Building Design

Human Thermal Comfort

[this article adapted from Andrew Marsh's Ecotect Natural Frequency Wiki]

Energy-efficient buildings are only effective when the occupants of the buildings are comfortable. If they are not comfortable, then they will take alternative means of heating or cooling a space such as space heaters or window-mounted air conditioners that could be substantially worse than typical Heating, Ventilation and Air Conditioning (HVAC) systems.

Thermal comfort is difficult to measure because it is highly subjective. It depends on the air temperature, humidity, radiant temperature, air speeds, activity rates, and clothing levels. However, each individual experiences these sensations a bit differently based on his or her physiology and state. 

A cold sensation will be pleasing when the body is overheated, but unpleasant when the core is already cold. At the same time, the temperature of the skin is not uniform on all areas of the body. There are variations in different parts of the body which reflect the variations in blood flow and subcutaneous fat. The insulative quality of clothing also has a marked effect on the level and distribution of skin temperature.

Thus, sensation from any particular part of the skin will depend on time, location and clothing, as well as the temperature of the surroundings.

Factors in Human Comfort

Use the widget below to get an intuitive sense for the factors that play into human comfort, and what makes us too hot or too cold. Drag the sliders with your mouse to experiment with different values.

 
 

Predicted Mean Vote (PMV)

The widget above is actually an interactive Predicted Mean Vote (PMV) Calculator. 

The Predicted Mean Vote (PMV) refers to a thermal scale that runs from Cold (-3) to Hot (+3), originally developed by Fanger and later adopted as an ISO standard. The original data was collected by subjecting a large number of people (reputedly many thousands of Isreali soldiers) to different conditions within a climate chamber and having them select a position on the scale the best described their comfort sensation. A mathematical model of the relationship between all the environmental and physiological factors considered was then derived from the data. It wasn't actually as simple as that, as the fundamentals of the equation are actually based on a physical analysis of the thermal exchanges and then modified slightly to fit the data, however it's a fair summary. For those who wish to know all the gory detail please read on.

(See this Ecotect tutorial on designing for Human Comfort that talks about PMV)

 

The math behind PMV

From the PMV, the Predicted Percentage of Dissatisfied people (PPD) can be determined. As PMV moves away from neutral (PMV = 0) in either direction, PPD increases. The maximum number of people dissatisfied with their comfort conditions is 100% and, as you can never please all of the people all of the time, the minimum number even in what would be considered perfectly comfortable conditions is 5%.

The PMV equation for thermal comfort is a steady-state model. It is an empirical equation for predicting the average vote of a large number of people on a 7 point scale (-3 to +3) of thermal comfort. The equation uses the steady state heat balance of the human body and develops a link between the thermal comfort vote and the degree of stress or load on the body (e.g sweating, vasoconstriction, vasodilation) caused by any deviation from perfect balance. The greater the load, the more the comfort vote will deviate from zero.

The partial derivative of the load function is estimated by exposing enough people to enough different conditions to fit a curve. PMV is arguably the most widely used thermal comfort index today. The ISO (International Standards Organization) Standard 7730 (ISO 1984), "Moderate Thermal Environments - Determination of the PMV and PPD Indices and Specification of the Conditions for Thermal Comfort," uses limits on PMV as an explicit definition of the comfort zone.

The PMV equation only applies to humans exposed for a long period to constant conditions at a constant metabolic rate. Conservation of energy leads to the following heat balance equation:

H - Ed - Esw- Ere - L = R + C

Where: H = internal heat production, Ed = heat loss due to water vapor diffusion through the skin, Esw = heat loss due to sweating, Ere = latent heat lossdue to respiration, L = dry respiration heat loss, R = heat loss by radiation from the surface of a clothed body, C = heat loss by convection from the surface of a clothed body

The equation is expanded by substituting each component with a function derivable from basic physics. All of the functions have measurable values with the exception of clothing surface temperature and the convective heat transfer coefficient which are functions of each other. To solve the equation, an initial value of clothing temperature is estimated, the convective heat transfer coefficient is then computed, and a new clothing temperature calculated etc. This is continued by iteration until both are known to a satisfactory degree. If the body is assumed not to be in thermal balance, the heat equation can be re-written as:

L = H - Ed - Esw - Ere - R - C

Where: L is the thermal load on the body.

