## 4 The Test of the Model for Different Ventilation Airflows  
The aim of this paragraph is to understand the applicability of the numerical model, i.e., whether it is limited to the ventilation type used in CALIB1 or can be further employed for other ventilation types. From the experimental viewpoint, two other experiments were carried out: (1) CALIB2 corresponding to small airflow rates (apartment buildings) and (2) CALIB3 corresponding to high ventilation rates (smoke and gases evacuation by means of ventilation system). The air speed was experimentally determined for all cases in the section of the air outlet in over 600 points, by means of an anemometer. The air speed profiles (Figure 7) were used to determine the average air speed, \(v_{a}\), in the air outlet section and airflow, \(Qv\). Higher ventilation rates correspond to higher airflow rates. Figure 6: Model calibration, according to HRRPUA criterion; (**a**) temperature evolution for different methods of introducing HRRPUA and (**b**) different decreasing slopes for HRRPUA. From the numerical simulation viewpoint, the same numerical model was used. The only parameter changed between the calibrated model (CALIB1) and current test cases is the ventilation rate. The experimentally measured values were introduced in the numerical model, as in the case of the inlet, by using a mass flowrate boundary condition at the inlet of the computational domain. Both the experiments and the numerical studies lead to the variation of the temperature in control point S24 over time. The temperature variation profiles, predicted by the numerical model, were compared to the experimentally determined profiles. The numerical model is appropriate if the error between the numerically predicted and measured temperature is acceptable for our field of research. We observe that the temperature variation profiles present have a logarithmic increase and tend to stabilize towards the end of the analyzed time period. A similar pattern is observed for all ventilation cases (Figure 8). For CALIB1 vs. MODEL1 (green curves in Figure 8), the graph shows that temperatures tend to stabilize at about 100 \({}^{\circ}\)C. That point is the value at which the amount of heat introduced by burning the fuel becomes equal to that lost by the system. The two temperature profiles are almost superposed, denoting an excellent match of the numerical prediction over the experimentally measured values. Figure 8: Temperature evolution chart in the model for CALIB1/MODEL1, CALIB2/MODEL2, and CALIB3/MODE3. Figure 7: Air speed distributions at the outlet. For CALIB2 vs. MODEL2 (yellow curves in Figure 8), the temperature profile, obtained by means of the numerical simulation, is almost superposed over the experimentally measured temperature profile. The standard deviation of the temperature prediction error is \(\sigma_{Err}\) = 2.6 \({}^{\circ}\)C. This value that is considered appropriate, being within the acceptable range for our phenomenon. This temperature profile tends to stabilize at about 90 \({}^{\circ}\)C.  
For CALIB3 vs. MODEL3 (blue curves in Figure 8), we can see that the two-temperature profile almost overlapped. The standard deviation of the temperature prediction error is \(\sigma_{Err}\) = 1.7 \({}^{\circ}\)C, the smallest value of all three cases. This value is also considered appropriate, being within the acceptable range for our phenomenon. We can observe the temperature curve is stabilizing at about 50 \({}^{\circ}\)C.  
From a phenomenological point of view, the higher the ventilation rate, the faster the indoor hot air is evacuated and replaced with cooler outdoor air, thus maintaining a cooler air indoor. Moreover, one can also expect that a higher airflow might influence the indoor air dynamics. Thus, the hot air might be drawn towards the center of the room (in the direct line between the air inlet and outlet) and less towards the upper side, leading to the same conclusion.