Key research themes
1. How can thermal comfort indexes be standardized and validated using large-scale field data to improve their applicability across diverse indoor environments?
This research area focuses on the collection, harmonization, and analysis of large thermal comfort datasets from real buildings and real occupants worldwide to support the development, testing, and validation of standardized thermal comfort indexes. It emphasizes empirical data-driven approaches and the use of extensive databases to uncover statistically significant patterns and improve existing comfort models like PMV and adaptive comfort models. Such work is critical for enhancing the robustness, accuracy, and generalizability of thermal comfort indexes used in standards and building design practice.
2. What factors influence occupant thermal sensitivity and how does this variability impact the accuracy of thermal comfort indexes?
This theme investigates how occupant thermal sensitivity—the change in thermal sensation relative to changes in indoor temperature—varies across building types, climate zones, ventilation modes, and occupant demographics. It challenges the use of universal constants in comfort models (e.g., Griffiths Constant) and explores the implications of such variability for more precise estimation of thermal neutrality and comfort zones. Understanding sensitivity differences expands the adaptability and accuracy of thermal comfort indexes, especially in heterogeneous real-world contexts.
3. How do outdoor and indoor environmental variables and dynamic factors impact the applicability and predictive power of thermal comfort indexes, especially regarding long-term comfort and outdoor environments?
This research area explores the applicability, limitations, and enhancements of thermal comfort indexes by accounting for temporal variability, outdoor climatic diversity, and mean radiant temperature estimation methods. It highlights the challenges in predicting comfort over extended periods and outdoors where environmental parameters fluctuate greatly. The goal is to refine indexes to better reflect real-world occupant experiences by integrating dynamic environmental measurements and improving index components like mean radiant temperature.