## 4 Results
### Analysis of Thermal Inertia  
To advance the study, the thermal inertia of the building is analysed, specifically, how the building retains heat over the course of consecutive days within the same week. For this purpose, the daily temperature trends are monitored for the 4 weeks across the 4 months with heating on. Figure 4 illustrates the evolution of the average temperatures of the building facade (orange curve) compared to the weather conditions (blue curve), highlighting the following observations:  
* In November, the weekday temperatures (Monday to Friday) for all weeks show a pattern similar to the evolution of the weather conditions. Over the weekends, the average temperature (orange curve) drops, due to the absence of occupancy and the heating being turned off;
* In December and January, the Christmas holidays are highlighted with green boxes in Figure 4b,c. Additionally, as shown in Figure 3, there are marked drops in temperatures (orange curve);
* During week 2 of December, when the weather follows a progressive cooling trend (blue curve), the heating gradually increases the temperatures (orange curve). The predicted effect occurs (black arrows), where the temperatures toward the end of the week surpass those of earlier days due to the thermal inertia. This effect is also observed in week 3, especially in the evolution of minimum temperatures;
* Following this explanation, the sawtooth pattern of progressively rising temperatures as the week progresses is more noticeable when the weather also follows an upward trend, as seen in weeks 3 and 4 of January (black arrows);
* In February, this effect is also observed (black arrows), leading to the conclusion that regardless of weather conditions, heating causes a progressive rise in temperatures (Monday to Friday and cumulatively over the 4 weeks of the month), defined by a sawtooth pattern.  
Figure 3: Analysis of thermal evolution in the autumn–winter period.  
To deeper analyse the thermal inertia, the temperature trends are examined during two holiday periods and highlighted as black boxes in Figure 3: period 1 (6-10 December, see Figure 5) and period 2 (23-31 December, see Figure 6). Figure 5a illustrates the weather conditions, showing maximum temperatures ranging between 10 and 14 \({}^{\circ}\)C (first three days: 6 th, 7 th, and 8 th), followed by an increase to 18 and 19 \({}^{\circ}\)C (on the 9 th and 10 th days). Figure 5b compares the average temperatures across several zones, following the layout in Figure 2b. Zones A, B, and C (yellow, green, and blue curves) display similar trends, while Zone D (red curve) records the lowest temperatures (with the largest variations). This is explained because Zone D (top floor) is more exposed to weather conditions. Additionally, as it is winter and spaces remain unoccupied during the holidays, Zone D is more affected by low temperatures. Comparing Zone D temperatures, see red curve in Figure 5b, with weather conditions, see Figure 5a, a similar pattern emerges, allowing to quantify a thermal inertia of approximately 3 \({}^{\circ}\)C above the outdoor temperatures.  
Similarly for holiday period 2, Figure 6a shows a gradual decrease in temperatures (from the 23 rd to the 28 th days) by approximately 16 \({}^{\circ}\)C, followed by a rise (from the 28 th to the 31 st), returning to the original 16 \({}^{\circ}\)C. Figure 6a again confirms that Zone D records the lowest temperatures, as previously explained, due to its exposure to weather conditions. Observing the first five days (23-28) and comparing Figure 6a,b, a thermal inertia of approximately 3 \({}^{\circ}\)C above the outdoor temperatures is again confirmed.  
Figure 4: Analysis of thermal inertia: (**a**) November; (**b**) December; (**c**) January; (**d**) February.  
Figure 5: Analysis of thermal inertia (holyday period 1): (**a**) Weather; (**b**) Comparison by zones.