## 3 Results and Discussion  
The development of temperature was measured and evaluated by SW Stabil to examine the potential of computational prediction of the thermal behaviour of such a residential object, as introduced in Section 2.3, using the approach described in Section 2.2. Figure 6 shows the time development of temperature in one selected room (number 5) in January 2018, i.e., in the period crucial for the controlled heating under the Central European climatic conditions, in 15-min intervals. There were two obtained datasets, (i) empirical data and (ii) the results of numerical simulation using the gbXML-based transfer from the digital twin of the structural object. From a thermal-technical perspective, the building is composed of materials with high thermal capacity, particularly considering botanical fibres such as wood. Throughout the study period, the entire building, including classrooms, remained unheated, allowing internal room temperatures to redistribute following the thermal fluxes driven by external boundary conditions--air temperature, solar irradiation, wind pressure, and natural ventilation. Since no artificial heating was active, the influence of neighbouring rooms  
Figure 6: Comparison of measured data with those obtained from computational prediction in one selected room, highlighted in Figure 4.  
was minimal, and additional internal heat sources, such as occupants or artificial lighting, were excluded. Empirical data reflect real thermal conditions inside the building, whereas model-based data aim to replicate these conditions using predefined physical parameters and environmental influences. The study considered boundary conditions based on a 20-year temperature average for the given locality. The period under review spanned 31 days, yielding 2976 measurements per dataset. The empirical data exhibit dynamic temperature fluctuations with sharp local transitions, likely caused by external factors such as (i) door openings or (ii) ventilation system changes. These short-term variations highlight momentary responses to ambient conditions essential for understanding the thermal behaviour of timber buildings. In contrast, computational simulation results show more moderate temperature changes due to numerical modelling simplifications. Short-term variations (i, ii) are not captured in detail, but long-term trends are well aligned between both datasets. To further validate the computational approach, temperature profiles for Room No. 5--located in the heavily insulated timber house--were analysed for January 2019. This period was characterised by low temperatures and limited solar irradiation under typical Central European winter conditions, with no artificial heating. The simulation considered temperature development over an entire year, including all seasons, winter, spring, summer, and autumn, ensuring quasi-periodic trends over multiple years, accounting for initial temperature distributions and potential controlled heating scenarios. Given the inherent uncertainties in climatic data, a sensitivity analysis was conducted. Original local climatic data spanning 26 years--including environmental air temperature and global and diffuse solar irradiation--were compared with officially averaged reference-year data. Comparative simulations using 26 distinct datasets were performed to evaluate deviations, including variables such as air exchange rates influenced by occupant behaviour. When applying reference-year data, the Pearson correlation coefficient between measured and simulated temperatures for January 2019 was 0.975, indicating strong alignment. To assess variability, standard deviations between specific yearly data and reference-year values were computed. Using an expansion factor of 2, a 95% confidence interval was established, resulting in a \(\pm\)2.1 K band around the temperature curve. Importantly, real measurements remained within this band, supporting the validity of the computational simulation approach and its applicability for long-term thermal predictions in timber buildings.