dr. congxiao shang room no.: 01 37p email: [email protected] section 3: thermal comfort env-2d02...

Dr Congxiao Shang

Room No 01 37PEmail cshangueaacuk

Section 3 Thermal Comfort

ENV-2D02 (2006)Energy Conservation ndash power point versions of lectures

31 IntroductionMain objective To examine whether an environment is thermally comfortable at minimum energy consumption

No two people will react the same in a given environment

If all individual have the same clothing that when the temperature is at the optimum 25 --- too cold 25 ---- too hot

Voting is normally done on the ASHRAE scale ranging from -3 for too cold to +3 for too hot

People who vote with values lt-2 or gt +2 are those who are at the extremes

3 very hot

25

2 hot

15

1 slightly warm

05

0 neutral

-05

-1 slightly cool

-15

-2 cold

-25

-3 very cold

Extremes

Extremes

31 Introduction

The number of people voting at particular values follows a Gaussian (normal) distribution which has its peak at a mean vote of zero at an optimum setting

If we respond only to complaints from those who are feeling too cold or too hot then we are likely to find that more people will be dissatisfied as the curve will be shifted to hotter or colder end

people who are too cold complain more actively than the other way with the consequence that the temperature is often kept unnecessarily high

3 very hot

25

2 hot

15

1 slightly warm

05

0 neutral

-05

-1 slightly cool

-15

-2 cold

-25

-3 very cold

Extremes

Extremes

Main objective To examine whether an environment is thermally comfortable at minimum energy consumption

31 Introduction

Bear in mind for every 1oC the energy requirement rises by 8-10 (in the UK)

So We need to be objective in any response to complaints by investigating the overall situation - not just the immediate problem of one or two complainants

32 Thermal Comfort TheoryThe perception of thermal comfort for an individual depends on maintaining a balance between heat produced by body and heat losses Heat generated by body depending on metabolic rate --------H

Heat lost through respiration ----------------------------------R 1 Exhaust air is warmer than air taken in AND 2 it is more moist - latent heat of evaporation

Heat lost through evaporation from skin (sweat) -----------------E

So net heat generated by body is (Q) from metabolic

Q = H - R - E

32 Thermal Comfort Theory

To maintain a balance this heat of value Q must be ldquoremovedrdquo by radiation (Qr) and convection (Qc) from the clothing in an actual environment as follows

Net heat generated by body is (Q)

Q = H - R - E = Qr + Qc

If Q gt Qr + Qc

Q lt Qr + Qc

33 Factors affecting thermal comfort

a) The air temperatureb) The mean radiant temperaturec) The relative humidityd) The level of clothinge) The activity level (Kcalhr-1m-2)

f) The air velocity

33 Factors affecting thermal comfortAt a specific area the mean radiant temperature within the area is measured with a Globe Thermometer and is related to the exchange of heat between a person and hisher surroundings

However within a buildingWe should consider the position you are in the room for measurement

Different walls have different surface temperatures eg internal walls external walls windows etc The mean radiant temperature is different at different points for measurements in the building


However within a building

As an approximation the AVERAGE MEAN radiant temperature within a room may be estimated by the following ( surface areas x surface temperatures) total surface area

34 Calculation of average mean radiant temperature

It is actually a mean temporal mean spatial MRT

Example

Office Size 3m x 3m x 3m (typical of UEA)

Windows 2m high and full width of one wall

Internal surface temperature of windows 8oC

The external wall 18oC

The air-temperature 20oC

What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo

34 Calculation of average mean radiation temperature

double glazing

3m 3m

3m2m

How about with double glazing

The internal surface temperature of the windows would rise to around 14oC and the AMRT is1944oC rather than 1856oC

From the previous example a rise of 1oC in AMRT Rise of Mean Vote by around 011

Therefore There will be improvement through double glazing in this room Alternatively we could reduce the air temperature slightly to get the same equivalent comfort level

35 Computation of thermal comfort level

Actual Thermal Comfort Votes ndash For the analysis of a particular environment Thermal comfort experiments need to be done at particular conditions for a large number of individuals

Predicted Mean Vote (PMV)

1 Computer prediction with Fangerrsquos Equations

2 Manual use of the charts

CLO level from thermal comfort clothing chart

Their activity level

Air temperature

Humidity

Wind speed

Mean radiant temperture

A controlled environment

35 Computation of thermal comfort levelCharts and tables for PMV at specific conditions were produced according to both experimental data and Fangerrsquos Equations

