Development of a mixed chamber experimental and CFD database of indoor environments

Abstract

Recent studies reveal that individuals spend the majority of their time indoors, and indoor air quality (IAQ) plays a crucial role in occupant health and productivity. However, current research primarily focuses on specific environments with complex variables and challenging boundary conditions, limiting our understanding of IAQ and thermal comfort. Many studies use fixed experimental chambers, restricting control over boundary conditions. To address these limitations, we propose a novel data-driven smart indoor environmental control framework. This study advocates for a standardized database that integrates diverse IAQ and thermal comfort metrics to enhance indoor environmental conditions and presents the initial phase of this endeavor, detailing the development of a chamber experimental database. This phase involves examining six standardized experiments and over 96 distinct case studies, resulting in a comprehensive dataset of 528,000 entries, rigorously analyzed. Simultaneously, this research enhances its empirical foundation by developing and validating computational fluid dynamics (CFD) models. These models complement and refine the database, increasing its utility and robustness. Notably, experimental findings regarding CO2 and temperature variations indicate a significant 32 % and 65 % decrease in average relative CO2 concentration when the inlet air speed increased from 1.7 to 2.1 and 2.5 m/s, respectively. Spatial variations were also observed, with areas near the inlet surface having lower pollution concentrations and higher air speeds. In summary, this research contributes significantly to the establishment of a comprehensive database, combined with insights from rigorous experimentation and computational modeling, paves the way for advancements in smart indoor environmental control strategies.