Sustainable Architecture Applied to Replicable Public Access Buildings
Module 5
Thermal mass and comfort:
the role of time
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Plan
Sustainable
Architecture Applied
to Replicable Public
Access Buildings
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Contract:
TREN/04/FP6EN/S07.31838/50
3118
1. Thermal mass and comfort:
the role of time
2. An example from India
3. Control temperature based on the
Adaptive Model
4. Adaptive in SARA project
The adaptive approach to
thermal comfort (1)
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• The adaptive approach assumes an
adaptive principle:
• If a change occurs such as to produce
discomfort, people react in ways which
tend to restore their comfort.
• These changes take place over varying
time periods and may be changes
made to the environment or to the
person:
The adaptive approach to
thermal comfort (2)
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• The adaptive approach therefore sees
comfort as part of an interaction between
buildings and occupants in the context of
culture and climate.
• Comfort temperature changes with
changes of clothing and other factors with
weather and season
• The feed-back nature of the system has led
to reproducible results
Generalising from field studies I
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35
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Comfort temperature
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30
Europe
Pakistan
Humphreys
25
20
15
10
15
20
25
30
Mean temperature experienced
35
40
Characteristic time periods
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• Instantaneous – particularly the taking on
or off of clothing in response to – or
anticipation of – a change in conditions
(e.g. going out of doors)
• Within day - responses to a change in the
environment within the day
• Day to day – e.g. reactions to changes in
the weather
• Longer term – resulting from the changing
seasons, often driven by the prevailing
culture.
Generalising from field studies
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• The indoor temperature in a particular
building is not always known
• But the indoor temperature in buildings
without heating or cooling (freerunning) generally follows the outdoor
temperature
• In these buildings the comfort
temperature will therefore also follow
the outdoor temperature:
Generalising from field studies II
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3118
Neutral or comfort temperatureoC
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AC buildings, line B
34
Free-running buildings, line A
32
30
28
A
26
B
24
22
20
18
16
Tn = To
14
12
-24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2
0
2
4
6
8 10 12 14 16 18 20 22 24 26 28 30 32 34
Monthly mean outdoor temperature oC
Each point on the graph is the mean from a particular survey
Over what time period?
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Contract:
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• Comfort temperature changes with outdoor
temperature: this does not happen
instantaneously, but over time
• A full investigation would require time-series
analysis, but this is very difficult unless the data
are complete and continuous.
• Most comfort data come from offices and are
therefore intermittent and separated by nights
and weekends
• A time series must therefore be assumed
Exponentially weighted running
mean temperature
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Trm = (1-).{Tod-1 + .Tod-2 +2Tod-3…..}
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Trmn = (1-).Todn-1 + .Trmn-1
 is a constant ( < 1),
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Trm Running mean temperature
Trmn is Trm on day n
In this database TrmX = Trm for  = X/100
Tod Daily mean temperature
Running mean temperature
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Outdoor temperatures in Oxford for June/July 1996
25
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Temperature
20
15
10
5
6/1/96
6/11/96
daily mean To
6/21/96
Trm33
7/1/96
Trm80
7/11/96
Tr0.90
7/21/96
Trm99
Deciding the optimal time
constant for the time series
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• The greater the value of  the more slowly
the time series changes
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• Data from field surveys in Europe allow us
to estimate the best value for 
• We can calculate the correlation
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TREN/04/FP6EN/S07.31838/50
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• coefficient of comfort temperature (Tc)
on different values of Trm
Correlation of comfort temperature (Tc) and daily
mean outdoor temperature (Tod)
with Trm for increasing values of . (1)
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0.25
Correlation with running mean
temperature
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1
0.2
0.8
0.15
Tod
Tc
0.6
0.4
0.2
Maximum correlation
with Tc when  is
about 0.8 (TR80)
0.1
0.05
0
0.2
0
0.4
0.6
0.8
Time constant for running mean 
1
Correlation of comfort temperature (Tc) and
daily mean outdoor temperature (Tod)
with Trm for increasing values of . (2)
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• The maximum correlation occurs when the
value of  is 0.8
• This implies that the comfort temperature
• changes in an exponential manner with a
half-life of about 4 days
1
Graph showing
the relative
change of
Tod
Trm80 following
Trm80
a step change
of temperature
Contract:
TREN/04/FP6EN/S07.31838/50
3118
0.5
on day 0
0
-3 -2 -1
0
1
2
3
4
5
6
7
8
9
10 11 12 13
Buildings
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How are the needs of thermal comfort
reflected in buildings?
