INCORPORATING PRODUCT DESIGN INTO THE …...PRESENTATION OUTLINE 1. Background 2. The Use of...

INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO INCORPORATING PRODUCT DESIGN INTO

THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW THE DEVELOPMENT OF NEW

REFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTS

By: Isaac Anderson and Christopher DiGiulioBy: Isaac Anderson and Christopher DiGiulio

[1] Vapor-Compression Refrigeration. Answers.com. 4/27/2007 <http://www.answers.com/topic/vapor-compression-refrigeration>.

PRESENTATION OUTLINEPRESENTATION OUTLINEPRESENTATION OUTLINEPRESENTATION OUTLINEPRESENTATION OUTLINEPRESENTATION OUTLINEPRESENTATION OUTLINEPRESENTATION OUTLINE

1.1. BackgroundBackground2.2. The Use of Consumer Preference Functions The Use of Consumer Preference Functions in Refrigerant Designin Refrigerant Design

3.3. Design of New Refrigerants Based on Design of New Refrigerants Based on Consumer Preference Functions and the Consumer Preference Functions and the Chosen MarketChosen MarketA.A. Discussion of Group Contribution TheoryDiscussion of Group Contribution TheoryB.B. Enumeration Modeling in Excel using Group Enumeration Modeling in Excel using Group Contribution TheoryContribution Theory

4.4. ConclusionsConclusions5.5. RecommendationsRecommendations

BACKGROUNDBACKGROUNDBACKGROUNDBACKGROUNDBACKGROUNDBACKGROUNDBACKGROUNDBACKGROUND

HISTORY OF REFRIGERATIONHISTORY OF REFRIGERATIONHISTORY OF REFRIGERATIONHISTORY OF REFRIGERATIONHISTORY OF REFRIGERATIONHISTORY OF REFRIGERATIONHISTORY OF REFRIGERATIONHISTORY OF REFRIGERATION

•• Refrigeration goes back Refrigeration goes back to ancient timesto ancient times

–– Stored Ice Stored Ice

–– Evaporative Evaporative ProcessesProcesses

•• In 1805, Oliver Evans In 1805, Oliver Evans proposed the use of a proposed the use of a volatile fluid in a closed volatile fluid in a closed cycle to freeze water into cycle to freeze water into iceice

HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF

REFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATION•• EvanEvan’’s theories most likely s theories most likely influenced Jacob Perkins influenced Jacob Perkins and Richard Trevithickand Richard Trevithick

•• They proposed an airThey proposed an air--cycle cycle system in 1828, but it wasnsystem in 1828, but it wasn’’t t built eitherbuilt either

•• Actual refrigerants were Actual refrigerants were introduced in the 1830s introduced in the 1830s with the invention of the with the invention of the vapor compression system vapor compression system by Perkinsby Perkins

[2] Calm, James M. and David A. Didion. "Trade-Offs in Refrigerant Selections: Past, Present and Future." Int. J. Refrig., 21, 308 (1998).

HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF HISTORY OF

REFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATIONREFRIGERATION

•• In 1928, Midgely, Henne, and McNary of GM In 1928, Midgely, Henne, and McNary of GM pioneered work to obtain molecules with pioneered work to obtain molecules with desirable properties using systematic designdesirable properties using systematic design

–– They synthesized all 15 combinations of They synthesized all 15 combinations of one carbon with various combinations of one carbon with various combinations of chlorine, fluorine, and hydrogen. chlorine, fluorine, and hydrogen.

–– They finally chose They finally chose dichlorodifluoromethane (Freon) as dichlorodifluoromethane (Freon) as having the most desirable characteristics, having the most desirable characteristics, thus introducing the first thus introducing the first chlorofluorocarbons chlorofluorocarbons

REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830REFRIGERANTS FROM 1830--------

PRESENTPRESENTPRESENTPRESENTPRESENTPRESENTPRESENTPRESENT

•• First GenerationFirst Generation

–– Generally solvents, fuels Generally solvents, fuels or volatile components or volatile components (whatever worked)(whatever worked)

•• Second GenerationSecond Generation

–– CFCs were introducedCFCs were introduced

•• Third GenerationThird Generation

–– Shift to HCFCsShift to HCFCs

•• Fourth GenerationFourth Generation

–– Focused on refrigerants Focused on refrigerants that do no contribute to that do no contribute to global warmingglobal warming

[3] Calm, James M. and Glenn C. Hourahan. Refrigerant Data Update. January 2007. Heating/Piping/Air Conditioning Engineering. Feb. 7, 2007 <http://www.hpac.com/Issue/Article/44475/Refrigerant Data Update>.

REFRIGERANT PHASEREFRIGERANT PHASEREFRIGERANT PHASEREFRIGERANT PHASEREFRIGERANT PHASEREFRIGERANT PHASEREFRIGERANT PHASEREFRIGERANT PHASE--------OUTOUTOUTOUTOUTOUTOUTOUT

•• 19871987

–– Montreal Protocol established Montreal Protocol established requirements that began the world wide requirements that began the world wide phasephase--out of CFCsout of CFCs

•• 19921992

–– Montreal Protocol established phaseMontreal Protocol established phase--out out for HCFCsfor HCFCs

PHASEPHASEPHASEPHASEPHASEPHASEPHASEPHASE--------OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR

HCFCSHCFCSHCFCSHCFCSHCFCSHCFCSHCFCSHCFCS

•• 2003 2003

–– The amount of all HCFCs that can be produced The amount of all HCFCs that can be produced nationwide must be reduced by 35.0% nationwide must be reduced by 35.0%

•• 20102010

–– The amount of all HCFCs that can be produced The amount of all HCFCs that can be produced nationwide must be reduced by 65.0% nationwide must be reduced by 65.0%

•• 20152015

–– The amount of all HCFCs that can be produced The amount of all HCFCs that can be produced nationwide must be reduced by 90.0%nationwide must be reduced by 90.0%

•• 20202020

–– The amount of all HCFCs that can be produced The amount of all HCFCs that can be produced nationwide must be reduced by 99.5%nationwide must be reduced by 99.5%

•• 20302030

–– No HCFCs can be producedNo HCFCs can be produced

PHASEPHASEPHASEPHASEPHASEPHASEPHASEPHASE--------OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR OUT SCHEDULE FOR

HCFCSHCFCSHCFCSHCFCSHCFCSHCFCSHCFCSHCFCS

THE USE OF CONSUMER THE USE OF CONSUMER THE USE OF CONSUMER THE USE OF CONSUMER THE USE OF CONSUMER THE USE OF CONSUMER THE USE OF CONSUMER THE USE OF CONSUMER

PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN PREFERENCE FUNCTIONS IN

REFRIGERANT DESIGNREFRIGERANT DESIGNREFRIGERANT DESIGNREFRIGERANT DESIGNREFRIGERANT DESIGNREFRIGERANT DESIGNREFRIGERANT DESIGNREFRIGERANT DESIGN

CONSUMER PREFERENCE CONSUMER PREFERENCE CONSUMER PREFERENCE CONSUMER PREFERENCE CONSUMER PREFERENCE CONSUMER PREFERENCE CONSUMER PREFERENCE CONSUMER PREFERENCE

