a real-time portable thermal comfort measurement …library.tni.ac.th/thesis/upload/files/thesis...

A REAL-TIME PORTABLE THERMAL COMFORT MEASUREMENT DEVICE

THROUGH COMMERCIALLY AVAILABLE RASPBERRY PI 3

MICROCONTROLLER.

Metinee Rodoum

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Engineering Program in Engineering Technology Graduate School

Thai-Nichi Institute of Technology

Academic Year 2016

Thesis Title. A Real-Time Portable Thermal Comfort Measurement

Device Through Commercially Available Raspberry pi3

Microcontroller.

By Metinee Rodoum

Field of Study Engineering Technology

Advisor Asst. Prof. Dr. Wimol San-Um

The Graduate School of Thai-Nichi Institute of Technology has been approved

and accepted as partial fulfillment of the requirements for the Master’s Degree

..…………………………………………Dean of Graduate School

(Assoc. Prof. Dr. Pichit Sukchareonpong)

Month………. Date………., Year……

Thesis Committees

...………………………………………….Chairperson

(Asst. Prof. Dr. Surapong Pongyupinpanich)

..…………………………………………Committee

(Dr. Phaisarn Sudwilai)

...…………………………………………Committee

(Asst. Prof. Dr. Warakorn Srichavengsup)

...…………………………………………Advisor

(Asst. Prof. Dr. Wimol San-Um)

iii

METINEE RODOUM: A REAL-TIME PORTABLE THERMAL

COMFORT MEASUREMENT DEVICE THROUGH COMMERCIALLY

AVAILABLE RASPBERRY PI3 MICROCONTROLLER. ADVISOR:

ASST. PROF. DR. WIMOL SAN-UM, 52PP.

It has been reported that primary energy consumption in household and

commercial building consumes approximately 40% of the total energy consumption.

The need for energy reduction is ultimately required for anera of energy resource

shortage. One approach to assist energy reduction is a consideration of Thermal

Comfort which is a state of human mind, indicating the level of comfort based on the

ASHRAE thermal sensation scale standard in which the Predicted Mean Vote (PMV)

is exploited as a standard indicator. Numerous PMV calculators has been suggested

and implemented for real-time measurement through website of applications on smart

phones. Nonetheless, the portable PMV calculator device has never been

reported. This thesistherefore presents a portable PMV calculator that indicate the

thermal comfort scale usingraspberry pi3 Microcontroller equipped with humid and

temperature sensors. The proposed device depicts a real time PMV values in which

the operator could conduct to industrial plants or in a building. In addition, the

proposed device is cost-effective with easy-to-use through a touch screen Graphic

User Interface (GUI).

Graduate School Student’s signature ....................................

Field of Study Engineering Technology Advisor’s signature ...................................

Academic Year 2017

iv

Acknowledgement

The author wishes to express her profound gratitude and respectfully

dedicate this work to her parent and family members for their endless

encouragements, love and sacrifices. The author is most grateful to her advisor, Asst.

Prof. Dr. Wimol San-Um, for hers valuable supervision, support and encouragements

throughout the study. In addition, grateful acknowledges are made to Asst. Prof. Dr.

Wipawadee Wongsuwan, Thammavich Wongsamerchue and Patinya Ketthongand

members of thesis support and help. Grateful acknowledges are made to Dr. Surapong

Pongyupinpanich, Asst. Prof. Dr. Warakork Srichavengsup and Dr. Phaisarn

Sudwilaimember of thesis committee, for their valuable suggestions and comments.

The author also acknowledges the Intelligent Electronic Systems Research Laboratory

and the Research and Academic Services Division of Thai-Nichi Institute of

Technology for financial support.

Metinee Rodoum

v

Contents

Pages

Abstract ......................................................................................................................... iii

Acknowledgement ......................................................................................................... iv

Contents .......................................................................................................................... v

List of Tables ............................................................................................................... vii

List of Figures ............................................................................................................. viii

Chapter

1 Introduction ......................................................................................................... 1

1.1 Introduction ............................................................................................ 1

1.2 Background ............................................................................................ 1

1.3 Motivation .............................................................................................. 2

1.4 Research Objectives ............................................................................... 2

1.5 Action .................................................................................................... 3

1.6 Work Plan ............................................................................................. 3

2 Related Theories and Literature reviews ............................................................ 4

2.1 Introduction ............................................................................................ 4

2.2 Related Theory ....................................................................................... 4

2.2.1 ASHRAE’s Thermal Comfort Standard ....................................... 4

2.2.2 Thermal Comfort .......................................................................... 5

2.2.3 Clothing ........................................................................................ 6

2.3 Literature Review ................................................................................ 11

2.4 Conclusion ........................................................................................... 18

3 Research Methodology ..................................................................................... 19

3.1 Introduction .......................................................................................... 19

3.2 Research Processes .............................................................................. 19

3.3 Research Tools .................................................................................... 20

vi

Contents (Continued)

Chapter Pages

3 3.3.1 Raspberry Pi .............................................................................. 20

3.3.2 Python ....................................................................................... 20

3.4 Conclusions .......................................................................................... 20

4 Experimental Results ........................................................................................ 21

4.1 Introduction ......................................................................................... 21

4.2 Nomenclature ...................................................................................... 21

4.2.1 Variable quantity ....................................................................... 21

4.2.2 PMV Equation of another paper ............................................... 22

4.3 Clothing table used in Thailand ........................................................... 24

4.4 PMV Calculate by Equipment ............................................................. 25

5 Conclusion ........................................................................................................ 29

5.1 Introduction ......................................................................................... 29

5.2 Conclusion ........................................................................................... 29

5.3 Recommendation ................................................................................. 29

Reference ...................................................................................................................... 30

Appendices .................................................................................................................... 35

Biography ...................................................................................................................... 54

vii

List of Tables

Table Pages

2.1 CLO value for individual items of clothing ................................................... 7

2.2 Summary of related publication ................................................................... 11

4.1 PMV Equation of another paper ................................................................... 22

4.2 Clothing table used in Thailand .................................................................... 24

4.3 PMV calculate by Equipment ....................................................................... 25

viii

List of Figures

Figures Pages

1.1 Work Plan ....................................................................................................... 3

2.1 Clothing level (in clo units)necessary for comfort at difference ......................

American Society of Heating, Refrigerating and Air-Conditioning

Engineers,Inc.). ....................................................................................... 9

2.2 Illustration of a range of clo values .............................................................. 10

3.1 Research Processes ....................................................................................... 19

4.1 PMV Calculate by Equipment: Scenario 1 ................................................... 25







B.1 Clothing ........................................................................................................ 44

C.1 Certificate of Conference ............................................................................. 50

Chapter 1

Introduction

1.1 Introduction

This Chapter presents a background of research approaches, involving

thermal comfort concepts and PMV and PPD calculate. It also includes the

motivation, research scope, research objective, Work plan and definition of technical

terms.

1.2 Background

The primary function of the air conditioning system for converts the air to

people. Thermal comfort of one person has been defined by ASHRAE (American

Society of Heating, Refrigerating and Air-Conditioning Engineers)[1 ]is the thermal

comfort of one person is not feeling too hot or cold

Standard ASHRAE 55-1992 [2]that refers to “A state of mind that they

represent satisfactory condition ambient air”Despite in one of weather conditions can

make people feel like, some people feel cold and some may feel the heat, therefore,

necessary to be studied optimal weather conditions that make most people feel

thermal comfort. The feeling of thermal comfort depends on quantitative factors,

including temperature, humidity, air speed, temperature radiant heat, the thickness of

the clothes they wear and the activities of people [3].