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TREN/04/FP6EN/S07.31838/50
3118
40
TL
35
30
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temperature
AO
25
AI
20
15
10
5
0
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3118
0
5
10
15
20
25
30
35
40
45
50
t ime
External Temperature
modulation
Internal Temperature
modulation
Time Lag = tL
Decrement Factor = AI /AO
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T-Tc
Contract:
TREN/04/FP6EN/S07.31838/50
3118
Increasing
Discomfort
Conclusions
Sustainable
Architecture Applied
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Contract:
TREN/04/FP6EN/S07.31838/50
3118
• People can adapt to a range of
temperatures
• However they take time to adjust to changes
in the temperature
• A heavyweight construction helps in two
ways:
1. the mean temperature changes more
slowly
2. the daily range of temperature is reduced
• Free-running heavy-weight buildings are
therefore more likely to be comfortable.
Sustainable Architecture Applied to Replicable Public Access Buildings
2. An example
from India
Hotel Suraj in Jaisalmer in the Thar
desert of Rajistan
With acknowledgements to: Dr Jane Matthews BA,
MSc, PhD
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The design of
the building
allows for a
variety of forms
with varying
thermal mass
characteristics
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The massive but airy principal reception room
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The heavy-weight
staircase
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The structure with thick mud floors and plenty of air
penetration
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Lightweight character of the upper floor
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Thermal mass is exploited to
provide variety throughout
the building
Increasing Time lag
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Increasing Time lag
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Daily mean temperatures outdoors and in the
basement over one year, illustrating an annual
decrement factor and time-lag
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33
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temp (deg C)
29
27
Basement
25
expo. w=0.035
23
21
19
17
15
26-Aug
14-Oct
2-Dec
20-Jan
9-Mar
27-Apr
date
15-Jun
3-Aug
21-Sep
9-Nov
Sustainable Architecture Applied to Replicable Public Access Buildings
3. Control temperature based on the
Adaptive Model
www.sara-project.net
State of the art review
Sustainable
Architecture Applied
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• The International Standard for indoor temperatures
favours the provision of constant temperatures in
buildings.
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• Research analysing field work throughout the world
has shown that the temperature which people find
comfortable varies with season and climate.
Contract:
TREN/04/FP6EN/S07.31838/50
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• Recent work has suggests that the comfort
temperature indoors can be defined by a timeseries of the outdoor temperature.
State of the art review (1)
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• This means that comfort can be achieved
using less energy because the indoor
temperature follows that outdoors.
• It also means that well designed buildings
can fall within the range of temperatures
which are comfortable without the use of
air conditioning.
State of the art review (2)
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• An algorithm was developed for the prediction of
comfort temperatures in buildings using the outdoor
temperature.
• This algorithm has been tested for UK and EC
conditions using dynamic thermal simulations and
was also tested in actual buildings.
Contract:
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• The use of such an algorithm can be shown to
produce energy savings of up to 25% when it is used
to define the set temperature in air conditioned
and partially mechanically ventilated buildings.
State of the art review (3)
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• In air conditioned (AC) buildings this is used as the
set-point temperature.
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• In NV buildings the same input information will be
used to assess whether the building is likely to
provide indoor comfort.
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• This means that it is more dependent on the exact
nature of the building and the controls over indoor
conditions which it affords.
Developing the adaptive
mechanism (1)
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Main assumption
• The approach is based on the assumption that
the comfort temperature is changing with time
in a way which is related to the outdoor
temperature.
Developing the adaptive
mechanism (2)
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•The comfort temperature (Tc) can be
calculated from the value of the globe
temperature (Tg) and the thermal comfort
vote (TF) using the equations:
TF = a Tg + b
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The globe temperature is used as an
approximation to the operative temperature.
Developing the adaptive
mechanism (3)
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• One problem for the adaptive approach to thermal
comfort, which relates the comfort temperature
inside buildings to the outdoor temperature is to
characterise the rate at which the comfort
temperature changes.
• A common measure of outdoor temperature used
as a predictor for indoor comfort temperature is the
exponentially-weighted running mean of the daily
mean outdoor temperature.