FUNCTIONS AND DEMANDFUNCTIONS AND DEMANDFUNCTIONS AND DEMANDFUNCTIONS AND DEMANDFUNCTIONS AND DEMANDFUNCTIONS AND DEMANDFUNCTIONS AND DEMANDFUNCTIONS AND DEMAND

•• In the design of the potential refrigerants, consumer preferenceIn the design of the potential refrigerants, consumer preferencefunctions were used to evaluate refrigerant properties functions were used to evaluate refrigerant properties

•• Consumer preference functions can also be used to solve for the Consumer preference functions can also be used to solve for the demand demand (d(d11) of a new refrigerant when it is in competition with an existin) of a new refrigerant when it is in competition with an existing g refrigerantrefrigerant

•• In the In the following equation, following equation, ββ is the only variable dependent on consumer is the only variable dependent on consumer preference functionspreference functions

Where: Where: Y is the market potentialY is the market potentialP is the priceP is the priceD is the demandD is the demandρρ was set to a constant value of 0.76was set to a constant value of 0.76αα is the consumer awareness of our productis the consumer awareness of our productββ relative consumer preferencerelative consumer preferenceThe subscript 1 refers to the new productThe subscript 1 refers to the new productThe subscript 2 refers to the existing comparison productThe subscript 2 refers to the existing comparison product

0)( 1

1

2

112111 =

−

−=−

ρρρ

βαφ d

p

dpYpdpd

DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF αα

•• Alpha is the consumer Alpha is the consumer awareness of the new awareness of the new refrigerant as a function refrigerant as a function of time.of time.

•• The plots on the right The plots on the right show the values of alpha show the values of alpha that were used when that were used when calculating the demandcalculating the demand

•• The bottom figure The bottom figure illustrates the effect of illustrates the effect of increases advertisingincreases advertising

Alpha vs. Time

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10

Time (Years)

Alp

ha

Alpha vs. Time

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10

Time (Years)

Alp

ha

DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF DEVELOPMENT OF ββ

•• The equation used to derive The equation used to derive ββ is as followsis as follows

•• Where HWhere Hii is the respective consumer is the respective consumer preference of each productpreference of each product

Where : Where : ωωi i is the weight of refrigerant propertyis the weight of refrigerant property

yyi i is the property score of each refrigerant propertyis the property score of each refrigerant property

1

2 )(

H

preferencencompetitioH=β

∑= iii yH ω


FUNCTIONSFUNCTIONSFUNCTIONSFUNCTIONSFUNCTIONSFUNCTIONSFUNCTIONSFUNCTIONS

•• Consumer preference functions Consumer preference functions predict consumer reactions to predict consumer reactions to different refrigerant design different refrigerant design propertiesproperties

•• The consumer preference The consumer preference functions were estimated using functions were estimated using expected consumer reactions to expected consumer reactions to refrigerant properties refrigerant properties

WHAT MAKES A GOOD WHAT MAKES A GOOD WHAT MAKES A GOOD WHAT MAKES A GOOD WHAT MAKES A GOOD WHAT MAKES A GOOD WHAT MAKES A GOOD WHAT MAKES A GOOD

REFRIGERANT?REFRIGERANT?REFRIGERANT?REFRIGERANT?REFRIGERANT?REFRIGERANT?REFRIGERANT?REFRIGERANT?

•• Safe: nonSafe: non--toxic, nonflammable, and toxic, nonflammable, and nonexplosivenonexplosive

•• Environmentally friendly: low ODP, low GWPEnvironmentally friendly: low ODP, low GWP

•• Compatible with existing refrigeration Compatible with existing refrigeration materialsmaterials

•• Desirable thermodynamic characteristics: high Desirable thermodynamic characteristics: high latent heat, low compression ratio, low specific latent heat, low compression ratio, low specific heat of liquidheat of liquid

•• Stable at operating temperaturesStable at operating temperatures



•• Based on 6 characteristicsBased on 6 characteristics–– FlammabilityFlammability

–– ExplosivenessExplosiveness

–– ToxicityToxicity

–– Global Warming PotentialGlobal Warming Potential

–– Ozone Depletion PotentialOzone Depletion Potential

–– Coefficient of PerformanceCoefficient of Performance

•• The outlook for discovery or synthesis of ideal The outlook for discovery or synthesis of ideal refrigerants is extremely unlikely. Traderefrigerants is extremely unlikely. Trade--offs offs among desired objectives are necessary to among desired objectives are necessary to achieve balanced solutionsachieve balanced solutions44

[4] Calm, James M. and David A. Didion. "Trade-Offs in Refrigerant Selections: Past, Present and Future." Int. J. Refrig., 21, 308 (1998).

SURVEY 1SURVEY 1SURVEY 1SURVEY 1SURVEY 1SURVEY 1SURVEY 1SURVEY 1

7

8

10

9

10

8

Expected consumer response

ESTIMATING ESTIMATING ESTIMATING ESTIMATING ESTIMATING ESTIMATING ESTIMATING ESTIMATING ωωiiiiiiii

•• This figure represents This figure represents the expected weights of the expected weights of the refrigerant the refrigerant propertiesproperties

•• It can be seenIt can be seen

that efficiencythat efficiency

is the most is the most

important property important property

to consumersto consumers

Weighted Consumer Preferences

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Co

effi

cien

t o

fP

erfo

rman

ce

Fla

mm

abil

ity

To

xici

ty

Exp

losi

on

Po

ten

tial

Glo

bal

War

min

gP

ote

nti

al

Ozo

ne

Dep

leti

on

Po

ten

tial

wi%

(w

her

e Σ

wi=

100%

)

`

Property Score vs. Sw eetness

0.00

0.20

0.40

0.60

0.80

1.00

Not Sweet

Semi Sweet

Very Sweet

Sweet Inedible Sweetness

Property Score vs. Sw eetness

0.00

0.20

0.40

0.60

0.80

1.00

Not Sweet

Semi Sweet

Very Sweet

Sweet Inedible Sweetness

SURVEY 2SURVEY 2SURVEY 2SURVEY 2SURVEY 2SURVEY 2SURVEY 2SURVEY 2

•• Each of the properties from Survey 1 are examined Each of the properties from Survey 1 are examined individuallyindividually

•• This Survey provides a correlation between consumer This Survey provides a correlation between consumer satisfaction and design properties satisfaction and design properties

•• Example Example –– ““Donut DesignDonut Design””

P r ope r t y S c or e v s. C onc . S uga r

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.4 0.8 1.2 1.6

Conc. of Sugar (g/cm 3)

Pro

per

ty S

core

Consumer Satisfaction vs. Sweetness

SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– EFFICIENCYEFFICIENCYEFFICIENCYEFFICIENCYEFFICIENCYEFFICIENCYEFFICIENCYEFFICIENCY

Property Score vs. Efficiency

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Pro

pert

y S

core

Not Efficient

Marginally Efficient

Efficient Highly Efficient

Extremely Efficient

Property Score vs. Efficiency

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Pro

pert

y S

core

Not Efficient

Marginally Efficient

Efficient Highly Efficient

Extremely Efficient

Consumer Satisfaction vs. Efficiency Property Score vs. ∆Hve/Cp

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.5 1 1.5 2 2.5 3

∆Hve/Cp

Pro

per

ty S

core

SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– FLAMMABILITYFLAMMABILITYFLAMMABILITYFLAMMABILITYFLAMMABILITYFLAMMABILITYFLAMMABILITYFLAMMABILITY