Thermal comfort equation has been accepted and the most applied are the

equation that studied and developed by Fangerwas from the heat balance between the

body and the environment. The heat generated within the body will transfer to outside

the body through sweat evaporation and heat transfer through the skin and clothing

including the heat out of the body by inhalation. An environment that makes people

feel comfortable. If the exchange between people and environment is zero that means

no the heat that occurs in the body and no heat emitted outside the body, but if the

heat exchange is not a 0 or be uneven. Causing feeling hot or cold.as if the heat

discharged from the body too much. That is people lose too much heat. People will

feel cool to very cool. On the other hand, if the heat generated within the body than

2

the heat flow out of the body people will feel hot to very hot. The ability to transfer

heat away from the body, depending on the circumstances at the time and level of

activity including thickness of clothing

As mentioned above, Thermal comfort has six variables that we can change

those variables to make most people feel thermal comfort. However, there is no

device that can calculate the thermal comfort value in a real-time it still requires

information from the database, so this paper presents a portable PMV calculator that

indicate the thermal comfort scale through the use ofraspberry pi3 Microcontroller

equipped with humid and temperature sensors. The proposed device depicts a real

time PMV values in which the operator could conduct to industrial plants or in a

building. In addition, the proposed device is cost-effective with easy-to-use through a

touch screen Graphic User Interface (GUI) and studies on the CLO at the people in

Thailand.

1.3 Motivation

Now there are many programs and applications to calculate the thermal

comfort value, by using the value in the database to get the air temperature, mean

radiant temperature, clothing value, airspeed and relative humidity. Nonetheless,

database cannot provide real time function and is not the same place that needs to

calculate the value. So, this thesis presents the device that can calculate the thermal

comfort value in that moment.

1.4 Research Objectives

1.4.1 To study the thermal comfort in the PMV equation to check

thecomfort of people

1.4.2 To design the device to calculate the PMV - PPD

usingmicrocontroller

1.4.3 Research Scopes.

1.4.3.1 To study the thermal comfort in the PMV equation to

check the comfort of people.

1.4.3.2 To design the device to calculate the PMV - PPD using

microcontroller.

3

1.4.4 Expected Outcome

1.4.4.1 Gain knowledge on the thermal comfort in the PMV

equationto check the comfort of people.

1.4.4.2 Gain the device to calculate the PMV - PPD using

microcontroller.

1.5 Action

1.5.1 Design and make the device calculate the PMV - PPD using

Raspberry Pi is a Real-time display.

1.5.2 Design the CLO value suitable for the people in Thailand.

1.6 Work Plan

Figure 1.1 Work plan

Chapter 2

Related Theories and Literature reviews

2.1 Introduction

This thesispresents the synthesis of the related theory, ASHRAE’s thermal

comfort standards, thermal comfort and clothing. Literature reviews on thermal

comfort and PMV and PPD calculator will also be presented.

2.2 Related Theory

2.2.1 ASHRAE’s Thermal Comfort Standard

ASHRAE’s Standard 55, Which is the Thermal Environmental Conditionsfor

Human Occupancy, describes the combinations ofindoor space conditions and

personal factors necessary toprovide comfort. It addresses the interactions between

temperature, thermal radiation, humidity, air speed, personalactivity level, and

clothing.

The standard recommends conditions that have beenfound experimentally to

be acceptable to at least 80 percentof the occupants within a space. The operative

temperaturerange for building occupants in typical winter clothing (0.8to 1.2 clo) is

specified as 68° to 74°F (20° to 23. 5°C). Thepreferred temperature range for

occupants dressed in summerclothes(0.35 to 0.6 clo)is 73° to 79°F (22.5° to 26°C).

These values are based on 60%of Relative Humidity, an activitylevel of

approximately 1. 2 met, and an air speed low enoughto avoid drafts. The standard

includes a chart that relates theallowable air speed to room air temperature and the

turbulenceof the air. For each 0.1 clo of increased clothing insulation, the acceptable

temperature range is lowered by 1°F(0.6°C). However, as the temperature decreases,

comfort depends more and more on maintaining a uniform distribution of clothing

insulation over the entire body, especiallythe hands and feet. For sedentary occupancy

of more than anhour, the operative temperature should not drop below 65°F(18°C).

5

2.2.2 Thermal Comfort

Thermal and atmospheric conditions in an enclosed space are usually

controlled in order to ensure (i) the health and comfort of the occupants or (ii) the

proper functioning of sensitive electronic equipment, such as computers, or certain

manufacturing processes that have a limited range of temperature and humidity

tolerance. The former is referred to as comfort conditioning, and the latter is called

process air conditioning. The conditions required for optimum operation of machinery

may or may not coincide with those conducive to human comfort.

The process air conditioning requirements are highly specific to the

equipment or operation involved. Specifications are generally available from the

producer or manufacturer, and the ASHRAE Handbook of applications provides a

description of acceptable conditions for a number of generic industrial processes.Once

the necessary conditions for process or machineryoperationareestablished, attention

must be paid to providingacceptable comfort, or at least relief from discomfort

orphysiological stress, for any people also occupying thespace.

Although human beings can be considered very versatilemachineshaving the

capacity to adapt to wide variationsin their working environment while continuing to

function, their productivity does vary according to the conditions intheir immediate

environment. Benefits associated withimprovements in thermal environment and

lighting qualityinclude:

1. Increased attentiveness and fewer errors

2. Increased productivity and improved quality of productsand services

3. Lower rates of absenteeism and employee turnover

4. Fewer accidents

5. Reduced health hazards such as respiratory illnesses

in feed, in many cases, air conditioning costs can be justified based on

increased profits. The widespread availabilityof air conditioning has also enabled

many U.S. companies to expand into the Sun Belt, which was previouslyimpractical.

Air conditioning and electric lights have eliminated theneed for large

windows, which provided light and ventilationin older commercial and institutional

buildings. Althoughwindows are still important for aesthetics, daylighting, andnatural

ventilation, windowless interior spaces may now beused to a much greater extent. Air

6

conditioning allows formore compact designs with lower ceilings, fewer windows,

less exterior wall areas, and less land space for a given enclosedarea. Conditioned air,

which is cleaner and humiditycontrolled, contributes to reduced maintenance of the

space. As a testament to the importance placed on air conditioning, over one-third of

the entire U. S. population presentlyspends a substantial amount of time in air-

conditioned environments. And all of this represents growth since the

commercializationof refrigeration cooling in the early 1950s.

On the other hand, this improvement in comfort has comeabout at the

expenseof greater equipment installation, maintenance, and energy costs. A

substantial portion of theenergy consumed in buildings is related to the maintenanceof

comfortable environmental conditions. In fact, approximately20 percent of the total

U.S. energy consumption isdirected toward this task. But this doesn’t have to continue

to be the case. With anunderstanding of thefactors that determine comfort in relationto

climate conditions, designers may select design strategies that provide human comfort

more economically. Thus, prior to investigating the energy-consuming

mechanicalsystems in buildings, we will begin by discussing theconcepts of human

comfort.

2.2.3 Clothing

Another determinant of thermal comfort is clothing. In themajority of cases,

building occupants are sedentary or slightly active and wear typical indoor clothing.

Clothing, through its insulation properties, is an important modifier ofbody heat loss

and comfort.The insulation properties of clothing are a result ofthe small air pockets

separated from each other to preventair from migrating through the material.

Newspaper, forexample, can serve as good insulation if several sheetsare separated so

that there are layers of air between the layers ofpapers; this can be used as a crude, but

effective, emergency blanket to cover the body. Similarly, the fine, soft down of

ducks is a poor conductor and traps air insmall, confined spaces. In general, all

clothing makes useof this principle of trapped air within the layers of clothfabric.

