## 4 Discussion and Limitations
However, the use of standardized occupancy schedules is crucial for computationally efficient decision-making in the early design stages. The approach to generate a set of schedules along with a probability of the occurrence of these scenarios [16] could assist to further improve the accuracy of our proposed IFC-based thermal comfort analysis. For the evaluation of the results, we modified, as described, more parameters than just the proposed clothing and activity parameters compared to the original TEASER templates [46] to meet the requirements of our residential building. Some parts of theTEASER templates originate from the DIN V 18599-10 [47], which has been designed for energetic validation and rating of buildings and, thus, may not be fully applicable for engineering tasks within the design stage of buildings. For a further use of our proposed thermal comfort parameters as addition to the TEASER template set, the full set of templates should also be tested for consistency. As an example: in the TEASER templates, the bedroom has full occupancy 24/7 while a hotel room is only occupied during the night. Taking a closer look at the thermal comfort analysis itself, it has to be noted that BPS using EnergyPlus only calculates a single-node-per-zone PMV measure, neglecting any kind of furniture or people position within the room. The BPS engineer should be aware of the BPS limitations and also of the inaccuracies due to the choice of parameters. For a detailed thermal comfort analysis, the user must apply a much more detailed CFD analysis, which could be focused on building parts that show a high dissatisfaction with thermal comfort discovered in the BPS analysis. When we take a closer look at the impact of the weather data, the presented results and examples only show the potential of our IFC-based approach. This study does not evaluate or compare actual design alternatives but focuses on proposing the IFC-based thermal comfort approach itself. Other weather files representing other climate change scenarios will lead to different results. However, our approach can be easily repeated using different weather files representing a variety of climate change scenarios. Design alternatives can be evaluated using our IFC-based approach without manual remodeling. However, our simulation results (heating and cooling loads) match the observations from related research [19; 68], even though the results can only be qualitatively compared as the building geometry, construction, location, and weather data vary from the cases from related literature. The development of benchmark cases could help to evaluate the accuracy of our proposed methods. A more general limitation of our proposed methods is that the selected timeframe for weather prediction should be chosen according to the predicted use of the analyzed buildings. The timespan of climate prediction from our use case is only used to highlight the potential of our proposed methods. However, until we reach the SSP5-8.5 (2080) scenario, the building can be refurbished multiple times (HVAC, insulation), or even demolished, or the usage has changed (used as an office of a smaller company vs. used as a holiday apartment), such that the comfort predictions and energy savings do not apply anymore. The construction weight and the resulting resilience of the building due to thermal mass in comparison to the embodied carbon can still be evaluated with our methods even for such large timespans of sixty years, but the occupancy schedules and internal loads can hardly be predicted. However, as long as the user is aware of the input data limitations when interpreting the thermal comfort results, the reduced model setup time due to enriched IFC data is still highly beneficial to the decision-making within the design process.