AI Summary & Key Takeaways
AI InsightAs a result of these three scenarios, the possibility of not providing thermal comfort in the underfloor heating system is detailed and interpreted.
📌 3 Key Takeaways
Abstract
Thermal comfort is related to the stability of the ambient temperature. Constant changes in ambient temperature appear as a situation that negatively affects comfort. The selected build-ing systems must be arranged to maintain this stability for the continuity of thermal comfort. In this study, issues affecting thermal comfort in water system underfloor heating applications of buildings are handled and analyzed using the Bayesian Network modeling methodology. Visual examples of the problems encountered in field applications are also given. Three dif-ferent scenarios are tested with the constructed Bayesian Network model. In the first scenario, assumed that mechanical project failures were prevented. In this case, it was observed that the failure rate decreased by about 5%. In the second scenario, assumed that mechanical applica-tion failures are prevented along with mechanical project failures. The failure rate decreased by 11% compared to the first situation. The third scenario assumed that the mechanical proj-ect preparation phase was concluded without any problems, the mechanical project was im-plemented without any failures, and the mechanical system was commissioned without any problems. In the last scenario, the failure rate decreased by 14% compared to the first case, and the probability of not providing thermal comfort remained at 2%. As a result of these three scenarios, the possibility of not providing thermal comfort in the underfloor heating system is detailed and interpreted.