1) select table for appropriate metabolic rate indicated by activity level2) select appropriate clothing level sub-table3) now read of vote value corresponding to air (dry-bulb) temperature and air velocity (ms) corresponding to wind speed

Now how to obtain the PMV via the tables for other environments5) Use the Humidity correction chart which gives the correction for each 1 variation in humidity from 506) Repeat for the Mean Radiant Temperature Correction chart ie for each 1oC that the MRT differs from the air (dry bulb) temperature7) Apply these corrections to the basic value to obtain the corrected PMV (predicted Mean Vote)8) Use further chart to estimate proportion of people likely to be dissatisfied with thermal environment

35 Thermal Comfort - ExampleAn office is 3m x 3m x 3m high with an external wall which is has a large 2m high window on the full width of the external wall facing North

Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Internal air in the building T = 195degC air velocity = 0

The mean radiant T at a workers desk- 17degC near the external wall - 185degC on the other sides of the room and - 20degC in a similar south facing room

An office worker wearing clothing with a CLO value of 10 and has an activity level of 60 kcal hr-1m-2 complains of being too cold

What action would you take

35 Thermal Comfort - Example

Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032

The same people at different activity levels may feel comfortable at different temp

The corrections for MRT difference

At 50 kcal hr-1m-2 correction is + 012 At 100 kcal hr-1m-2 correction is + 006

- Estimate Predicted Mean Vote (PMV)- Consider Strategies

At 60 kcal hr-1m-2

35 Thermal Comfort - ExampleAir Temp degC PMV

18 -075

20 -032

Known values

Air Temperature ordmC

By linear interpolation

Predicted Mean Vote at 195 degC =

-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2


Activity Level KcalHr-1m-2

MR

T

Co

rrec

tio

n

1006050

006

012




Hence the correction at 60 kcal hr-1m-2

012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence

ACTION-Moving the desk to the other side of the room or better still to a south facing office

- By complaining an office worker must be voting a PMV lt -2 and yet the above PMV is only slightly negative suggesting that the person always feels cold and should be encouraged to wear an extra sweater( Increasing the CLO value to 125 will increase the vote by about 03)

In North facing Office near window

PMV = - 043 + 011 (17-195 ) = - 069on other side of officePMV = - 043 + 011 (185 -195 ) = - 054in south facing officePMV = - 043 + 011 (20-195) = - 037

Thermal Comfort Study Arts 301 25th January 2006 Sample Size 26

Metabolic Rate Clo Actual PMV Actual Predicted MRT Dry Wet

all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023

unknown sex 58 115 048front of class 58 079 042

middle 58 121 016window 58 125 049

dissatisfied Hot represent people voting +2 or morePredictions are reasonable for large numbers eg gt100

Vote dissatisfied Hot

Time seated Activity Level (Kcalhr-1m-2) ~ 5 minutes 70 ~ 15 minutes 60 ~ 30 minutes 55 ~ 60 minutes 50 ~ 90 minutes 45 gt 2 hours 40

80 Kcalhr-1m-2 for a person who is standing

-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re

Actual PMVMRT DryWet

36 Thermal comfort summeryThermal Comfort measurements may be used to assess a given environment and are a useful additional aspect of Energy ManagementThe level of comfort may be predicted using Fangers Equations however you should note the following

It is difficult to accurately assess metabolic rate and there is a tendency to underestimate value for people who are seated unless they have been in the particular Environment and at the particular activity level for at least an hour

Fangers Theory strictly applies only to individuals having the same clothing but taking the mean values of a large number of votes should give the same as Fangerrsquos

If actual votes are available then we can still use Thermal Comfort Tables made under standard conditions or the computer to assess the effects of changes in the Environmental Conditions on the mean VOTE

Rarely is actual thermal comfort data used in Energy Management Decisions - responses are usually made for those who feel too cold without identifying the real problem

Correction charts for the increment of PMV for each 1 variation in humidity from 50

Correction charts for the increment of predicted mean vote for each 1oC variation of mean radiant temperature from the air (dry-bulb) temperature