Property Score vs. Flash Point

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0.90

1.00

0 50 100 150 200 250

Flash Point (F)

Pro

per

ty S

core

Property Score vs. Flammability

0.00

0.10

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0.70

0.80

0.90

1.00

Pro

pert

y S

core

Non Flammable

Slightly Flammable

FlammableHighly Flammable

Extremely Flammable

Property Score vs. Flammability

0.00

0.10

0.20

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0.40

0.50

0.60

0.70

0.80

0.90

1.00

Pro

pert

y S

core

Non Flammable

Slightly Flammable

FlammableHighly Flammable

Extremely Flammable

Consumer Satisfaction vs. Flammability

SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– TOXICITYTOXICITYTOXICITYTOXICITYTOXICITYTOXICITYTOXICITYTOXICITY

Property Score vs. LD50 Conc.

0.00

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0.70

0.80

0.90

1.00

0 500 1000 1500 2000 2500 3000

LD50 (mg/kg)

Pro

per

ty S

core

Property Score vs. Toxicity

0.00

0.10

0.20

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0.40

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0.80

0.90

1.00

Pro

pert

y S

core

Non Toxic

Very Slightly Toxic

Slightly Toxic

Moderately Toxic

Highly Toxic

Extremely Toxic

Property Score vs. Toxicity

0.00

0.10

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0.40

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0.90

1.00

Pro

pert

y S

core

Non Toxic

Very Slightly Toxic

Slightly Toxic

Moderately Toxic

Highly Toxic

Extremely Toxic

Consumer Satisfaction vs. Toxicity

SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– EXPLOSION EXPLOSION EXPLOSION EXPLOSION EXPLOSION EXPLOSION EXPLOSION EXPLOSION

POTENTIALPOTENTIALPOTENTIALPOTENTIALPOTENTIALPOTENTIALPOTENTIALPOTENTIAL

Property Score vs. Explosion Potential

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1.00

Pro

pert

y S

core

No RiskLow RiskModerate Risk

High RiskExtremely Risk

Property Score vs. Explosion Potential

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0.90

1.00

Pro

pert

y S

core

No RiskLow RiskModerate Risk

High RiskExtremely Risk

Property Score vs. LEL

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0.80

0.90

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0 2 4 6 8 10 12 14 16

LEL (%)

Pro

per

ty S

core

Consumer Satisfaction vs. Explosion Potential

SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING


Property Score vs. GWP

0.00

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0.80

0.90

1.00

0 1000 2000 3000 4000 5000 6000

GWP (Rel. CO2)

Pro

per

ty S

core

Property Score vs. Global Warming Potential

0.00

0.10

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0.30

0.40

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0.60

0.70

0.80

0.90

1.00

Pro

pert

y S

core

No GWP

Very Slight GWP

Slight GWP

Moderate GWP

High GWP

Extremely High GWP

Property Score vs. Global Warming Potential

0.00

0.10

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0.40

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0.70

0.80

0.90

1.00

Pro

pert

y S

core

No GWP

Very Slight GWP

Slight GWP

Moderate GWP

High GWP

Extremely High GWP

Consumer Satisfaction vs. GWP

SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING GLOBAL WARMING


SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 SURVEY 2 –––––––– OZONE DEPLETION OZONE DEPLETION OZONE DEPLETION OZONE DEPLETION OZONE DEPLETION OZONE DEPLETION OZONE DEPLETION OZONE DEPLETION

POTENTIAL POTENTIAL POTENTIAL POTENTIAL POTENTIAL POTENTIAL POTENTIAL POTENTIAL

Property Score vs. ODP

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1.00

0 2 4 6 8 10 12 14 16

ODP (Rel. to CCl3F)

Pro

per

ty S

core

Property Score vs. Ozone Depletion Potential

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0.90

1.00

Pro

pert

y S

core

No ODP

Very Slight ODP

Slight ODP

Moderate ODP

High ODP

Extremely High ODP

Property Score vs. Ozone Depletion Potential

0.00

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0.30

0.40

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0.80

0.90

1.00

Pro

pert

y S

core

No ODP

Very Slight ODP

Slight ODP

Moderate ODP

High ODP

Extremely High ODP

Consumer Satisfaction vs. ODP

SOLVING FOR THE MARKET SOLVING FOR THE MARKET SOLVING FOR THE MARKET SOLVING FOR THE MARKET SOLVING FOR THE MARKET SOLVING FOR THE MARKET SOLVING FOR THE MARKET SOLVING FOR THE MARKET

POTENTIAL (Y)POTENTIAL (Y)POTENTIAL (Y)POTENTIAL (Y)POTENTIAL (Y)POTENTIAL (Y)POTENTIAL (Y)POTENTIAL (Y)

•• Before the market potential can be solved for, a Before the market potential can be solved for, a market must be definedmarket must be defined

•• Possible Markets for New Refrigerants Possible Markets for New Refrigerants include:include:–– Air conditioning for homes and commercial Air conditioning for homes and commercial buildingsbuildings–– Air conditioning of personal cars, trucks and Air conditioning of personal cars, trucks and sport utility vehiclessport utility vehicles–– Refrigerated transportation (food, animals, Refrigerated transportation (food, animals, beer, medical supplies etc.)beer, medical supplies etc.)–– Refrigerators and freezersRefrigerators and freezers–– Industrial operationsIndustrial operations

CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD CENTRAL AIR/HOUSEHOLD

UNITSUNITSUNITSUNITSUNITSUNITSUNITSUNITS

•• In 2006, the number In 2006, the number of total housing units of total housing units in the US was 124.4 in the US was 124.4 Million UnitsMillion Units

•• The number of air The number of air conditioners sold in conditioners sold in the US is estimated to the US is estimated to reach 10.7 million reach 10.7 million units in 2008units in 2008

5US Air Conditioners 2004.

AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005AUTOMOBILES SOLD IN 2005

•• The automotive The automotive industry offers industry offers higher numbers of higher numbers of units sold per yearunits sold per year

•• Advantage of the Advantage of the automotive marketautomotive market

–– Higher VolumeHigher Volume

Number of cars purchased in 2005 (by country)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

USA Japan China UK

Un

its

in M

illi

on

s

ESTIMATING THE MARKET ESTIMATING THE MARKET ESTIMATING THE MARKET ESTIMATING THE MARKET ESTIMATING THE MARKET ESTIMATING THE MARKET ESTIMATING THE MARKET ESTIMATING THE MARKET

POTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKETPOTENTIAL OF THE AUTO MARKET

•• In this study, the automotive In this study, the automotive market was chosen because it market was chosen because it offers higher volume in salesoffers higher volume in sales

•• The market potential was The market potential was estimated by multiplying estimated by multiplying automotive sales by an average automotive sales by an average refrigerant volume required of refrigerant volume required of 24oz.24oz.