Clothing insulation can be described in terms of its clovalue. The clo value is

a numerical representation of a clothingensemble’s thermal resistance. 1 clo = 0.88ft2·

hr· °F/Btu = 0.155m2 ·°C/WA heavy two-piece business suit andaccessorieshave an

7

insulation value of about 1 clo, while a pair of shorts is about 0.05 clo. Clo values for

common articlesof clothing are listed in Table 2. 3. The total insulationvalue of a

clothing ensemble can be estimated as the sum ofthe individual garment clo values.

Table 2.1 CLO value for individual items of clothing.

Men Women

Clothing clo Clothing clo

Underwear Underwear

Sleeveless 0.06 Girdle 0.04

T-Shirt 0.09 Bra and panties 0.05

Briefs 0.05 Half slip 0.13

Long underwear, upper 0.10 Full slip 0.19

Long underwear, lower 0.10 Long underwear, upper 0.10

Long underwear, lower 0.10

Shirt Blouse

Light, short sleeve 0.14 Light, long sleeve 0.20

Long sleeve 0.22 Heavy, long sleeve 0.29

Heavy, short sleeve 0.25 Dress, light 0.22

Long sleeve 0.29 Dress, heavy 0.70

(plus 5% for tie or turtleneck) Skirt, light 0.10

Vest, light 0.15 Skirt, heavy 0.22

Vest, heavy 0.29 Slacks, light 0.10

Trousers, light 0.26 Slacks, heavy 0.44

Trousers, heavy 0.32 Sweater

Sweater, light 0.20 Light, sleeveless 0.17

Sweater, heavy 0.37 Heavy, long sleeve 0.37

Jacket, light 0.22 Jacket, light 0.17

Jacket, heavy 0.49 Jacket, heavy 0.37

8

Table 2.1 CLO value for individual items of clothing (Continued)

Men Women

Clothing clo Clothing clo

Socks Stockings

Ankle length, thin 0.03 Any length 0.01

Ankle length, thick 0.04 Panty hose 0.01

Knee high 0.10

Shoes Shoes

Sandals 0.02 Sandals 0.02

Oxfords 0.04 Pumps 0.04

Boots 0.08 Boots 0.08

Hat and overcoat 2.00 Hat and overcoat 2.00

The relationship between clothing insulation and roomtemperature necessary

for a neutral thermal sensation is presentedin Figure 2.6 for sedentary occupants, and

specifiedair speed and humidity. Comfortable clothing levels areexpressed as a

function of operative temperature, which isbased on both air and mean radiant

temperatures. At airspeeds of 8 fpm (0.4 m/s)or less and MRT less than 120°F(50°C),

the operative temperature is approximately the averageof the air and mean radiant

temperatures and is equal tothe adjusted dry-bulb temperature. There is no

combination of conditions that would satisfyall people all the time. The optimum

operative temperature, represented by the middle line in Figure 2. 6, is the

temperaturethat satisfies the greatest number of people with agiven amount of

clothing and specified activity level. Theupper and lower thermal acceptability limits

demarcate aroom environment that at least 80 % of the occupantswould find thermally

acceptable.

9

Figure 2.1 Clothing level (in clo units)necessary for comfort at difference

Operativetemperature. (Reprinted from Standard 55 by permission of the

American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.).

From the 1920s to the early 1970s, energy was abundantand

inexpensive. During this period, the preferred amount ofclothing worn by

building occupants decreased, and correspondinglythe preferred temperatures

increased from about68°F (20°C)for winter to the year-round range of 72°F

to78°F (22° to 25. 5°C). Present conditions, however, make itdesirable to

minimize energy consumption for providingthermal comfort.

Conditions that are thermally acceptable to at least 80% of normally clothed

occupants are presented in Figure 2.6. By adjusting clothing as desired, the

remainingoccupants can satisfy their own comfort requirements. Energy savings can

10

be achieved if the insulation value ofclothing worn by people indoors is appropriate to

the seasonand outside weather conditions.

During the summer months, suitable clothing in commercial establishments

consists of lightweight dresses, lightweight slacks, short-sleeved shirts or blouses,

stockings, shoes, underwear, accessories, and sometimes a thin jacket. These

ensembles have insulation values ranging from 0. 35to 0. 6 clo. The winter heating

season brings a change to thicker, heavier clothing. A typical winter

ensembleincluding heavy slacks or skirt, long-sleeved shirt or blouse, warmsweater or

jacket, and appropriately warm accessorieswould have an insulation value ranging

from 0.8 to 1.2 clo. During more temperate seasons, the clothing would likely consist

of medium-weight slacks or skirt, long-sleeved shirtor blouse, and so on, having a

combined insulation value of0.6 to 0.8 clo. Figure 2.7 illustrates various clo values.

Figure 2.2 Illustration of a range of clo values.

These seasonal clothing variations of building occupantsallow indoor

temperature ranges to be higher in the summer than in the winter and yet remain

comfortable. Inthe wintertime, additional clothing lowers the ambient

temperaturenecessary for comfort and for thermal neutrality. Adding 1 clo of

insulation permits a reduction in air temperatureof approximately 13°F (7. 2°C)

11

without changing the thermal sensation. At lower temperatures, however, comfort

requires a fairly uniform level of clothing insulationover the entire body. For

sedentary occupancy of morethan an hour, the operative temperature should not be

lessthan 65°F (18°C).The insulation of a given clothing ensemble can be estimatedby

adding up the clo values of the individual items worn, as listed in Table 2.2, and

multiplying the sum by 0. 82. A rough approximation of the clo value may also be

estimated by multiplying each pound of clothing by 0.15 clo(oreach kilogram by 0.35

clo).

2.3 Listerature Review

Table 2.2 sumary of related publication

No. Years Authors Titles

1 2011 J. A.Orosa and A. C. Oliveira

[4]

A new thermal comfort approach

comparing adaptive and PMV

models

2 2012 A. Pourshaghaghy and M.

Omidvari [5]

Examination of thermal comfort in

a hospital using PMV-PPD model

3 2013 J. H. Kim et al.[6] Is the PMV Index an Indicator of

Human Thermal Comfort

Sensation?

4 2013 C. Manuel [7] Spreadsheets for the calculation of

thermal comfort indices PMV and

PPD

5 2011 S. Mors et al. [8] Adaptive thermal comfort in

primary school classrooms:

Creating and validating PMV-

based comfort charts

12

Table 2.2 Sumary of related publication (Continued) No. Years Authors Titles

6 2010 A. Kumar et al. [9] Anapproach towards development

of PMV based thermal comfort

smart sensor

7 2014 Y. Yanga et al. [10] A study of adaptive thermal

comfort in a well-controlled

climate chamber

8 2011 H. Matsumoto [11] Estimation of Thermal Comfort by

Measuring Clo Value without

Contact

9 2009 M. V. M. Hott [12] Subjective evaluation of thermal

comfort on a vehicle

10 2014 P. Baruah and M. Tech [13] Thermal Comfort in Naturally

Ventilated Classrooms

11 2014 O. E. Abiodun [14] Examination of thermal comfort in

a naturally ventilated hostel using

PMV-PPD model and field survey

As shown in Table 2.9, J. A. Orosa and A. C. Oliveira [4] said in

buildings with heating, ventilation, and air-conditioning (HVAC), the Predicted

Mean Vote index (PMV) was successful at predicting comfort conditions,

whereas in naturally ventilated buildings, only adaptive models provide

accurate predictions. On the other hand, permeable coverings can be considered

as a passive control method of indoor conditions and, consequently, have

implications in the perception of indoor air quality, local thermal comfort, and

energy savings. These energy savings were measured in terms of the set point

temperature established in accordance with adaptive methods. Problems appear

when the adaptive model suggests the same neutral temperature for ambiences

with the same indoor temperature but different relative humidities. In this

13

paper, a new design of the PMV model is described to compare the neutral

temperature to real indoor conditions. Results showed that this new PMV

model tends to overestimate thermal neutralities but with a lowervalue than

Fanger’ s PMV index. On the other hand, this new PMV model considers

indoor relative humidity, showing a clear differentiation of indoor ambiences in

terms of it, unlike adaptive models. Finally, spaces with permeable coverings

present indoor conditions closer to thermal neutrality, with corresponding

energy savings.

