
The first findings discussed are each city's overall mean values for the three thermal performance parameters studied, comparing wooden and granite radiant flooring. In the three figures included in this section, the value given for the wooden flooring in each city is the mean value found by simulating the thermal behaviour of the 60 wood floors in each of the 216 dwellings defined. As only one granite floor was defined, the value shown for each city is the mean value of the 216 dwellings analysed. The mean minimum and maximum values for the wood floors in all the 216 dwellings are depicted as error bars.  
Mean energy demand values are shown in Figure 4 by city. In this chart, the values were computed excluding cases where the operative temperature was, on average, greater or equal to 20 \({}^{\circ}\)C for less than 14 h a day. That criterion was adopted for reasons of comparability since very thick, low thermal conductivity wooden floors, for instance, might present a low heat transfer rate on the water side, from which it might be falsely inferred  
Figure 3: Law for the assignment of window U-values with heating degree days in the coldest month in each city.  
that they constitute a good choice of material. A low energy demand value under such conditions may be an indication, however, that those floors, able to transfer only small amounts of heat, fail to comply with this minimum comfort requirement of 14 h a day. In short, this figure compares the overall results in terms of energy demand for cases complying with a minimum comfort requirement.  
The mean energy demand for the wooden floors was only slightly higher than that of the granite floor in all the cities, and in nearly every case the mean minimum values associated with the best performing wooden floors (with lowest energy demand) were practically the same as for granite. The mean maximum values, i.e., the mean for the worst performing wooden floor (with the highest demand), varied widely from city to city. In general, a greater difference between the mean maximum and mean values was observed where demand was higher, i.e., where winter weather was more severe. That observation would appear to infer that the choice of a given wooden flooring has less impact in cities with mild winters such as Madrid or La Paz.  
The mean values for comfort hours are shown in Figure 5, with fewer observed in the cities with the most severe winters. In all the cities, the mean value for the wooden floors was lower than that for the granite floor, although the difference in most cases was fairly small (1 h or less), the exceptions being places with very severe winters such as Irkutsk or Yakutsk. One finding of note was that the mean maximum, denoting the best-performing woods in terms of comfort levels, were consistently slightly higher than the value for the granite floor, with the exception of extreme winters. In other words, the operative temperature was comfortable for slightly longer with the most suitable wooden floor than with the granite one. Another finding was that the difference between the mean maximum and mean minimum values was greater in the cities with the coldest winters. That supports the premise that the choice of a wooden flooring with suitable properties is more important in cities with severe winters than in those with milder temperatures.  
The mean start-up lag time values for each city are shown in Figure 6, including only cases where comfortable conditions were attained in less than 72 h. In all the cities, the mean start-up lag time was shorter with granite floors, with only the best-performing wooden floors exhibiting comparable levels. The graph also shows that the difference between the mean maxima and mean minima was greater in the cities with the severe  
Figure 4: Mean energy demand values in each city.  
winters, again implying that the choice of wooden floors with suitable properties would be of greater significance in these cities.