## 3 Simulation Results and Discussion
### Effect of Thermal Conductivity  
The preceding section discusses the findings for energy demand, thermal comfort, and start-up lag time depending on climate and dwelling construction characteristics. The mean, maximum, and minimum values for wooden floors were compared with the value for granite. This section addresses the impact of the thermal properties of wood on these three performance parameters. As in the previous research [29], only the thermal conductivities that performed best are shown. The thermal inertia (density, specific heat, and conductivity) of all the radiant floor materials was envisaged in the simulations. However, this section addresses the impact of only the thermal conductivity of the flooring because of the relationship existing between the thermal conductivity and density of wood shown in [29], and because the same specific heat was considered for all the kinds of wood. Therefore, the effect of varying thermal conductivity encompasses the effect of thermal inertia. No simple rules can be found to define the properties that a wooden flooring must possess to minimise energy demand depending on the dwelling and climate. In pursuit of a possible solution, the wooden floorings were grouped by thermal conductivity and the percentage of cases was determined for which each conductivity range exhibited the best performance. Figure 9 shows the percentage of cases among all the dwellings and cities analysed in which each thermal conductivity range would be that of choice from an energy demand and thermal comfort perspective. Figure 9a shows the percentage of cases in which each conductivity range was identified with the lowest energy demand while meeting the minimum comfort requirement of 14 h a day. It shows that the percentage was highest in the highest conductivity range, although in 10% of cases the heating demand was lowest for the wood floorings with the lowest conductivity. The percentage of cases of each conductivity range associated with the greatest number of comfort hours is shown in Figure 9b. The wood in the highest conductivity range delivered greatest number of comfort hours in a higher percentage of cases, although that with a thermal conductivity as low as 0.12 W/(m-K) was associated with the highest comfort levels in 10% of the cases. Figure 9: Percentage of cases in which each conductivity range was identified with **(a)** the lowest energy demand while meeting the minimum comfort requirement and **(b)** the greatest number of comfort hours. This behaviour pattern was also found in the previous research by the present authors [29], in which they analysed the effect of wood properties on energy demand and thermal comfort in Madrid. The present study demonstrates the aptness of low thermal conductivity wooden floorings for providing thermal comfort with low energy demand in dwellings all around the world. A priori, no wood should be rejected for use in radiant floors from an energy demand and comfort point of view solely on the basis of its conductivity value. It is clear that to evaluate the thermal behaviour of these heating systems correctly, it is necessary to perform a simulation of the radiant floor together with the building under transient conditions. As in the previous research, for all dwellings and in all climates, the radiant floor that consistently presented the shortest lag time to attain the set-point temperature after start-up was the one with the highest thermal conductivity and the least thickness. Nonetheless, the impact of thermal conductivity on variations in this parameter is worth exploring. This is shown in Figure 10, where the reference corresponds to the floor with the highest thermal conductivity. For each thermal conductivity value, it shows the mean, maximum, and minimum percentage increase in start-up lag time relative to the reference value, averaging for all dwellings in all climates.