A. Pourshaghaghy and M. Omidvari [5] said in this study, the

performance of air conditioning system and the level of thermal comfort are

determined in a state hospital located in Kermanshah city in the west of Iran in

winter and summer using the Predicted Mean Vote (PMV) model which has

been presented by ISO-7730 (2005). The Predicted Mean Vote (PMV)and the

Predicted Percentage Dissatisfied (PPD)indices were computed using the data

acquired from the experimental measurements performed in the building. The

results showed that the values of PMV in some parts of the building, both for

men and women, are not within the standard acceptable range defined by ISO.

It was found that the most thermal problems in winter occur in morning work

shift, and the worst thermal conditions in summer occur in noon work shift.

The t-test results revealed that there is no noticeable difference between the

thermal conditions of some rooms and those of the surroundings.

J. H. Kim et al. [6] said the examined how indoor environmental

variables affect the human thermal comfort sensation. To examine the effect,

both subjective comfort and thermal sensation were measured by the comfort

sensation vote (CSV) and the thermal sensation vote (TSV) in thermal

environmental conditions during heating or cooling. CSV was used by Tanabe

(1998) and TSV was defined in ASHRAE (1989). In addition, physical

environmental variables such as the air temperature, relative humidity, mean

radiant temperature, air velocity, and the predicted mean vote (PMV) were

14

used as the indices of thermal comfort sensation, and then the relationships

between physical environmental variables and subjective variables were

examined. The results showed a significant relationship between the PMV and

the TSV, whereas a significant relationship was not shown between the PMV

and the CSV even if there was a significant relationship between the relative

humidity from the components of the PMV and the CSV. These results imply

that PMV does not reflect human thermal comfort sensation adequately, and

humidity control may be important in reflecting human thermal comfort

sensation in indoor environments.

C. Manuel [7] said a set of spreadsheets developed in Microsoft Excel

to calculate the thermal comfort indices, using the Fanger’s method proposed in

ISO Standard 7730 is presented. The calculation method is based upon the

determination, through an iterative process, of the clothing external

temperature, being the PMV index calculated from a human body thermal

balance equation where internal heat generation and heat exchanges with the

surrounding environment are considered. The main objective of the work was

to develop user-friendly simple software tools for the calculation of thermal

comfort indices. Thus, different spreadsheets were prepared allowing the

calculation with environmental data measured with different sets of sensors.

S. Mors et al. [8] said in this research the thermal comfort and thermal

comfort parameters for childrenin primary school classrooms have been

investigated. Actual thermal sensation and clothing insulation of

children (age 9–11) in non-air-conditioned classrooms in three different

schools in the Netherlands have been obtained. Results are available for a total

of 24 days, covering winter, spring and summer conditions (year 2010).

Questionnaires have been applied to obtain the actual thermal sensation and

clothing insulation in the morning and afternoon of regular school days. In this

period, physical parameters (temperature, relative humidity, etc)were recorded

as well in order to derive the PMV.The results show that children adapt

15

clothing during the year from mean values around 0.9 clo in winter to 0.3 clo in

summer, with the largest changes occurring in the mid-season. There is a small

difference in clothing adaptation between male and female children, with the

females showing more adaptation.Comparison of the actual mean vote with the

calculated PMV, based on the measured data, indicates a clear difference. The

conclusion is that the PMV model does not predict the thermal sensation of

these children accurately; it underestimates the mean thermal sensation up to

1. 5 scale point. When the actual thermal sensation votes are compared to

comfort predictions based on adaptive temperature limits it shows that children

prefer lower temperatures than predicted by these methods.

A. Kumar et al. [ 9] said ASHRAE 55-2004 and ISO 7730 standards

failed to predict actual comfort level and lead to oversize design of HVAC

system. So, proper thermal environment monitoring is an important subject to

have right size of HVAC systems. A prototype thermal EM system has been

developed. Thermal environment parameters such astemperature, relative

humidity, CO and CO2 are measured by using the developed system. These

data are used to calculate the thermal comfort index. The subjective judgments

and the calculated PMV are compared with the results. The results showed the

possibility of using PMV based thermal comfort smart sensor.

Y. Yanga et al. [10] said this paper aims to critically examine the

application of Predicted Mean Vote (PMV) in an air-conditioned environment

in the hot-humid climate region. Experimental studies have been conducted in a

climate chamber in Chongqing, China, from 2008 to 2010. A total of 440

thermal responses from participants were obtained. Data analysis reveals that

the PMV overestimates occupants' mean thermal sensation in the warm

environment (PMV > 0)with a mean bias of 0. 296 in accordance with the

ASHRAE thermal sensation scales. The Bland–Altman method has been

applied to assess the agreement of the PMV and Actual Mean Vote (AMV)and

reveals a lack of agreement between them. It is identified that habituation due

16

to the past thermal experience of a long-term living in a specific region could

stimulate psychological adaptation. The psychological adaptation can

neutralize occupants’ actual thermal sensation by moderating the thermal

sensibility of the skin. A thermal sensation empirical model and a PMV-revised

index are introduced for air-conditioned indoor environments in hot-humid

regions. As a result of habituation, the upper limit effective thermal comfort

temperature SET* can be increased by 1.6 °C in a warm season based on the

existing international standard. As a result, a great potential for energy saving

from the air-conditioning system in summer could be achieved.

H. Matsumoto [ 11] said in order to create more comfortable and

energy saving living spaces, we have to investigate what is comfortable and

how to measure comfort of users in a living space. Some measures of thermal

comfort have been defined as Predicted Mean Vote (PMV)and Predicted

Percentage Dissatisfied (PPD)as an international standard. However, complex

and high cost equipment are required to measure PMV by conventional

methods. In this paper, we propose a method for PMV estimation more easily

and cheaper than conventional methods by using a camera. PMV is calculated

from temperature, humidity, air velocity and clo value estimated by sensors and

clothes database.

M. V. M. Hott [12] said the present study has as objective to evaluate

the thermal comfort into the vehicle giving emphasis to the climatization

system from the point of view of the user. The importance of having

comfortable vehicles, either for security reasons, health or thermal welfare of

the passengers, imposes to the automotive industry the search for methods of

thermal comfort evaluation that comes as close as possible to the occupant’s

sensation. In this work results of subjective tests conducted with a group of

people in a stabilized chamber capable of simulate the environmental

conditions in a warm day with intense solar irradiation is presented. The

evaluation of the comfort, made for the people through grades, is related to the

17

values of temperature, humidity, air speed and the time required to achieve the

physiological welfare conditions. The interviews had been made always in the

same vehicle under the same conditions, with the interviewed in the same

position, with similar clothes so that the uniformity of the experiment was

remained. According to the results of the interviews, the Predicted Mean Vote

(PMV)and Predicted Percentage of Dissatisfied (PPD)can also be obtained.

These grades will be calculated for a comparison with the people opinion too.