Trm = (1-).{Tod-1 + .Tod-2 + 2Tod-3…..}
Developing the adaptive
mechanism (4)
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• The way in which the running mean
temperature changes is equivalent to the
decay of a radioactive source with a
characteristic half-life.
• The use of an infinite series would be very time
consuming but it can easily be reduced to
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• The values of and a, b,  can be determined
by using statistical analysis.
Trmn = (1-).Todn-1 + .Trmn-1
Thermal Comfort Surveys-SCAT
project (1)
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• 25 buildings were surveyed across the UK, France,
Sweden, Greece and Portugal by members of the
SCATs consortium.
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• This data formed 3 distinct databases of thermal
comfort
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• The data collected included indoor and outdoor
temperatures, thermal comfort responses, occupant
use of controls, demographic data of building
occupants, clothing insulation and metabolic rate.
• Approximately 25000 responses are available for
analysis
Thermal Comfort Surveys-SCAT
project (2)
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• Temperature - comfort vote (7 point scale) and
preference (5 point scale)
• Air movement - comfort vote (7 point scale) and
preference (5 point scale)
• Humidity -comfort vote (7 point scale) and preference
(5 point scale)
• Lighting - comfort vote (7 point scale) and preference
(5 point scale)
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• Noise - comfort vote (7 point scale) and preference
(5 point scale)
• Air quality vote (7 point scale)
• Overall comfort (6 point scale)
• Perceived productivity (5 point scale)
The adaptive algorithm
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UK
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Tr80 < 10 oC
Tr80 > 10 oC
Tc = 22.9 oC
Tc = 0.302*Tr80 + 19.4
=0.2
Developing Controls (1)
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What has to be implemented at BMS level is the following:
• The actual outdoor temperature is measured once
every hour, added up, and the average outdoor
temperature.
• The Running mean temperature is calculated as:
TRMn =  * TDMn-1 + (1- ) * TRMn-1
Contract:
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• TRM = Running mean temperature
• TDM = Actual average temperature
•  is set default to 0.2.
Developing Controls (2)
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The Control temperature is calculated as
• If the running mean temperature is below 10 °C,
the Control temperature is set to a fixed value of
22.88 °C.
• In other cases, the Control temperature is
calculated as:
Contract:
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Tc = a * TRM + b
Where :
- a = 0.302
- b = 19.39
Sustainable Architecture Applied to Replicable Public Access Buildings
4. Adaptative Control in the SARA project
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Adaptative Control in the SARA
project (1)
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•
The control algorithm is used to calculate the
comfort temperature setpoint at the BMS level
depending on the historical outdoor
temperature in a very specific way explained
elsewhere. The comfort temperature setpoint is
then used to control the indoor temperature.
What has to be implemented at BMS level is the
following:
The actual outdoor temperature is measured
once every hour, added up, and the average
outdoor temperature is calculated once every
day at 7 o’clock (no adjustment for daylight
saving time).
Adaptative Control in the SARA
project (2)
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•
The Running mean temperature is
calculated as:
–
–
–
TRM = Running mean temperature
TDM = Actual average temperature
TRMn = c * TDMn-1 + (1-c) * TRMn-1where the
constant c is set default to 0.2.
Adaptative Control in the SARA
project (3)
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Contract:
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•
The Running mean temperature is
calculated as:
–
–
–
TRM = Running mean temperature
TDM = Actual average temperature
TRMn = c * TDMn-1 + (1-c) * TRMn-1where the
constant c is set default to 0.2.
Adaptative Control in the SARA
project (4)
Sustainable
Architecture Applied
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•
The Control temperature is calculated as
•
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•
If the running mean temperature is below 10 °C,
the Control temperature is set to a fixed value of
22.88 °C.
In other cases, the Control temperature is:
-
Contract:
TREN/04/FP6EN/S07.31838/50
3118
Tc = a * TRM + b
where a = 0.302 and b = 19.39
Contr ol temperature
PVR

10
Control temperature
PVR


0.3 02
PVR
PVR
19 .39
22 .88
Running mean temperature(°C)
If Trm80 is less than or equal to 10oC, Tc = 22.88oC
If Trm80 is greater than 10oC, Tc = a * Trm80 + b
Adaptative Control in the SARA
project (5)
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Contract:
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This algorithm was
implemented at the BMS level
in December 2007 and it is
running in part of the building.