CFD has long been an important
tool in the prediction of thermal comfort in occupied spaces.
However, despite a proven track record in accurately predicing
physical quantities such as temperature and velocity, relating
primative flow variables to the degree of thermal comfort
actually experiened by an occupant is much more difficult.
Although the level of thermal comfort experienced obviously
depends on the local flow environment and the exposure
of the occupant to thermal radiation, individual human
beings respond in a subjective way to the local heat transfer
in different parts of their bodies.
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Fig. 1: Three climate evaluation methods: human subjective ratings, manikin
measurements and computer modeling |
Fig. 2: Flow tracks around MANIKIN3 inside
the virtual calibration chamber " dressed" in
the same clothing as the physical MANIKIN2
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Fig. 3: MANIKIN3 and computer inside the virtual office equipped
with mixing ventilation
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Thermal sensation ratings provided by panels of subjects are probably still
the most objective way to gather information about the effects of different
thermal climates. However, the work with panels is expensive and time consuming,
as well as difficult to standardize and use for predictions. As a response
to this, artificial human shaped mannequins are increasingly used in-place
of actual human subjects. Measurements in various parts of the mannequin’s
body in a specially controlled thermal environment can be correlated to the
responses from panels of real human beings in an identical situation.
This article describes work performed to construct a numerical thermal mannequin
known as ”MANIKIN3” using STAR-CD, from data collected by an
existing physical thermal mannequin “MANIKIN2” as well as more
than 500 experiments with subjects. (Fig.1)
The first problem to overcome when constructing such a model is how to define
a simple, yet effective measure of thermal comfort. One of the best measures
is the equivalent temperature (teq), which is a measure of the effects of
non-evaporative heat loss from the human body. The major advantage of this
measure is that it expresses the combined effects of thermal influences in
a single figure that is easy to interpret and explain. It is consequently
particularly useful for local assessment of complex climatic conditions.
| Action |
Influence |
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| Increased air speed |
Lower teq |
| Decreased air temperature |
Lower teq |
| Decreased mean radiant temperature |
Lower teq |
| Decreased air speed |
Higher teq |
| ncreased air temperature |
Higher teq |
| Increased mean radiant temperature |
Higher teq |
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The relationship between
changes in different thermal factors and the change
in equivalent temperature
Single measurements of thermal factors do not account for all effects on
a human body. Human shaped thermal manikins measure equivalent temperature
over the whole surface, in all directions simultaneously. Consequently new,
extended definitions of the concept of equivalent temperature have also been
developed, along with theories describing equivalent temperature as a vector-valued
function. These new theories are used to make more efficient computer codes
and increase the understanding of measurement differences.
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Fig. 4: Comfort zone diagram for 16
segments of the body for the case with mixing
ventilation (Notice the measured and simulated
seat zones)
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Fig. 5: MANIKIN2 inside the vehicle
simulator exposed to the artificial sun
at the Swedish Institute for Agricultural
and Environmental Engineering
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The virtual MANIKIN3 has been formulated to be identical
in size, area and number of zones to the real MANIKIN2.
Calibration is carried out by locating the computational
MANIKIN3 in a fictitious chamber. This arrangement gives
an ideal environment for the determination of the heat
transfer coefficients needed for the equivalent temperature
calculations (Fig. 2).
In order to investigate how well CFD calculations can predict the effects
of different climate situations, a number of reference cases have been carried
out.
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Fig. 6a & b: Temperature fields with reflective
(adove) and clear glass (below) (Note the heating
effects from the manikin and the untreated
windows) |
The office room case
This first investigation was a part of the Swedish project called "The
Healthy Building" that investigated how the use of modern calculation
tools can improve the thermal climate in buildings. MANIKIN3 had no problem
simulating the increased insulation of the seat zones supplied by the virtual
office chair. The office CFD simulations produced slightly higher equivalent
temperatures due to a lower simulated air temperature (Fig. 3 & 4).
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Fig. 7: The first picture of MANIKIN4 made with methods for manikin shape
reconstruction from point cloud data (Scanned with a CYRA Cyclone
(Cyra Technologies Inc.) at the University of Gävle) |
The vehicle simulator case
This second study was a part of a research project investigating how the
use of "special glazing" can improve the thermal climate inside
a vehicle.
In this study a small climatic test cabin, a vehicle simulator, was positioned
in a large climatic chamber (Fig. 5). The intensity of the transmitted solar
radiation varied with the glazing tested. The supplied air was distributed
through defroster and panel inlets in the front and at the doors. The two
outlets were positioned at the back wall (Fig. 6a & b). The calculated
results from this study show good agreement with the measurements made with
MANIKIN2. Some deviations were found at the hands and the zones at the middle
of the mannequin. MANIKIN3 simulates the reduced insulation of the ventilated
seat well.
Conclusions
The objective of this work is to use and develop computer-based methods to
visualize, analyze, and evaluate thermal climate in order to improve the
environmental conditions. The methods are used to find useful system solutions
that provide improved thermal climate in many different situations, e.g.
homes, schools, offices, cars, trucks, and trains. The cubical MANIKIN3 is
sufficient for most engineering calculations, but it is interesting from
a research point of view to further develop the similarities between reality
and the CFD model.
For further information, contact: hakann@kth.se
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