P. Baruah and M. Tech [13] said thermal comfort study is very

important because it correlates occupants comfort in built environment to the

functioning of the building and energy consumption. PMV-PPD method works

fairly well for conditioned buildings. However, this method does not provide

expected results when applied to naturally ventilated buildings. Naturally

ventilated buildings are much more dynamic compared to conditioned

buildings in terms of thermal environment and occupant’s behavior in the built

environment. In this study, questionnaire based thermal comfort survey has

been carried out in naturally ventilated classrooms of Tezpur University during

the months of February and May 2013 i.e. at the end of the winter season and

the beginning of summer. Thermal sensation and preferences of 228 students

are recorded on ASHRAE thermal sensation scale. Various associated

parameters like indoor and outdoor air temperature, humidity, clothing and

metabolic rate are also measured. The results reveal that the subjects did not

feel extreme levels of thermal discomfort during this period. It has been

observed that there is a large variation in the clothing pattern (0.83 to 1.52 clo

in winter and 0.43 to 0.68 clo in summer) in both the seasons which justify the

behavioral, physiological and psychological adaptation of the respondent. It is

also found that the other adaptive means like use of fans, closing or openings of

windows etc. are used quite often. This study concludes that the comfort

temperature range varies from 22 to 23.5 °C in winter month and 27.3 to 30.7

°C in summer month. It also concludes that most of the objects recorded cool

18

thermal sensation and preferred a warmer climate in winter and warm thermal

sensation and preferred a cooler environment in summer.

O. E. Abiodun [14] said the application of Predicted Mean Vote

( PMV) and Predicted Percentage Dissatisfied ( PPD) indices for thermal

comfort quality assessment in naturally ventilated (NV)buildings in warm-

humid climate has been observed to lead to overestimation of occupants`

comfort and dissatisfaction levels. The thermal comfort quality in a naturally

ventilated hostel located in ObafemiAwolowo University, Ile-Ife was

determined using PMV and PPD indices. The measured indoor air temperature

and relative humidity were 28. 1-34oC and 30. 8% -75. 5%. The subjective

assessments showed that more than 80%of the respondents were comfortable

(PD ˂ 20%)while the PPD index predicted that 58%of the occupants were not

comfortable. The calculated PMV index on the average was +1.63. There was

no correspondence between the thermal conditions predicted by PMV-PPD

index and actual comfort vote. Fanger`s PMV-PPD model cannot be used to

predict indoor climate in the study area as it overestimated occupants` comfort

and dissatisfaction levels.

2.4 Conclusion

This chapter has presentd the synthesis of the related theory,

ASHRAE’ s Thermal Comfort Standards, Thermal Comfort and Clothing in

with acknowledge. Literature reviews on thermal comfort and PMV and PPD

calculator that support the PMV and PPD calculate has also been included.

Chapter 3

Research Methodology

3.1 Introduction

This Chapter presents research methodology, including the built the new

model equipment for keep the information and calculate PMV - PPD value.

3.2 Research Processes

Figure 3.1 Research Processes

3.2.1 Study the thermal comfort from ASHRAE’s Thermal Comfort

Standard

3.2.2 Design the PMV equation from ASHRAE’s Thermal Comfort

Standard via MATLAB

3.2.3 Apply the PMVequationto create the generate to use withRaspberry

Pi S3 using Python languages

3.2.4 Test the device to calculate the PMV and PPD valuein 7 scenarios.

20

3.2.5 Validate the PMV and PPD with MATLAB code, PMV and PPD

calculate apps and PMV and PPD calculate websites.

(http://comfort.cbe.berkeley.edu/)

3.2.6 Analyze the test result for activities, temperature, and power to find

the average value. In order to find CLO value for employee in air-conditioning room

in Thailand

3.3 Research Tools

3.3.1 Raspberry Pi

The raspberry Pi was born in 2549 at University of Cambridge English by

Eben Upton for use the raspberry pi us r for minicomputer have small cost and easy to

program. The raspberry pi is a minicomputer to connect with the monitor that support

HDMI port and can connect keyboard and mouse with USB port. The raspberry pi can

adapt in electronic project, program writing or mini personal computer. This thesis

used Raspberry Pi 3. Which is the new generation of Raspberry Pi. This board

includes Wi-Fi technology and Bluetooth technology. Such a technology makes the

Raspberry Pi 3 to become a full IoT(Internet of Thing)

3.3.2 Python

Python is a programming language used in one language. Which

developed by not stick to platform. Python can run in both on UNIX, Linux, Windows

NT, Windows 2000, Windows XP or FreeBSD system. Python is Open Source like

PHP means anyone can use the Python to develop our programs for free without

charge. Due to Python is the Open Source the people will develop the ability to

Python has increased.

3.4 Conclusions

This chapter has presented research methodology, including the built the

new model equipment for keep the information and calculate PMV-PPD value.

Chapter 4

Experimental Results

4.1 Introduction

PMV value and PPD value predict the thermal comfort of most people. By

equation based on ASHRAE standard to calculate PMV and PPD value. This chapter

proposesthe PMV equations, clothing table used in Thailand and PMV Calculate by

Equipment

4.2 Nomenclature

4.2.1 Variable quantity

PMV = Predicted Mean Vote Unit less

PPD = Predicted Percentage of Dissatisfied (%)

M = Metabolic rate (met)

W = External work (w/m2)

Pa = Partial water vapor pressure (N/m2),

ta = Air temperature (0C)

Fcl =Clothing area factor

tmr = Mean radiant temperature (0C)

tcl = Clothing surface temperature (0C)

hc = Convective heat tranfer coefficient (W/m2/ 0C)

Var = Relative air velocity with respect to human body (m/s)

Icl = Thermal resistance of clothing (CLO)

va = Air velocity (m/s)

ADU = Dubious area (m2)

22

4.2.2 PMV Equation of another paper

Table 4.1 PMV equation of another paper

Ref. PMV Equation

1 Standard ASHRAE PMV = (0.303exp(− 0.0336M) + 0.028)× {(M –

W) – 3.5 × 10−3[5733 – 6.99 (M– W)−pa] – 0.42

(M – 58. 5) – 1. 7 ×10− 5 × M (5867 – pa) –

0.0014M (34 – ta) – 3.96 × 10−8fcl[(tcl + 273)4 –

(tr+273)4]- fcl × hc(tcl-ta)}

2 An Approach Towards

Development of PMV

Based Thermal Comfort

Smart Sensor

(0.303e-0.036M+0.028){(M –W) - 3.05 x 10-3 [5733

- 6.99 (M-W)Pa] – 0.42 [(M –W) - 58.15] – 1.7 x

10-5M (5867 - Pa) - 0.0014M (34 - ta) - 3.96 x 10-

8Fcl[(tmr+ 273)4 – (tmr– 273)4]- Fclhc(tcl - ta)}

3 Estimation of Thermal

Comfort byMeasuring

CLO Value without

Contact

(0.303 EXP (-0.036M + 0.028)(M –W) - 3.05 x

10-3x[5733 - 6.99 (M –W) - pa] - 0.42 [(M –W) -

58.15] - 1.7 x 10-5 M (5867 - pa) - 0.0014M (34 -

ta) - 3.96 x 10-8 fcl(tcl + 273)4–(tr + 273)4 - fclhc(tcl

- ta)}

4 Examination of Thermal

Comfort in a Naturally

Ventilated Hostel Using

PMV-PPD Model and

Field Survey

(0.303e-0.036M + 0.028) {(M - W) - 3.05 x 10-3

( 5733 - 6. 99 ( M - W - Pa) - 0. 42 ( M - W) -

58.15} - 1.7 x 10-5M (5867 - Pa) - 0.0014M (34 -

Tmrt) – 3.96 x 10-8fcl (Tcl + 273)4 - (Tmrt + 273)4 -

fclhc (Tcl - Tmrt)]

5 Spreadsheets for The

Calculate of Thermal

Comfort Indices PMV and

PPD.