PMV (predicted mean vote)

bull It represents on a thermal sensation scale of the mean vote of a large population of people exposed to a certain environment

bull It is derived from the physics of heat transfer combined with an empirical fit to sensation

bull It establishes a thermal strain based on steady-state heat transfer between the body and the environment and assigns a comfort vote to that amount of strain

bull The PMV equation for thermal comfort is an empirical equation for predicting the mean vote on a ordinal category rating scale of thermal comfort of a population of people (not required here)

bull PMV gt 0 towards hot discomfort PMV lt 0 towards cold discomfort

Note Thermal comfort- Clothing (ldquoCLOrdquo)

ndash 1048708 ldquoCLOrdquo is a CLOthing insulation unit (Icl)

ndash 1048708 1 clo = 0155 m2 degCW

ndash 1048708 Lowest clo value is 0 (naked body)

ndash 1048708 Highest practical clo value = 4 clo (Eskimo clothing fur pants coat hood gloves etc)

ndash 1048708 Summer clothing ~ 06 clo

ndash 1048708 Winter clothing ~ 1 clo


31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20

36 Thermal comfort summery

Slide 22

Slide 23



31 IntroductionMain objective To examine whether an environment is thermally comfortable at minimum energy consumption

No two people will react the same in a given environment

If all individual have the same clothing that when the temperature is at the optimum 25 --- too cold 25 ---- too hot

Voting is normally done on the ASHRAE scale ranging from -3 for too cold to +3 for too hot

People who vote with values lt-2 or gt +2 are those who are at the extremes

3 very hot

25

2 hot

15

1 slightly warm

05

0 neutral

-05

-1 slightly cool

-15

-2 cold

-25

-3 very cold

Extremes

Extremes

31 Introduction




3 very hot

25

2 hot

15

1 slightly warm

05

0 neutral

-05

-1 slightly cool

-15

-2 cold

-25

-3 very cold

Extremes

Extremes


31 Introduction







Q = H - R - E




Q = H - R - E = Qr + Qc

If Q gt Qr + Qc

Q lt Qr + Qc



f) The air velocity









Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23



31 Introduction




3 very hot

25

2 hot

15

1 slightly warm

05

0 neutral

-05

-1 slightly cool

-15

-2 cold

-25

-3 very cold

Extremes

Extremes


31 Introduction







Q = H - R - E




Q = H - R - E = Qr + Qc

If Q gt Qr + Qc

Q lt Qr + Qc



f) The air velocity









Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23



31 Introduction







Q = H - R - E




Q = H - R - E = Qr + Qc

If Q gt Qr + Qc

Q lt Qr + Qc



f) The air velocity









Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23







Q = H - R - E




Q = H - R - E = Qr + Qc

If Q gt Qr + Qc

Q lt Qr + Qc



f) The air velocity









Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23






Q = H - R - E = Qr + Qc

If Q gt Qr + Qc

Q lt Qr + Qc



f) The air velocity









Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23





f) The air velocity









Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23











Example






What is AMRT

3m 3m

3m2m

5 3 3 20 1 3 18 2 3 8

6 3 3

334

1818 56

x x x x x x x

x xCo


double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23




double glazing

3m 3m

3m2m












Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23










Air temperature

Humidity

Wind speed







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23







Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3






Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23




Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Air Temp degC PMV

18 -075

20 -032





At 60 kcal hr-1m-2


18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23




18 -075

20 -032

Known values




-075 + (195 - 18) [-032- (-075)] (20-18) = - 043

PM

V

18 2019195

-075

-032

21

A

BC

Crsquo Brsquo

At 60 kcal hr-1m-2



MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23





MR

T

Co

rrec

tio

n

1006050

006

012





012 ndash (60-50) x [(012-006) (100-50)] = 011


Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23




Window

N

3

3

2

1

20ordmC

17ordmC

(195ordmC)

185

ordmC

185

ordmC3

Hence







all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23





all data 58 115 028 022 263 480 213 203 1630905 70 116 071 060 769 950 220 202 1620930 55 115 017 012 000 360 215 202 1630945 50 117 -001 -014 000 160 205 204 164

males 58 117 030females 58 116 023


middle 58 121 016window 58 125 049





-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23



-05

00

05

10

15

20

25

all data 0905 0930 0945

Vot

e

-5

0

5

10

15

20

25

Tem

per

atu

re























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23
























31 Introduction

Slide 3

Slide 4


Slide 6


Slide 8

Slide 9




Slide 13


Slide 15

Slide 16

Slide 17

Slide 18

Slide 19

Slide 20


Slide 22

Slide 23



dr. congxiao shang room no.: 01 37p email: [email protected] section 3: thermal comfort env-2d02...

Documents

mean radiant temperature

thermal comfort theory

perception of thermal

thermal comfort experiments

qc slide

e slide

thermal comfort clothing

equivalent comfort level