•• The answer obtained was The answer obtained was approximately 14.2 thousand approximately 14.2 thousand metric tons per yearmetric tons per year

COMPARING THIS VALUE TO COMPARING THIS VALUE TO COMPARING THIS VALUE TO COMPARING THIS VALUE TO COMPARING THIS VALUE TO COMPARING THIS VALUE TO COMPARING THIS VALUE TO COMPARING THIS VALUE TO

DATA PROVIDED BY THE DATA PROVIDED BY THE DATA PROVIDED BY THE DATA PROVIDED BY THE DATA PROVIDED BY THE DATA PROVIDED BY THE DATA PROVIDED BY THE DATA PROVIDED BY THE UNFCCCUNFCCCUNFCCCUNFCCCUNFCCCUNFCCCUNFCCCUNFCCC

•• The market potential was then compared to information The market potential was then compared to information obtained from obtained from United Nations Framework Convention on United Nations Framework Convention on Climate ChangeClimate Change (UNFCCC). The table is on the following (UNFCCC). The table is on the following slideslide

•• The UNFCCC provides the amounts of varying The UNFCCC provides the amounts of varying refrigerants produced by the participating countriesrefrigerants produced by the participating countries–– These countries are Australia, Colombia, the European These countries are Australia, Colombia, the European Union and its member states, Japan, Switzerland and the Union and its member states, Japan, Switzerland and the USA.USA.

•• Using the aforementioned estimation, it was calculated Using the aforementioned estimation, it was calculated that the US accounts for 1/10that the US accounts for 1/10thth RR--134a production cited 134a production cited by UNFCCCby UNFCCC

•• This value seems reasonable given the volume of This value seems reasonable given the volume of automobile purchased each yearautomobile purchased each year

PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA PRODUCTION & RELEASE DATA

PROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCCPROVIDED BY THE UNFCCC

HOLE IN THE OZONEHOLE IN THE OZONEHOLE IN THE OZONEHOLE IN THE OZONEHOLE IN THE OZONEHOLE IN THE OZONEHOLE IN THE OZONEHOLE IN THE OZONE

DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS DESIGN OF NEW REFRIGERANTS

BASED ON CONSUMER BASED ON CONSUMER BASED ON CONSUMER BASED ON CONSUMER BASED ON CONSUMER BASED ON CONSUMER BASED ON CONSUMER BASED ON CONSUMER

PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND PREFERENCE FUNCTIONS AND

THE CHOSEN MARKETTHE CHOSEN MARKETTHE CHOSEN MARKETTHE CHOSEN MARKETTHE CHOSEN MARKETTHE CHOSEN MARKETTHE CHOSEN MARKETTHE CHOSEN MARKET

METHODS FOR EXAMINING METHODS FOR EXAMINING METHODS FOR EXAMINING METHODS FOR EXAMINING METHODS FOR EXAMINING METHODS FOR EXAMINING METHODS FOR EXAMINING METHODS FOR EXAMINING

REFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTSREFRIGERANTS

Analysis from a listAnalysis from a list

•• Only known molecules Only known molecules can be consideredcan be considered

•• Extensive database is Extensive database is necessary for complete necessary for complete analysisanalysis

•• Limited to molecules Limited to molecules already identified as already identified as refrigerantsrefrigerants

Group contribution Group contribution theorytheory

•• Allows for the Allows for the consideration of consideration of unknown moleculesunknown molecules

•• No need for extensive No need for extensive databasesdatabases

•• Generalized approachGeneralized approach

DISCUSSION OF GROUP DISCUSSION OF GROUP DISCUSSION OF GROUP DISCUSSION OF GROUP DISCUSSION OF GROUP DISCUSSION OF GROUP DISCUSSION OF GROUP DISCUSSION OF GROUP

CONTRIBUTION THEORYCONTRIBUTION THEORYCONTRIBUTION THEORYCONTRIBUTION THEORYCONTRIBUTION THEORYCONTRIBUTION THEORYCONTRIBUTION THEORYCONTRIBUTION THEORY

GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION

THEORYTHEORYTHEORYTHEORYTHEORYTHEORYTHEORYTHEORY

•• Developed by observation of existing Developed by observation of existing molecules as a way to predict the basic molecules as a way to predict the basic characteristics of ANY moleculecharacteristics of ANY molecule

•• Uses characteristics of each functional Uses characteristics of each functional group to estimate the characteristics of a group to estimate the characteristics of a molecule formed from the functional molecule formed from the functional groupsgroups

MOLECULE MADE OF MOLECULE MADE OF MOLECULE MADE OF MOLECULE MADE OF MOLECULE MADE OF MOLECULE MADE OF MOLECULE MADE OF MOLECULE MADE OF

FUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPS

•• Specific groups of Specific groups of atoms within a atoms within a moleculemolecule

•• Responsible for the Responsible for the chemical makechemical make--up of up of the moleculethe molecule

•• Example: Example:

–– 3 different 3 different functional group functional group typestypes

–– 6 total groups6 total groups1,1,1,2-Tetrafluoroethane

FUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPSFUNCTIONAL GROUPS

=O=O

--COOCOO--=C==C=

--NO2NO2--COOHCOOH=C<=C<

--CNCN--CHOCHO=CH=CH--

R=NR=N--2R>CO2R>COR=C<2RR=C<2R=CH2=CH2

>N>N-->CO>CO--IIR=CHR=CH--RR>C<>C<

RR--SS--RR2R>NH2R>NHRR--OO--RR--BrBr2R>C<2R2R>C<2R>CH>CH--

--SS-->NH>NH--OO----ClCl2R>CH2R>CH--RR--CH2CH2--

--SHSH--NH2NH2--OHOH--FFRR--CH2CH2--RR--CH3CH3

Sulfur Sulfur GroupsGroups

Nitrogen Nitrogen GroupsGroups

Oxygen Oxygen GroupsGroups

Halogen Halogen GroupsGroups

Cyclic Cyclic GroupsGroups

Acyclic Acyclic GroupsGroups

= represents a double bond, bonding site

-- represents a single bond, bonding site

R represents a ring bonding site

ENUMERATION MODELING IN ENUMERATION MODELING IN ENUMERATION MODELING IN ENUMERATION MODELING IN ENUMERATION MODELING IN ENUMERATION MODELING IN ENUMERATION MODELING IN ENUMERATION MODELING IN

EXCEL USING GROUP EXCEL USING GROUP EXCEL USING GROUP EXCEL USING GROUP EXCEL USING GROUP EXCEL USING GROUP EXCEL USING GROUP EXCEL USING GROUP


ENUMERATION VS. ENUMERATION VS. ENUMERATION VS. ENUMERATION VS. ENUMERATION VS. ENUMERATION VS. ENUMERATION VS. ENUMERATION VS.