(0.303e-2.100 * M + 0.028) * [(M –W) – (3.96 * 10-8

* fcl * [(tcl + 273)4–(tr+ 273)4]- fcl * hc * (tcl - ta))

– (3.05 * 10-3 * [5733 - 6.99 * (M –W)- pa] –

0.42 * [(M –W) – 58.15)] – (0.0014 * M * (34 -

ta)) – (1.7 * 10-5 * M * (5867 - pa))]

23

Table 4.1 PMV equation of another paper (Continued)

Ref. PMV Equation

6 Thermal Comfort Analysis

of PMV Model Prediction

in Air Conditioned and

Naturally Ventilated

Buildings.

(0.303exp(-0.0336M + 0.028))× { (M – W ) – 3.5

× 10-3[5733 -6.99 (M – W )- pa]- 0.42 (M -58.5)-

1.7 ×10-5 × M (5867 – pa)– 0.0014M (34 – ta) –

3.96 × 10-8fcl[(tcl + 273)4 – (tr + 273)4] –fcl × hc(tcl

– ta)}

7 Examination of Thermal

Comfort in a Hospital

Using PMV-PPD Model.

(0.303e-0.036M+ 0.028)x {(M – W) - 3.05 x 10-3 x

[5733 - 6. 99(M –W) - Pa] - 0. 42 x [(M –W)-

58.15] - 1.7 x 10-5M (5867 - Pa) - 0.0014M (34 -

ta) - 3.96 x 10-8fcl x [(tcl+ 273)4 – (tr + 273)4] -

fclhc(tcl - ta)

8 Thermal Comfort for Air-

Conditioning in Thailand

(0.325e-0.042M + 0.032) [M - 0.35(43 - 0.061M -

Pv) - 0. 42 ( M - 50) - 0. 0023M( 44 - Pv) -

0.0014M(34 - Ta ) - 3.4 x 10-8fcl ((Tcl+ 273)4 -

(Tmrt + 273)4) - fclhc (Tcl- Ta)]

9 Thermal Discomfort in a

Public Terminal Building

( 0.303e-0.036M + 0.028) {( M – W) - 3.05 ×10-3

[5733 – 6.99 M – W – Pa] - 0.42 × [(M – W) –

58.15] – 1.7 ×10-5 M (5867 - Pa) – 0.0014M (34 -

ta) - 3.96 × 10-8fcl × [(tcl + 273)4 – (Tmrt + 273)4 –

fclhc (tcl - ta)}

24

4.3 Clothing table used in Thailand

Table 4.2 Clothing table used in Thailand

Description CLO Description CLO

Underwear Trousers and Skirts

Bra 0.01 Slacks 0.22

Panties 0.03 Jeans 0.28

Men’s briefs 0.03 Overall 0.33

Half-slip 0.08 Coverall 0.42

Full slip 0.13 Thai Pants 0.24

Shirt Cropped Pants 0.22

T-Shirt 0.22 Board Shorts 0.20

Fake Layered 0.28 Legging 0.18

Shirt, Business Shirt 0.20 Maxi Skirt 0.20

Polo Shirt 0.25 Midi Skirt 0.18

Dress 0.28 Mini Skirt

Tunic 0.25 Foot wear

Camisole 0.15 Sandals 0.02

Sleeveless 0.18 Shoes 0.05

Tank Top 0.18 Boots 0.15

Tube Top 0.15 Loafer 0.10

Coat Pumps 0.08

Suit 0.38 Panty hose 0.01

Sweater 0.35 Low-Cut Sport 0.03

Vest 0.30 Ankle-Dress Socks 0.08

Hoodie 0.35 Knee-Length Socks 0.1

Bolero 0.22

Windbreaker 0.40

25

4.4 PMV Calculate by Equipment

Table 4.3 PMV Calculate by Equipment

Air

-

tem

pera

ture

Mea

n R

adia

nt

Tem

pera

ture

rela

tive

hum

idit

y

air

velo

city

Clo

thin

g

PM

V

PP

D

factory 42 40 40 0.4 0.6 6.1 100

office 22 32 30 0.6 0.8 -0.57 11.9

air-school 26 36 30 0.6 0.6 0.6 12.5

natural school 32 30 60 0.8 0.6 1.96 75

restaurant 24 30 30 0.2 0.6 -0.07 5.1

theatre 22 32 30 0.2 0.6 -0.17 5.6

sea 37 40 80 1 0.4 5.81 100

4.4.1 In factory temperature 42 Celsius Mean Radiant Temperature

40Celsius relative humidity 40% air velocity 0.4 m/s Clothing 0.6 CLOPMV = 6.1,

PPD = 100%

Figure 4.1 PMV Calculate by Equipment: Scenario 1

26

4.4.2 In office temperature 22 Celsius Mean Radiant Temperature 32

Celsius relative humidity 30% air velocity 0.6 m/s Clothing 0.8 CLO PMV = -0.57,

PPD = 11.9%

Figure 4.2 PMV Calculate by Equipment: Scenario 2

4.4.3 In air-school temperature 26 Celsius Mean Radiant Temperature 36

Celsius relative humidity 30% air velocity 0.6 m/s Clothing 0.6 CLO PMV = 0.6,

PPD = 12.5%

Figure4.3 PMV Calculate by Equipment: Scenario 3

27

4.4.4 In natural school temperature 32 Celsius Mean Radiant

Temperature30Celsius relative humidity 60% air velocity 0.8 m/s Clothing 0.6 CLO

PMV = 1.96, PPD = 75%


4.4.5 In restaurant temperature 28 Celsius Mean Radiant Temperature 30


PPD = 5.1%


28

4.4.6 In theatre temperature 22 Celsius Mean Radiant Temperature 32


PPD = 5.6%


4.4.7 In sea temperature 37 Celsius Mean Radiant Temperature 40

Celsius relative humidity 80% air velocity 1 m/s Clothing 0.4 CLO PMV = 5.81,

PPD = 100%


Chapter 5

Conclusion

5.1 Introduction

The purpose of this chapter is to summarize the research and suggest

research and policy recommendations for further analysis. The first section of the

chapter will discuss the objectives of the research and the methodology use to

accomplish the analysis. A summary of the major result will be described. The second

part of the chapter will discuss policy implications of the research and purpose

recommendations for further both on the simulation results and experimental results.

5.2 Conclusion

Comfort is best defined as the absence of discomfort. People feel

uncomfortable when they are too hot or too cold. Was from the heat balance between

the body and the environment. An environment that makes people feel comfortable is

the exchange between people and environment is 0 that means no the heat that occurs

in the body and no heat emitted outside the body, but if the heat exchange is not a 0 or

be uneven. Causing feeling hot or cold. There for this thesis has presented the portable

PMV calculator that indicate the thermal comfort scale using raspberry pi3

Microcontroller. The proposed device depicts a real time PMV values in which the

equipment can actually work and the results are close to the PMV value in ASHRAE

Standard. In addition, the proposed device is cost-effective with easy-to-use through a

touch screen Graphic User Interface (GUI).

5.3 Recommendation

Future work may add the sensors to measure the temperature value,

humidity value, vapor and air speed for calculate the PMV and PPD value in that time

and in that place. Can send the data to monitor in web interface and can remote

forcontrolling for the comfort.

References

31

Reference

[1] American Society of Heating, Refrigerating and Air Conditioning Engineers

(ASHRAE), ASHRAE Handbook of Fundamentals, Atlanta : n.p., 1989.

[2] American Society of Heating, Refrigerating and Air Conditioning Engineers

(ASHRAE), Thermal Environmental Conditions for Human Occupancy,

Atlanta : n.p., 2004.

[3] K. E. Charles, Fanger’s Thermal Comfort and Draught Models, Canada:

CNRC, 2003.