Define thermal strain or sensation Y as some unknown function of L and metabolic rate. Holding all variables constant except air temperature and metabolic rate, we use mean votes from climate chamber experiments to write Y as function of air temperature for several activity levels. Then substituting L for air temperature, determined from the heat balance equation above, evaluate the partial derivative of Y with respect to L at Y=0 and plot the points versus metabolic rate. An exponential curve is fit to the points and integrated with respect to LL is simply renamed "PMV" and we have (in simplified form):

PMV = exp(Met) * L

PMV is "scaled" to predict thermal sensation votes on a seven point scale (hot 3, warm 2, slightly warm 1, neutral 0, slightly cool -1, cool -2, cold -3) by virtue of the fact that for each physical condition, Y is the mean vote of all subjects exposed to that condition. The major limitation of the PMV model is the explicit constraint of skin temperature and evaporative heat loss to values for comfort and 'neutral' sensation at a given activity level.

Figure 5 - Predicted Mean Vote values plotted on the Psychrometric Chart,
showing variation with DBT and RH for a person standing around in a light
business suit in a pleasant breeze and next to a reasonably warm window.

Adaptive Comfort

Adaptive comfort models add a little more human behaviour to the mix. They assume that, if changes occur in the thermal environment to produce discomfort, then people will generally change their behaviour and act in a way that will restore their comfort. Such actions could include taking off clothing, reducing activity levels or even opening a window. The main effect of such models is to increase the range of conditions that designers can consider as comfortable, especially in naturally ventilated buildings where the occupants have a greater degree of control over their thermal environment.

Table 1 - The effect of adaptive behaviours on optimum comfort temperatures. Taken from BRE
BEHAVIOUR EFFECT OFFSET
Jumper/Jacket on or off Changes Clo by ± 0.35 ± 2.2K
Tight fit/Loose fit clothing Changes Clo by ± 0.26 ± 1.7K
Collar and tie on or off Changes Clo by ± 0.13 ± 0.8K
Office chair type Changes Clo by ± 0.05 ± 0.3K
Seated or walking around Varies Met by ± 0.4 ± 3.4K
Stress level Varies Met by ± 0.3 ± 2.6K
Vigour of activity Varies Met by ± 0.1 ± 0.9K
Different postures Varies Met by ± 10% ± 0.9K
Consume cold drink Varies Met by -0.12 + 0.9K
Consume hot drink/food Varies Met by +0.12 - 0.9K
Operate desk fan Varies Vel by +2.0m/s + 2.8K
Operate ceiling fan Varies Vel by +1.0m/s + 2.2K
Open window Varies Vel by +0.5m/s + 1.1K
 

As they depend on human behaviour so much, adaptive models are usually based on extensive surveys of thermal comfort and indoor/outdoor conditions. This research clearly shows that providing people with the means to control their local environment greatly increases the percentage of satisfied occupants and makes them more forgiving of occasional periods of poor performance. Humphreys & Nicol (1998) give equations for calculating the indoor comfort temperature from outdoor monthly mean temperature as follows.

Free Running Building:

Tc = 11.9 + 0.534 Tave

Heated or Cooled Building:

Tc = 23.9 + 0.295(Tave-22) exp([-(Tave-22)/33.941]²)

Unknown system (an average of all buildings):

Tc = 24.2 + 0.43(Tave-22) exp(-[(Tave-22)/28.284]²)

The following graphs show these relationships using a rolling mean monthly average outdoor temperature (from d-15 to d+15). The different formula can give quite different values so their appropriate application is advised. Use the free running method for any building in which the occupants can directly control their own local environment, with fans, lights and operable windows. The heated and cooled formula is more applicable to fully thermostatically controlled air-conditioned buildings. 

Figure 3 - Comfort zones plotted against outdoor dry bulb temperature (blue).

 

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