Indoor thermal stratification and its statistical distribution.

Area of Science:

• Building physics
• Environmental engineering
• Fluid dynamics

Background:

• Thermal stratification occurs in various indoor environments due to buoyancy-driven air movement.
• Common in large buildings, ventilated spaces, and fire scenarios with distinct hot and cold air layers.
• Understanding vertical temperature distribution is crucial for HVAC design and safety.

Purpose of the Study:

• To investigate the statistical distribution of indoor thermal stratification.
• To establish a predictive model for vertical temperature profiles.
• To demonstrate practical applications of the proposed methodology.

Main Methods:

• Analysis of indoor environment temperature data.
• Application of statistical distribution modeling, specifically the Beta distribution.
• Validation using field measurements from five warehouse-type buildings and eleven literature studies.

Main Results:

• Indoor thermal stratification follows the statistical Beta distribution, characterized by two shape parameters (Alpha and Beta).
• Vertical temperature profiles can be accurately estimated using as few as two or four temperature points.
• The methodology proved effective across diverse ventilation types and heat sources.

Conclusions:

• The Beta distribution provides a robust framework for characterizing indoor thermal stratification.
• A simplified, data-efficient method for estimating temperature profiles is now available.
• The dimensionless approach has potential applications in other indoor stratification phenomena.