OPTIMIZATIONOPTIMIZATIONOPTIMIZATIONOPTIMIZATIONOPTIMIZATIONOPTIMIZATIONOPTIMIZATIONOPTIMIZATION

EnumerationEnumeration

•• No initial guess requiredNo initial guess required

•• Calculates every possible Calculates every possible optionoption

•• Complete confidence in Complete confidence in solutionsolution

•• Very time consumingVery time consuming ––requires hours or days requires hours or days for processingfor processing

Optimization ModelOptimization Model

•• Requires a good initial Requires a good initial guessguess

•• Calculates only options Calculates only options which lead to a more which lead to a more likely solutionlikely solution

•• Almost complete Almost complete confidence in solutionconfidence in solution

•• Less time consuming Less time consuming ––requires a few hours for requires a few hours for

processingprocessing

WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION WHAT IS THE ENUMERATION

METHOD?METHOD?METHOD?METHOD?METHOD?METHOD?METHOD?METHOD?

•• Also known as the exhaustive method or brute force Also known as the exhaustive method or brute force methodmethod

•• Take into account every possible combination of Take into account every possible combination of functional groupsfunctional groups

-CH3 n-CH3 = 0 1 2

-CH2- n-CH2-= 0 1 2 0 1 2 0 1 2

>CH- n>CH-= 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2

Iterations for 3x3 = 27

VBA CODEVBA CODEVBA CODEVBA CODEVBA CODEVBA CODEVBA CODEVBA CODE

REFRIGERANT MODELINGREFRIGERANT MODELINGREFRIGERANT MODELINGREFRIGERANT MODELINGREFRIGERANT MODELINGREFRIGERANT MODELINGREFRIGERANT MODELINGREFRIGERANT MODELING

Our designOur design

1.1. Design Basic Thermodynamic Design Basic Thermodynamic OptimizationOptimization

2.2. Include structural constraintsInclude structural constraints

3.3. Include physical constraintsInclude physical constraints

4.4. Find information on existing Find information on existing moleculesmolecules

5.5. Select molecules for further researchSelect molecules for further research

FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM FLOW OF VARIABLES FROM

GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION GROUP CONTRIBUTION

THEORYTHEORYTHEORYTHEORYTHEORYTHEORYTHEORYTHEORY

HOW TO USE GROUP HOW TO USE GROUP HOW TO USE GROUP HOW TO USE GROUP HOW TO USE GROUP HOW TO USE GROUP HOW TO USE GROUP HOW TO USE GROUP


Tb=Boiling temperatureTb=Boiling temperatureTbi=contribution of group i to Tbi=contribution of group i to

boiling temperatureboiling temperatureTc=critical temperatureTc=critical temperatureTci= contribution of group i to critical Tci= contribution of group i to critical temperaturetemperature

ai=number of atoms in group iai=number of atoms in group iPci= contribution of group i to critical Pci= contribution of group i to critical pressurepressure

Tavg= average temperature (user Tavg= average temperature (user defined)defined)

Cp0ai=Cp0ai=a a contribution to heat contribution to heat capacity capacity

Cp0bi=Cp0bi=b b contribution to heat contribution to heat capacity capacity

Cp0ci=Cp0ci=c c contribution to heat contribution to heat capacity capacity

Cp0di=Cp0di=d d contribution to heat contribution to heat capacity capacity at average at average

temperature temperature *** Equations 1*** Equations 1--4 are the only ones 4 are the only ones dependent upon values of nidependent upon values of ni

3

1

70

2

1

40

10

100

*10*06.2*

*10*91.3*

*21.0*93.37*

avg

N

idipi

avg

N

icipi

avg

N

ibipi

N

iaipiap

TCn

TCn

TCnCnC

−+

−+

−+−=

∑

∑

∑∑

=

−

=

−

==

2

1 1

***0032.0113.0

1

−+

=

∑ ∑= =

N

i

N

iciiii

c

Pnan

P

∑ ∑= =

−+

=N

i

N

iciicii

bc

TnTn

TT

1

2

1

***965.0584.0(

∑=

+=N

ibiib TnT

1

*21.198

THERMODYNAMIC THERMODYNAMIC THERMODYNAMIC THERMODYNAMIC THERMODYNAMIC THERMODYNAMIC THERMODYNAMIC THERMODYNAMIC

EQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONS•• Liquid Heat Capacity at TLiquid Heat Capacity at Tavgavg

•• Heat of vaporization at boiling temperature (Riedel Heat of vaporization at boiling temperature (Riedel Method)Method)

•• Heat of vaporization at evaporation temperatureHeat of vaporization at evaporation temperature

( )( )

−+

−++

−++=

avgravgr

avgr

avgrappla TT

T

TCC

1

742.11*2.2511.17**25.0

1

45.045.1*314.8*

1868.4

13/1

0 ω

( )

−−

=∆br

cbrcvb T

PTTRH

930.0

013.1ln****093.1

38.0

1

1*

−−

∆=∆cb

cevpvbve TT

TTHH

PRESSURE EQUATIONSPRESSURE EQUATIONSPRESSURE EQUATIONSPRESSURE EQUATIONSPRESSURE EQUATIONSPRESSURE EQUATIONSPRESSURE EQUATIONSPRESSURE EQUATIONS

•• Vapor pressure at condensing Vapor pressure at condensing

•• Vapor pressure at evaporationVapor pressure at evaporation

( ) ( )( )[ ]32 13*1*ln cndrcndrcndrcndr

vpcr TTkTT

GP −++−−=

( ) ( )( )[ ]32 13*1*ln evprevprevprevpr

vper TTkTT

GP −++−−=

cvpcrvpc PPP *=

cvpervpe PPP *=

GROUP COMBINATION GROUP COMBINATION GROUP COMBINATION GROUP COMBINATION GROUP COMBINATION GROUP COMBINATION GROUP COMBINATION GROUP COMBINATION

CONSTRAINTS CONSTRAINTS CONSTRAINTS CONSTRAINTS CONSTRAINTS CONSTRAINTS CONSTRAINTS CONSTRAINTS

1.1. Structural feasibilityStructural feasibility

2.2. Size and molecular weightSize and molecular weight

3.3. Vapor pressureVapor pressure

STRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITYSTRUCTURAL FEASIBILITY

•• Even number of groups with odd number of Even number of groups with odd number of bonding sitesbonding sites•• 2 2 ““--CH3CH3”” groups or 1 groups or 1 ““--CH3CH3”” group and 1 group and 1 ““>CH>CH--”” groupgroup

•• Groups must be able to connect to form Groups must be able to connect to form ONE moleculeONE molecule•• 2 2 ““--CH3CH3”” groups cannot connect with 2 groups cannot connect with 2 ““--FF””groups to make ONE moleculegroups to make ONE molecule

•• Total number of bonding sites should be Total number of bonding sites should be eveneven•• 2 bonding sites make 1 bond2 bonding sites make 1 bond

STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY STRUCTURAL FEASIBILITY

CONCONCONCONCONCONCONCON’’’’’’’’DDDDDDDD

•• Number of each bonding type should be even Number of each bonding type should be even •• 2 2 ““=CH2=CH2”” groups, 2 groups, 2 ““=O=O”” groups, or 1 groups, or 1 ““=CH2=CH2”” with 1 with 1 ““=C==C=”” with 1 with 1 ““=O=O”” groupgroup

•• Mixed bonding types should have a transition Mixed bonding types should have a transition groupgroup

•• 1 1 ““=CH2=CH2”” and 1 and 1 ““--FF”” requires 1 requires 1 ““=CH=CH--”” groupgroup