[4] J. A. Orosa and A. C. Oliveira, “A new thermal comfort approach comparing

adaptive and PMV models,” Renewable Energy, vol. 36, no.3, pp. 951-956,

March 2011.

[5] A. Pourshaghaghy and M. Omidvari, “Examination of thermal comfort in a

hospital using PMV-PPD model,” Applied Ergonomics, vol. 43, no. 6, pp.

1,089-1,095, November 2012.

[6] J. H. Kim et al, “Is the PMV index an indicator of human thermal comfort

sensation,” International Journal of Smart Home, vol. 7, no. 1, pp. 27-34,

January 2013.

[7] C. Manuel, “Spreadsheets for the calculation of thermal comfort indices PMV

and PPD,” Ph.D. dissertation (Mechanical Engineering), University of

Coimbra, Coimbra, Portugal, 2013.

[8] S. Mors et al, “Adaptive thermal comfort in primary school classrooms:

creating and validating PMV-based comfort charts,” Building and

Environment, vol. 46, no. 12, pp. 2,454-2,461, December 2011.

[9] A. Kumar et al, “An approach towards development of PMV based thermal

comfort smart sensor,” International Journal on Smarts Sensing and

Intelligent Systems, vol. 3, no. 4, pp. 621-641, December 2010.

[10] Y. Yanga et al, “A study of adaptive thermal comfort in a well-controlled

climate chamber,” Applied Thermal Engineering, vol. 76, no.5, pp. 1-9,

February 2014.

32

[11] H. Matsumoto, “Estimation of thermal comfort by measuring CLO value

without contact,” IAPR Conference on Machine Vision Applications,

MVA2011, Nara, Japan, June 13-15, 2011, pp. 491-494.

[12] M. V. M. Hott, “Subjective evaluation of thermal comfort on a vehicle,”

International Congress of Mechanical Engineering, COBEM2009, Gramado,

Brazil, November 15 – 20, 2009, no page.

[13] P. Baruah and M. Tech, “Thermal comfort in naturally ventilated classrooms,”

International PLEA Conference, PLEA2014, Ahmedabad, India, December

16-18, 2014, pp. 1-8.

[14] O. E. Abiodun, “Examination of thermal comfort in a naturally ventilated

hostel using PMV-PPD model and field survey,” American Journal of

Engineering Research (AJER), vol. 3, no. 8, pp.63- 78, November 2014.

[15] E. Yasa, “Evaluation of the effect of the different distances between two

facades natural ventilation on atrium buildings with DSF and PMV-PPD

comfort,” 9th International Symposium on Heating, Ventilation and Air

Conditioning and the 3rd International Conference on Building Energy and

Environment, (ISHVAC and COBEE), Tianjin, China, July 12-15, 2015,

pp.667-674.

[16] D. G. Kroger, Air-Cooled Heat Exchangers and Cooling Towers: Thermal-

Flower Performance Evaluation and Design, Oklahoma: PennWell Corp,

2004.

[17] E. Bas, Indoor Air Quality, 2nd ed., USA. : Fairmont Press, 2003.

[18] D.W. Bearg, “Indoor Air Quality and HVAC Systems,” USA. : Taylor &

Francis Inc., 1993.

[19] B. O. Brooks and W. F. Davis, Understanding Indoor Air Quality, USA. :

Taylor & Francis Inc., 1991.

[20] R. B. Gammage, Indoor Air and Human Health, 2nd ed., USA. : CRC Press,

1985.

[21] F. L. Edwin, Clothing Comfort and Function, USA. : Marcel Dekker, 1970.

[22] W. E. Woodson, Human Factors Design Handbook: Information and

Guidelines for the Design of Systems, Facilities, Equipment, and Products for

Human Use, USA. : McGraw-Hill Book Company, 1981.

33

[23] R. A. Wadden and P. A. Scheff, Indoor Air Pollution: Characterization,

Prediction, and Control, USA. : John Wiley & Sons, Inc., 1982.

[24] B. Givoni, Passive Low Energy Cooling of Buildings, USA. : John Wiley &

Sons, Inc., 1994.

[25] T. Godish, Sick Buildings: Definition, Diagnosis and Mitigation, USA. : CRC

Press, 1994.

[26] B. Givoni, Climate Considerations in Building and Urban Design, USA. : n.p,

1998.

[27] T. Godish, Indoor Environmental Quality, USA. : CRC Press, 2000.

[28] H. E. Burroughs and S. J. Hansen, Managing Indoor Air Quality, 5th ed, USA.

: Fairmont Press, 2004.

[29] R. Hyde, Climate Responsive Design: A Study of Buildings in Moderate and

Hot Humid Climates, UK. : Taylor & Francis Ltd., 2000.

[30] G. E. Keller et al, Indoor Air Pollution: Radon, Bioaerosols, and VOCs, USA.

: Taylor & Francis Inc., 1991.

[31] H. Koch-Neilsen, Stay Cool: A Design Guide for the Built Environment in Hot

Climates. Earths can Publications, UK. : Taylor & Francis Ltd., 2002.

[32] D. G. Kroger, Air-Cooled Heat Exchangers and Cooling Towers: Thermal-

Flow Performance Evaluation and Design Vol. 1, USA. : PennWell Books,

2004.

[33] N. H. Lechner, Cooling, and Lighting: Design Methods for Architects, 2nd ed.,

USA. : John Wiley & Sons, Inc., 2001.

[34] F. W. Lunau and G. B. Leslie (editors) , Indoor Air Pollution: Problems and

Priorities, UK. : Cambridge University Press, 1994.

[35] J. Lstiburek, Builder’ s Guide to Mixed Climates: Details for Design and

Construction, USA. : Taunton Press, 2000.

[36] S. M. Mc-Gregor and N. B.Trulsson, Living Homes: Sustainable Architecture

and Design, USA. : Chronicle Books, 2008.

[37] J. D. Odom and G. Dubose (editor), Commissioning Buildings in Hot Humid

Climates: Design and Construction Guidelines, USA. : Fairmont Press, 2000.

[38] O’Reilly et al, Keeping Buildings Healthy, USA. : John Wiley & Sons, Inc.,

1998.

34

[39] J. S. Reynolds, Courtyards: Aesthetic, Social, and Thermal Delight, USA. :

John Wiley & Sons, Inc., 2001.

[40] C. Salmon, Architectural Design for Tropical Regions, 1st ed., USA. : John

Wiley & Sons, Inc., 1999.

[41] J. M. Samet and J. D. Spengler, Indoor Air Pollution: A Health Perspective

( The Johns Hopkins Series in Environmental Toxicology), 1st ed., USA. :

Johns Hopkins University Press, 1991.

[42] M. S. Sanders and E. J. McCormick, Human Factors in Engineering and

Design, 7th ed., USA. : McGraw-Hill Book Company, 1993.

