Thermal Comfort

Thermal comfort is an important aspect of indoor environments has significant effect on human a being overall satisfaction. Poor thermal comfort parameters can affect a person's health and day to day activity in the environment. Achieving optimal thermal comfort is essential in various settings, including residential buildings, offices, schools, and industrial spaces.

To quantify thermal comfort, parameters such as the Predicted Mean Vote (PMV) and the Predicted Percentage of Dissatisfaction (PPD) indices are an effective way to determine the thermal comfort in an environment. The PMV index predicts the average thermal comfort of an environment based on factors such as air temperature, humidity, air velocity, mean radiant temperature, metabolic rate, and clothing insulation. The PPD index, derived from the PMV, estimates the percentage of people likely to feel discomfort under specific thermal conditions.

By accurately calculating PMV and PPD, engineers and building designers can optimize HVAC systems, enhance energy efficiency, and improve occupant comfort. This project focuses on the evaluation of thermal comfort using PMV and PPD models, exploring their applications, influencing factors, and implications for building design and environmental control. 

The PMV PPD setup was simulated in OpenFOAM. Although OpenFOAM has a PMV PPD library, it does not include important aspects of the calculation and treats most of the values as constant. A new library was built upon the original library to take variability of the calculation parameters to predict thermal comfort accurately. The new library also includes a radiation model to calculate the the effect of Mean Radiant Temperature.

The plot below shows the relation between PMV and PPD.

More details on PMV PPD can be found here: https://www.simscale.com/blog/what-is-pmv-ppd/

In this project, we evaluate the thermal comfort of a human being in a room with a small heat source and an AC vent. 

Simulation Settings:

Solver: buoyantSimpleFoam(for SteadyState, Buoyant, Incompressible, Turbulent flows)

Radiation model:  fvDOM (Discrete Ordinates Method)

Relative Humidity: 50% 

Clothing Factor : 0.5

Metabolic rate: 1.2

Inlet: 0.2 m/s at 285K

Outlet: 0 Pa inletOutlet at 298.15K

Result

The image above shows a human being present inside the room. On his left, an AC vent with an inlet velocity of 0.2 m/s enters the room. The air exits the room through the door with 0 Pa outlet boundary condition. The image shows the PMV contour inside the room. It is clearly visible from the image that the man present inside the room feels slightly warm on his right side due to high mean radiant temperature due to the heat source . Moreover, the roof above also has a higher temperature which makes the human head slightly warmer. This highlights the importance of accounting for variable radiation temperature in PMV calculation. On the left side, the man feels a bit cool due to the effect the AC vent. 

The image shows the PPD contour inside the room. It is observable from the image that the man present inside the room has a PPD value of 5%, which show his high satisfaction level while the wall are atthe highest dissatifaction level. It is worth mentioning here that although our heat flux source had a higher temperature and PMV level compared to heat source, still it has lower dissatisfaction level compared to other surfaces. This is because, the walls here are cool to the extent that the temperature near the wall is cold enough to make it uncomfortable for people, while the heat source is at a temperature where it provides right the amount of heat.