•• Every branch should have an edge (end cap)Every branch should have an edge (end cap)•• Example: 1 Example: 1 ““>C<>C<”” group have 4 branches which will group have 4 branches which will require 4 groups with only 1 bonding site such as require 4 groups with only 1 bonding site such as ““--FF””

MOLECULAR SIZEMOLECULAR SIZEMOLECULAR SIZEMOLECULAR SIZEMOLECULAR SIZEMOLECULAR SIZEMOLECULAR SIZEMOLECULAR SIZE

•• Minimum number of groups is 2Minimum number of groups is 2

•• Maximum number of groups is 10Maximum number of groups is 10–– Max groups by type:Max groups by type:

one bond = 7 one bond = 7 –– CC--CHCH--C(F)C(F)77=10=10

two bonds = 8 two bonds = 8 –– CHCH33--(CH(CH22))88--CHCH33=10 =10

three bonds = 4 three bonds = 4 –– (CH)(CH)44(F)(F)66=10=10

four bonds = 2 four bonds = 2 –– (C)(C)33(F)(F)88=11=11

•• Our results show that the maximum number of Our results show that the maximum number of groups used is 9groups used is 9

•• Typically larger molecules have higher boiling Typically larger molecules have higher boiling points making them unfit for refrigerationpoints making them unfit for refrigeration

VAPOR PRESSUREVAPOR PRESSUREVAPOR PRESSUREVAPOR PRESSUREVAPOR PRESSUREVAPOR PRESSUREVAPOR PRESSUREVAPOR PRESSURE

•• Minimum vapor pressure at evaporation Minimum vapor pressure at evaporation temperature of 1 bartemperature of 1 bar

–– Atmospheric pressureAtmospheric pressure

•• Maximum vapor pressure at Maximum vapor pressure at condensation of 10 barcondensation of 10 bar

–– Mechanical compressibility factorMechanical compressibility factor

–– MultiMulti--stage compressor (cost prohibitive)stage compressor (cost prohibitive)

•• Heat capacity must be positiveHeat capacity must be positive

–– Negative heat capacity is not possible Negative heat capacity is not possible physicallyphysically

““““““““MAKINGMAKINGMAKINGMAKINGMAKINGMAKINGMAKINGMAKING”””””””” A MOLECULEA MOLECULEA MOLECULEA MOLECULEA MOLECULEA MOLECULEA MOLECULEA MOLECULE

•• nn--F F = 2= 2

•• nn--Cl Cl = 2= 2

•• nn>C< >C< = 1= 1

•• FreonFreon

•• nn--------CH3CH3CH3CH3CH3CH3CH3CH3 = 2= 2

•• nn--CH2CH2--= 2= 2

•• ButaneButane

•• nn--CH3 CH3 = 3= 3

•• nn>CH>CH--= 1= 1

•• isoiso--butanebutane

•• nn--CH3 CH3 = 2= 2

•• nn>CH>CH-- = 1= 1

•• nn--CH2CH2--= 1= 1

•• nn--OH OH = 1= 1

•• isoiso--butanolbutanol

•• nn=CH2 =CH2 = 1= 1

•• nn=C< =C< = 1= 1

•• nn--OO-- = 1= 1

•• nn--F F = 2= 2

•• ????

MOLECULE MAKERMOLECULE MAKERMOLECULE MAKERMOLECULE MAKERMOLECULE MAKERMOLECULE MAKERMOLECULE MAKERMOLECULE MAKER

n= Pvpe FALSE 0 Tavg K 294sCH3 2 Pvpc FALSE 0 Tevp K 272

sCH2s 2 heatcap TRUE 1 Tcnd K 317ssCHs 2 0 N groups 6ssCss 0 Tboil K 334.61dCH2 0 Ynt true 1 Tcrit K 499.73 dCHs 0 oddfree true 1 Pcrit bar 35.01 dCss 0 connected true 1 heatcap J/molK 0.131dCd 0 nofree true 1 Tb reduced 0.670

rCH2r 0 bond type true 1 Tavg reduced K 0.588rrCHr 0 singlefree true 1 Tcnd reduced 0.633rrCrr 0 double free true 1 Tevp reduced 0.544

drCHr 0 triple free true 1 alpha -0.942drCrr 0 single cyclic free true 1 beta -2.734sF 0 double cyclic free true 1 omega 0.345sCl 0 mixed true 1 heat capacity J/molK 45.325sBr 0 end cap false 0 enthalpy of vaporization boil tempkJ/mol 29.502sI 0 real structure 0 enthalpy of vaporization evap tempkJ/mol 33.335

sOH 0 h 7.179sOs 0 Yss 1 G 3.790rOr 0 Ydd 0 ka 0.561

ssCO 0 Ytt 0 Pvpcr 0.015rrCO 0 Ysr 0 Pvper 0.002

sCHO 0 Ydr 0 Pvpc bar 0.533sCOOH 0 Yr 0 Pvpe bar 0.070sCOOs 0 Ysd 0 t= 0.000

doO 0 Yst 0sNH2 0 Yssr 0ssNH 0 Ysdr 0rrNH 0 Ydsr 0 iterationsssNs 0 Y0m 1 27drNs 0 Ym5 0sCN 0 Ym1 1

sNO2 0 Ym6 0sSH 0 Ym2 1sSs 0 Ym7 0rSr 0 Ym3 1

6 Ym8 0Ym4 1Ym9 0

Binary Variables

Physical Constraints Thermodynamic Properties

Structural Constraints

RESULTS FROM EXCELRESULTS FROM EXCELRESULTS FROM EXCELRESULTS FROM EXCELRESULTS FROM EXCELRESULTS FROM EXCELRESULTS FROM EXCELRESULTS FROM EXCEL

•• 3,692,945 possible solutions (16 hours)3,692,945 possible solutions (16 hours)

•• 649 solutions649 solutions

•• 566 structurally feasible solutions (passed the 566 structurally feasible solutions (passed the filter, but not feasible)filter, but not feasible)

•• Since each solution was evaluated by Since each solution was evaluated by referencing online databases the process for referencing online databases the process for finding molecules was extremely tediousfinding molecules was extremely tedious

•• are included in optimization function are included in optimization function calculations for comparisoncalculations for comparison

ββ VALUESVALUESVALUESVALUESVALUESVALUESVALUESVALUES

•• Using the preceding six quantitative plots, a value for Using the preceding six quantitative plots, a value for ββfor each possible refrigerant can be definedfor each possible refrigerant can be defined

Chemical Formula H = Σxiyij β = H2/H1 Rank

CH2=CH-F 0.61 1.39 2CH3 -CH=CH2 0.61 1.39 4

CH2=CF2 0.51 1.68 8CH2=CH-Cl 0.50 1.69 1CH2=CFCl 0.49 1.75 3

CH2=C=CH-F 0.40 2.13 5CH2=CH-O-F 0.40 2.14 6

CH2=CH-C(=O)-F 0.40 2.14 20Cl2 0.40 2.15 7F-Br 0.39 2.17 9

CH2=CCH3F 0.39 2.17 10CH2=CH-CH2-F 0.39 2.18 11

CH2=C=CF2 0.39 2.18 12CH2=C=C=C=O 0.39 2.19 13

FSH 0.39 2.19 14CH2=C(-F)-O-F 0.39 2.19 15

FNH2 0.39 2.19 16cyc(CH=CH-CH2) 0.39 2.19 17

cyc(CH=CH-O) 0.39 2.20 18O=CH-Br 0.38 2.22 19

R134a 0.85 1.00 -

LIMITATIONS OF GROUP LIMITATIONS OF GROUP LIMITATIONS OF GROUP LIMITATIONS OF GROUP LIMITATIONS OF GROUP LIMITATIONS OF GROUP LIMITATIONS OF GROUP LIMITATIONS OF GROUP


