## 3 Simulation Results and Discussion
### Effect of Thermal Resistance  
The mean results in the previous section indicate that, a priori, no wood should be rejected for use in radiant flooring based solely on its thermal conductivity value. However, different thermal behaviour should be expected when a certain thickness of a wood is used in a specific climate or building. This section aims to clarify whether certain combinations of wood and thicknesses should be rejected according to the climate and construction characteristics of a dwelling. Specifically, the parameter that relates the thermal conductivity and thickness of a material is thermal resistance, which is one of the most commonly used measures of the thermal performance of construction materials. Thus, this section explores the effect of the thermal resistance of wooden flooring on the thermal performance of radiant heat systems. Figure 10: Effect of wood thermal conductivity on start-up lag time: percentage rise of start-up lag time relative to that of the floor with the highest wood covering conductivity. Figure 11 shows how the thermal resistance of the wooden flooring affects energy demand, thermal comfort hours, and start-up lag time for the five cities selected in Section 3.2. Three data series are shown: series 1 corresponds to dwellings with the lowest energy demand, greatest comfort hours, or shortest start-up lag time for the respective thermal conductivity values (referred to as 'best performing'); Series 2 corresponds to dwellings with the highest energy demand, lowest comfort hours, or longest start-up lag time for the respective thermal conductivity values (referred to as 'worst performing'); and Series 3 corresponds to the mean values for energy demand, comfort hours, or start-up lag time for the respective thermal conductivities considering all dwellings. Since the designation of 'best' and 'worst performance' in Figure 11 varies depending on the parameter analysed, the best-performing dwellings in terms of comfort were not necessarily the best regarding demand or start-up lag time, although this often was the case. As a rule, the dwellings that performed well in one parameter also exhibited good performance in the other two. The data represented by hollow dots in the figure correspond to cases where the minimum comfort requirement of 14 h a day was not met. The findings in Figure 11 are addressed parameter by parameter below. Concerning energy demand, the data for the best performing dwellings (Series 1) and also for the mean (Series 3) showed that it was practically unrelated to thermal resistance in all but one city, Yakutsk, where the mean series declined very slightly with rises in resistance. That decline was attributable to the decline in pipe-to-space heat transfer capacity with rising thermal resistance. One consequence of lower heat transfer was fewer hours in conditions of comfort; on average, at a thermal resistance above around 0.10 m\({}^{2}\) K/W in Yakutsk, the radiant system failed to meet the minimum comfort requirement of 14 h a day. For the worst-performing dwellings (Series 2), the energy demand fell at higher thermal resistance values for all the cities, although this decrease was more significant in the coldest climates. As explained above, that decline was attributable to lower pipe-to-space heat transfer, resulting in fewer comfort hours. In all the cities, the radiant system failed to meet the minimum comfort conditions after exceeding a given thermal resistance. Specifically, the worst performing dwellings in Yakutsk failed to reach these minimum conditions at any thermal resistance. In the best-performing dwellings (Series 1), rises in thermal resistance had no effect on the number of thermal comfort hours. In nearly all the cities, such dwellings presented thermal comfort conditions for close to 24 h a day. On average (Series 3), rises in thermal resistance led to a decrease in the number of comfort hours, this decline depending on the severity of the winter in each city.