Appendices

36

AppendicesA. Computer program for calculate PMV and PPD

37

Variables Symbols in program

Clothing, clo CLO

Metabolic rate, met MET

External work, met WME

Air temperature, °C TA

Mean radiant temperature, °C TR

Relative air velocity, m/s VEL

Relative humidity, % RH

Partial water vapour pressure, Pa PA

10 Computer program (BASIC) for calculation of

20 Predicted Mean Vote (PMV) and Predicted Percentage of

Dissatisfied (PPD)

30 in accordance with International Standard, ISO 7730

40 CLS: PRINT "DATA ENTRY" data entry

50 INPUT "Clothing(clo) "; CLO

60 INPUT " Metabolic rate (met) " MET

70 INPUT" External work, normally around 0 (met) " WME

80 INPUT "Air temperature (°C)" TA90 INPUT

"Mean radiant temperature (°C) " TR

100 INPUT " Relative air velocity (m/s) " VEL

110 INPUT "ENTER EITHER RH OR WATER VAPOURPRESSURE BUT

NOT BOTH"

120 INPUT "Relative humidity (%) " RH

130 INPUT " Water vapour pressure (Pa) " PA

140 DEF FNPS (T) = EXP (16.6536-4030.183/T+235)) : saturated vapour

pressure, kPa

150 IF PA = 0 THEN PA = RH * 10 * FNPS (TA) : water vapour pressure,

Pa

160 ICL = .155 * CLO : thermal insulation of

the clothing in m2K/W

38

170 M = MET * 58.15 : metabolic rate in

W/m2

180 W = WME * 58.15 : external work in

W/m2

190 MW = M – W : internal heat

production in the

human body

200 IF ICL u .078 THEN FCL = 1 + 1.29 * ICL

ELSE FCL = 1.05 + 0.645 * ICL : clothing area factor

210 HCF = 12.1 * SQR (VEL) : heat transf. coeff. by

forced convection

220 TAA = TA + 273 : air temperature in

Kelvin

230 TRA = TR + 273 : mean radiant

temperature in Kelvin

240 -----CALCULATE SURFACE TEMPERATURE OF CLOTHING BY

ITERATION ---

250 TCLA = TAA + (35.5-TA) / (3.5 * ICL + .1) : first guess for surface

temperature of clothing

260 P1 = ICL * FCL : calculation term 270

P2 = P1 * 3.96 : calculation term 280

P3 = P1 * 100 : calculation term 290

P4 = P1 * TAA : calculation term

300 P5 = 308.7 - .028 * MW + P2 * (TRA/100) * 4

310 XN = TLCA / 100

320 XF = XN

330 N = 0 : N: number of

iterations

340 EPS = .00015 : stop criteria in

iteration

350 XF = (XF + XN)/2

39

360 HCN =2.38 * ABS (100 * XF – TAA) ^ .25: heat transf. coeff. by natural

convection

370 IF HCF>HCN THEN HC = HCF ELSE HC = HCN

380 XN = (P5 + P4 * HC – P2 * XF ^ 4) / (100 + P3 * HC)

390 N = N + 1

400 IF N > 150 THEN GOTO 550

410 IF ABS (XN – XF) > EPS GOTO 350

420 TCL = 100 * XN - 273 : surface temperature of

the clothing

430 --------------------------HEAT LOSS COMPONENTS -----------------------------

440 HL1 = 3.05 * .001 (5733-6.99 * MW-PA) : heat loss diff. through

skin

450 IF MW > 58.15 THEN HL2 = .42 * (MW – 58.15)

ELSE HL2 = 0! : heat loss by sweating

(comfort)

460 HL3 = 1.7 * .00001 * m * (5867-PA) : latent respiration heat

loss

470 HL4 = .0014 * m * (34 - TA) : dry respiration heat

loss

480 HL5 = 3.96 * FCL * (XN^4 – (TRA/100^4) : heat loss by radiation

500 -------------------------CALCULATE PMV AND PPD ----------------------------

510 TS = .303 * EXP (- .036 * m) + .028 : thermal sensation trans

coeff

520 PMV = TS * (MW – HL1 – HL2 – HL3 – HL4 – HL5 –HL6) : predicted

mean vote

530 PPD = 100 – 95 * EXP (- .03353 * PMV ^ 4 - .2179 * PMV^ 2) : predicted

percentage dissat.

540 GOTO 570

550 PMV = 999999!

560 PPD = 100

570 PRINT:PRINT "OUTPUT" : output

40

580 PRINT " Predicted Mean Vote (PMV): "

:PRINT USING "# # . #": PMV

590 PRINT " Predicted Percent of Dissatisfied (PPD): "

:PRINT USING "# # # . #": PPD

600 PRINT: INPUT "NEXT RUN (Y/N)"; RS

610 IF (RS = "Y" OR RS = "y") THEN RUN

620 END

41

python.exec( "

import math

defcomfPMV(ta, tr, vel, rh =, met, clo, wme):

#returns [pmv, ppd]

#ta, air temperature(c)

#tr, mean radiant temperature(c)

#vel, relative air velocoty (m/s)

#rh, relative humidity (%) Used only this way to input humidity level

#met, metabolic rate (met)

#wme, external work, normally around 0 (met)

pa = rh * 10 exp(16.6536-4030.183/(ta+235))

Icl = 0.155 * clo

m = met * 58.15

w = wme * 58.15

mw = m - w

if (icl<= 0.078):

fcl = 1 + (1.29 * icl)

else:

fcl = 1.05 + (0.645 * Icl)

#heat transf (convection)

hcf = 12.1 * sqr(vel)

taa = ta + 273

tra = tr + 273

tcla = taa + (35.5 - ta)/(3.5 * Icl + 0.1)

p1 = Icl * fcl

p2 = p1 * 3.96

42

p3 = p1* 100

p4 = p1 * taa

p5 = (308.7 - 0.028 * mw) + (p2 * (tra / 100)^4)

xn = tcla /100

xf = tcla /50

eps = 0.00015

n = 0

while abs(xn - xf) >eps:

xf = (xf + xn) / 2

hcn = 2.38 * math.pow(abs(100.0 * xf - taa), 0.25)

if (hcf>hcn):

hc - hcf

else:

hc = hcn

xn = (p5 + p4 * hn = p2 * math.pow(xf, 4)) / (100 + p3 * hc)

n += 1

if (n > 150)

print 'Max iteration exceeded'

return 1

tcl = 100 * xn -273

#heat Loss diffenerce Skin

hl1 = 3.05 * 0.001 * (5733 - (6.99 * mw) - pa)

#heat loss CLO

if mw > 58.15:

hl2 = 0.42

else:

hl2 = 0

43

#latent repiration heat loss

hl3 = 1.7 * 0.00001 * m * (5867 - pa)

#dry respiration heat loss

hl4 = 0.0014 * m * (34 - ta)

#heat loss by rediation

hl5 = 3.96 * fcl * (math.pow(xn, 4) - math.pow(tra / 100,4))

#heat loss bu convection

hl6 = fcl * hc * (tcl - ta)

ts = 0.303 * math.exp(-0.036 * m) + 0.028

PMV = ts * (mw - hl1 - hl2 - hl3 - hl4 - hl5 - hl6)

PPD = 100 - 95 * math.exp(-0.03353 * pow(pmv, 4) - 0.2179 * pow(pmv,

2))

returnpmv

" )

44

AppendicesB. Clothing

45

T-shirt Polo Shirt Shirt

Hoodie Windbreaker Bra

Camisole Tank Top Coverall Dress

Figure B.1 Clothing

46

Maxi Skirt Midi Skirt Mini Skirt Half-slip

Board Shorts Men’s briefs Panties

Slacks Legging Jeans Cropped Pants

Figure B.1Clothing (Continued)

47

Boots Shoes Loafer

Pumps Ankle-Dress Socks Low-Cut Sport

Figure B.1Clothing (Continued)

48

AppendicesC.

53

FigureC.1 Certificate of Conference

54

Biography

Name - Last name: Ms. Metinee Rodoum

Date of Birth: July 30, 1991

Address: 37/3 moo 2, Phadungsawadrd, SalaKlang,

Bang Krui, Nonthaburi, 11130, Thailand

Email: [email protected]

Educational Background

2015-2016 Master of Engineering in Engineering Technology

Thai-Nichi Institute of Technology, Thailand

2010-2014 Bachelor of Engineering in Computer Engineering

Thai-Nichi Institute of Technology, Thailand

Working Experiences

2014-Present Network Engineer

ZyXEL (Thailand) Co., Ltd.

a real-time portable thermal comfort measurement …library.tni.ac.th/thesis/upload/files/thesis...

Documents