•• Actual data compared with data found using functional Actual data compared with data found using functional group theory group theory

abs(Tabs(Tb(theory)b(theory)--TTb(act)b(act))= )= ∆∆TTbb

•• Average Average ∆∆TTbb = 39.7K= 39.7K

•• Examples: Examples:

33--fluorofluoro--11--propene, min propene, min ∆∆TTbb=1.2K=1.2K

11--fluorofluoro--22--propanonepropanone, max , max ∆∆TTbb=89.9K=89.9K

12%12%14%14%16%16%averageaverage

0.5%0.5%1.1%1.1%0.4%0.4%minmin

36%36%32%32%47%47%maxmax

PPcritcritTTcritcritTTboilboil

ERROERRORR

LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL LIMITATIONS OF FUNCTIONAL

GROUP THEORYGROUP THEORYGROUP THEORYGROUP THEORYGROUP THEORYGROUP THEORYGROUP THEORYGROUP THEORY

•• Errors reveal inconsistencies with Errors reveal inconsistencies with functional group theoryfunctional group theory

•• Possibly good refrigerants were likely Possibly good refrigerants were likely excluded from our findingsexcluded from our findings

RECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONSRECOMMENDATIONS


1.1. Develop correlations to relate data obtained from models to Develop correlations to relate data obtained from models to consumer preference functions. Relationships could be consumer preference functions. Relationships could be developed to relate properties that can be found from the developed to relate properties that can be found from the empirical data to those exclusive to an individual molecule. empirical data to those exclusive to an individual molecule.

2.2. Link spreadsheets to databases to quickly search through Link spreadsheets to databases to quickly search through molecules. Not all properties can be examined from a molecules. Not all properties can be examined from a moleculemolecule’’s empirical formula or structure. Many s empirical formula or structure. Many databases, in periodicals, for potential refrigerant databases, in periodicals, for potential refrigerant molecules are available for possible refrigerants. These molecules are available for possible refrigerants. These databases could eliminate error caused by property databases could eliminate error caused by property estimation. estimation.

3.3. A large scale survey needs to be performed. A large scale A large scale survey needs to be performed. A large scale random survey is needed to find actual consumer random survey is needed to find actual consumer preferences to refrigerant properties. preferences to refrigerant properties.


3.3. More structural constraints need to be More structural constraints need to be developed. Some molecular structures pass developed. Some molecular structures pass the filters in the iterative method, but do not the filters in the iterative method, but do not exist in reality.exist in reality.

4.4. Considering refrigerant blends would create Considering refrigerant blends would create many more options for refrigerant solutions.many more options for refrigerant solutions.

5.5. Laboratory study Laboratory study -- The laboratory setting The laboratory setting offers the benefit of being able to measure offers the benefit of being able to measure properties for synthesized refrigerants. In properties for synthesized refrigerants. In this way, more accurate correlations for this way, more accurate correlations for group contributions or efficiency could be group contributions or efficiency could be developed.developed.

QUESTIONS?QUESTIONS?QUESTIONS?QUESTIONS?QUESTIONS?QUESTIONS?QUESTIONS?QUESTIONS?

WORKS CITEDWORKS CITEDWORKS CITEDWORKS CITEDWORKS CITEDWORKS CITEDWORKS CITEDWORKS CITED

1.1. History of the Refrigerator. History of the Refrigerator. History.com. 2/7/2007 History.com. 2/7/2007 <<http://www.history.com/exhibits/modern/fridge.htmlhttp://www.history.com/exhibits/modern/fridge.html>.>.

2.2. Refrigerant Data UpdateRefrigerant Data Update. January 2007. Heating/Piping/Air . January 2007. Heating/Piping/Air Conditioning Engineering. Feb. 7, 2007 Conditioning Engineering. Feb. 7, 2007 <<http://www.hpac.com/Issue/Article/44475/Refrigerant_Data_Updatehttp://www.hpac.com/Issue/Article/44475/Refrigerant_Data_Update>.>.

3.3. What you Should Know about Refrigerants when Purchasing or What you Should Know about Refrigerants when Purchasing or Repairing a Residential A/C System or Heat Pump. Repairing a Residential A/C System or Heat Pump. Jan. 29, 2007. Jan. 29, 2007. Environmental Protection Agency. Jan. 29Environmental Protection Agency. Jan. 29thth, 2007 , 2007 <<http://www.epa.gov/ozone/title6/phaseout/22phaseout.htmlhttp://www.epa.gov/ozone/title6/phaseout/22phaseout.html>.>.

4.4. HCFC Phaseout Schedule. HCFC Phaseout Schedule. April 16April 16thth, 2006. Environmental Protection , 2006. Environmental Protection Agency. Feb. 5Agency. Feb. 5thth, 2007 , 2007 <<http://www.epa.gov/ozone/title6/phaseout/hcfc.htmlhttp://www.epa.gov/ozone/title6/phaseout/hcfc.html>.>.

5.5. Air Conditioners 2004. Air Conditioners 2004. July 2004.July 2004. Snapshot International. Feb. 11Snapshot International. Feb. 11thth, , 2007 <2007 <http://dx.doi.org/10.1337/us080034http://dx.doi.org/10.1337/us080034>.>.

6.6. American Housing Survey for the United States: 2005.American Housing Survey for the United States: 2005. August 2006. August 2006. U.S. Department of Housing and Urban Development and the US U.S. Department of Housing and Urban Development and the US Department of Commerce. Feb 11Department of Commerce. Feb 11thth, 2007 , 2007 <<http://www.census.gov/prod/2006pubs/h150http://www.census.gov/prod/2006pubs/h150--05.pdf05.pdf>.>.

7.7. Trends in Residential AirTrends in Residential Air--Conditioning Usage from 1978 to 1997.Conditioning Usage from 1978 to 1997. July July 24, 2000. US Department of Energy. Feb 1124, 2000. US Department of Energy. Feb 11thth, 2007 , 2007 <<http://www.eia.doe.gov/emeu/consumptionbriefs/recs/actrends/recshttp://www.eia.doe.gov/emeu/consumptionbriefs/recs/actrends/recs_ac_t_ac_trends.htmlrends.html>.>.

8.8. The Properties of Gases and Liquids 5The Properties of Gases and Liquids 5thth Edition. Edition. OO’’Connell, J., B. Poling Connell, J., B. Poling and J. Pransnite.McGrawand J. Pransnite.McGraw--Hill, New York, 2001. Chapter 2 (78Hill, New York, 2001. Chapter 2 (78--89).89).

APPENDIXAPPENDIXAPPENDIXAPPENDIXAPPENDIXAPPENDIXAPPENDIXAPPENDIX

CREATING MORE ACCURATE CREATING MORE ACCURATE CREATING MORE ACCURATE CREATING MORE ACCURATE CREATING MORE ACCURATE CREATING MORE ACCURATE CREATING MORE ACCURATE CREATING MORE ACCURATE



•• To accurately predict the refrigerant To accurately predict the refrigerant market, a large scale survey needs to be market, a large scale survey needs to be performedperformed

•• The large scale survey will eliminate The large scale survey will eliminate inaccuracies present in the survey inaccuracies present in the survey prepared and presented previouslyprepared and presented previously

•• These inaccuracies stem from the These inaccuracies stem from the inherent bias in a small surveyinherent bias in a small survey

MORE THERMODYNAMIC MORE THERMODYNAMIC MORE THERMODYNAMIC MORE THERMODYNAMIC MORE THERMODYNAMIC MORE THERMODYNAMIC MORE THERMODYNAMIC MORE THERMODYNAMIC

EQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONSEQUATIONS

( ) 6*169347.0ln*28862.109648.6

013.1ln97214.5 brbr

br

c TTT

P−++

−−=α

( ) 6*43577.0ln*4721.136875.15

2518.15 brbrbr

TTT

+−−=β

βαω =

( )br

cbr

T

PTh

−=

1

013.1ln*

hG *4605.04835.0 +=

( )( )( )213

1

brbr

br

TT

TGhk

−++−

=

THERMODYNAMICSTHERMODYNAMICSTHERMODYNAMICSTHERMODYNAMICSTHERMODYNAMICSTHERMODYNAMICSTHERMODYNAMICSTHERMODYNAMICS

•• Functional group theory can be used to Functional group theory can be used to determine many important determine many important characteristicscharacteristics

•• TemperatureTemperature--Entropy data are needed Entropy data are needed to accurately determine efficiency, but to accurately determine efficiency, but cannot be determined from functional cannot be determined from functional group theorygroup theory

•• ∆∆H/CH/Cpp is used to estimate efficiencyis used to estimate efficiency

GAMS CODEGAMS CODEGAMS CODEGAMS CODEGAMS CODEGAMS CODEGAMS CODEGAMS CODE

SYSTEMATIC DESIGNSYSTEMATIC DESIGNSYSTEMATIC DESIGNSYSTEMATIC DESIGNSYSTEMATIC DESIGNSYSTEMATIC DESIGNSYSTEMATIC DESIGNSYSTEMATIC DESIGN

ENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTSENVIRONMENTAL EFFECTS

•• Ozone depletion potentialOzone depletion potential

–– Only heavy halogens are known to Only heavy halogens are known to contributecontribute

•• Global warming potentialGlobal warming potential

–– Requires experiments to find radiative Requires experiments to find radiative efficiency and time dependent decayefficiency and time dependent decay

) / exp(-3.858*)(n 0.05013 ODP 1.510Cl τ=

OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE OBTAINING VALUES FOR THE

OBJECTIVE FUNCTIONOBJECTIVE FUNCTIONOBJECTIVE FUNCTIONOBJECTIVE FUNCTIONOBJECTIVE FUNCTIONOBJECTIVE FUNCTIONOBJECTIVE FUNCTIONOBJECTIVE FUNCTION

•• Flammability and Flammability and explosivenessexplosiveness

–– Based on lower Based on lower explosive limitexplosive limit

–– Based on vapor pressureBased on vapor pressure

–– No strong correlationNo strong correlation

•• Toxicity Toxicity

–– Based on experimental Based on experimental resultsresults

–– Found only for existing Found only for existing moleculesmolecules

Vapor Pressure vs. LELy = 176.5x - 29.778

R2 = 0.0351

-5000

0

5000

10000

15000

20000

25000

30000

35000

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1

LEL (%)

Vap

or

Pre

ssure

(mm

Hg

)

Flash Point vs. LEL

Lineary = -66.281x + 68.752

R2 = 0.4087

3rd Order Polynomial

y = 50.242x3 - 231x2 + 275.14x - 92.641

R2 = 0.4151

6th Order Polynomial

y = -1196.1x6 + 9953.1x5 - 34677x4 + 65066x3 - 69409x2 + 39657x - 9368.3

R2 = 0.5702

-120

-100

-80

-60

-40

-20

0

20

40

0 0.5 1 1.5 2 2.5

LEL (%)

Fla

sh P

oin

t (oC

)

CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH

MOLECULAR WEIGHTMOLECULAR WEIGHTMOLECULAR WEIGHTMOLECULAR WEIGHTMOLECULAR WEIGHTMOLECULAR WEIGHTMOLECULAR WEIGHTMOLECULAR WEIGHT

y = -0.0095x + 1.749

R2 = 0.9276

0.3

0.5

0.7

0.9

1.1

1.3

50 75 100 125 150molecular wieght

dH

/Cp

average comparison

∆∆∆∆∆∆∆∆H/CH/CH/CH/CH/CH/CH/CH/CPPPPPPPP CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH CORRELATION WITH

COPCOPCOPCOPCOPCOPCOPCOP

Correlation of dH/Cp with COP

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 1 2 3 4 5

COP (PRO/II)

dH

/Cp dH/Cp

Poly. (dH/Cp)

EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR

NEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTS

•• The following journal publications The following journal publications describe in detail how the COP for new describe in detail how the COP for new refrigerants can be evaluatedrefrigerants can be evaluated

1.1. Fleming, John S., Alex C. Bwalya and William Dempster. Fleming, John S., Alex C. Bwalya and William Dempster. ““The testing and evaluation of trial refrigerants: Part 1. The testing and evaluation of trial refrigerants: Part 1. System description.System description.”” International Journal of Energy International Journal of Energy Research Research 24.14 (2000): 121724.14 (2000): 1217--1241.1241.

2.2. Fleming, John S., Alex C. Bwalya and William Dempster. Fleming, John S., Alex C. Bwalya and William Dempster. ““The testing and evaluation of trial refrigerants: Part 2. The testing and evaluation of trial refrigerants: Part 2. The practical use of measured data.The practical use of measured data.”” International International Journal of Energy Research Journal of Energy Research 24.14 (2000): 124324.14 (2000): 1243--1256.1256.

EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR EVALUATING THE COP FOR

NEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTSNEW REFRIGERANTS

•• Following a similar procedure, outlined in Following a similar procedure, outlined in these two articles, would provide the COP for these two articles, would provide the COP for the tested refrigerantsthe tested refrigerants

•• Then a correlation could be developed to relate Then a correlation could be developed to relate the COP to functional group contributionsthe COP to functional group contributions

•• This correlation would allow for a more This correlation would allow for a more rigorous analysis of all the possible rigorous analysis of all the possible refrigerantsrefrigerants

•• The refrigerants could then be ranked and The refrigerants could then be ranked and analyzed using more accurate consumer analyzed using more accurate consumer preference functionspreference functions

INCORPORATING PRODUCT DESIGN INTO THE …...PRESENTATION OUTLINE 1. Background 2. The Use of...

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