factors contributing to k-factor optimization with ecomate ® blown foams cpi orlando 2007

Factors contributing to k-factor optimization with ecomate® blown foams

CPI Orlando 2007

2

How does ecomate compare?

ecomate 141b 245fa 365mf

c

365/227

93 / 7

n-C5 cC5

Mol wt 60 117 134 148 149,6 72 70

Bpt, C 31,5 32 15,3 40,2 30 36 49

Sp Gr 0,982 1,24 1,32 1,25 1,28 0,62 0,75

Lambda 10,7 10 12,2 10,6 10,7 14* 11*

LEL/UEL 5,0 – 23,0

7,6 – 17,7 n/a 3,5 – 9,0

3,8 – 13,3

1,4 – 17,8

1,4 – 8,0

3

How does ecomate comparein Foams ? Handmix Pours Comparison

Molar Substitution - in same formulation Same Index Same Surfactant amount Same Catalyst amount Same molar BA content

4

BA Molar Substitution2” thick sample, 75 ºF

0.18

0.185

0.19

0.195

0.2

0.205k-factor

141b 245fa ecomate

Handmix Data ONLY

Results are Relative

ECOMATE ~ same as 245fa

k NOT SOLELY dependant on MW

0.2040.2020.187

5

Thermal Conductivity Not dependant solely on:

Molecular Wt Gas λ K-Factor at standard conditions

Depends on many additional factors, including: Temperature Processing Formulation Configuration Protection

6

Temperature / k-factor Dependence

k-factor change w Temperature

0.100

0.110

0.120

0.130

0.140

0.150

0.160

-40 -20 0 20 40 60 80

TEMP, F

K F

AC

TO

R

7

Examine Processing Effects

Hand Mix Factorial Design Examine

Mix Time Mix Speed Pour Size Surfactant Concentration

8

PROCESSING EFFECTS:HAND MIX FACTORIAL

DESIGNMIX TIME,

sec

Low 5

Mid 7.5

High 10

9


DESIGNMIX TIME,

secMIX SPEED,

rpm

Low 5 1000

Mid 7.5 2000

High 10 3000

10


DESIGNMIX TIME,

secMIX SPEED,

rpm

POUR SIZE,

gm

Low 5 1000 150

Mid 7.5 2000 225

High 10 3000 300

11


DESIGNMIX TIME,

secMIX SPEED,

rpm

POUR SIZE,

gm

SURF CONC,

pct

Low 5 1000 150 1

Mid 7.5 2000 225 1.5

High 10 3000 300 2

12

PROCESSING EFFECTS:Handmix Results Summary

Mix Time Mix Speed Pour Size Surf. Concentration

Not significant Faster = lower λ (less BA loss) Larger = lower λ (less surface

area) More = lower λ (less BA loss)

1.00 1.25 1.50 1.75 2.00

28

29

30

C: SURF CONC

lambd

a

One Factor Plot

1000 2000 3000

28

29

30

A: MIX SPEED

lambd

a

One Factor Plot

150 200 250 300

28

29

30

B: SIZE POUR

lambd

a

One Factor Plot

13

Handmix v MachineSame ecomate Formulations

0.14

0.15

0.16

0.17

0.18

0.19

0.2

J91-5 J91-6 J91-8

HAND

MACHINE

Machine ALWAYS Superior !

14

Examine Formulation Effects Polyol

Type and Amount Catalyst Surfactant

Type and Amount Blowing agent

Temp Effect Loss / Diffusion Blends

15

Examine Polyol Effects In a Hand Mix Factorial Design

Vary POLYOL BLEND Hold Constant

Catalyst Surfactant Blowing Agent INDEX = 120

16

POLYOL BLEND Design

DESIGN Func. Eq. Wt. Visc. LO – HI LEVELS

Sucrose Glycerin

7 152 30K 25-75

EDA 4 70 17K 0-25

Ester 2.3 212 12K 0-50

17

Polyol Effect: DENSITYDESIGN-EXPERT Plot

DENSITYDesign Points

X1 = A: SUC-GLYX2 = B: ESTERX3 = C: EDA

A: SUC-GLY100.00

B: ESTER75.00

C: EDA75.00

0.00 0.00

25.00

DENSITY

1.6

1.65

1.7

1.75

1.8

1.85

• EDA faster,

- Captures more BA

- Thus Lower Density

25 – 75%0 – 50%0 – 25%

18

Polyol Effect: THERMAL Props

DESIGN-EXPERT Plot

THERMALDesign Points

X1 = A: SUC-GLYX2 = B: ESTERX3 = C: EDA

A: SUC-GLY100.00

B: ESTER75.00

C: EDA75.00

0.00 0.00

25.00

THERMAL

27

28 29

30

31EDA worse !

Strong affinity for BA

Less in vapor space

19

Polyol Results Choice of Polyol Critical -

Not only affects Physicals Faster reactivity captures more BA Polyol Type can also affect k-factor, λ

20

Examine Catalyst Effects Speed of reaction Cell Orientation

Blow v Gel Cats Gel / Rise Ratio

21

Gel Time EffectsFaster = Lower k

0.130

0.132

0.134

0.136

0.138

0.140

0.142

0.144

20 30 40 50 60

Gel Time (s)

Th

erm

al C

on

du

ctiv

ity

18.718.919.119.319.519.719.920.120.320.520.7

LA

MB

DA

PU Expo2002, pg 459, fig 12

22

Cat Effects:

STRETCHED

SMALL, _|_ RISE BEST

23

Catalyst Effects Results Speed of reaction Cell Orientation Gel / Rise Ratio

Faster is betterSmaller, rounder

betterGel at Rise best

24

Surfactant Effects AFFECTS

Cell formation Polyol / ISO compatibility Strut / window thickness Cell Windows open / closed Fineness of Cells Density

TYPE – Critical ! Mol Wt Siloxane content Degree of modification See Degussa Paper [ref 4]

AMOUNT – very important Optimize for each formulation

25

Examine BA Effects Molecular WeightInfluential, not

critical

26

Examine BA Effects Molecular Weight Gas λ Value

Influential, not critical


27

Examine BA Effects Molecular Weight Gas λ Value Solubility = Viscosity



Very Important on Flow

28

Examine BA Effects Molecular Weight Gas λ Value Solubility = Viscosity Flow = Cell Orientation




Critical to Thermal Properties

29

Examine BA Effects Molecular Weight Gas λ Value Solubility = Viscosity Flow = Cell Orientation Vapor pressure





Very Important

30

Examine BA Effects Molecular Weight Gas λ Value Solubility = Viscosity Flow = Cell Orientation Vapor pressure Liquid v Gas





Very ImportantMeasure k at Use

Temp

31

Liquid v Gaseous BACondensation Effect

k-factor change w Temperature

0.100

0.110

0.120

0.130

0.140

0.150

0.160

-40 -20 0 20 40 60 80

TEMP, F

K F

AC

TO

R

32

Liquid v Gaseous BA GAS

Advantage of potential lower thermal properties

Lost because of higher Vapor Pressure More Gas escapes during foaming

33

Caveat Moisture

Very poor insulator Very small molecule [MW=18],

Smaller than N2 [MW=28, 78%],

Smaller than O2 [MW=32, 21%]

Ubiquitous Penetrates foams readily Plays havoc with K-factor

34

Diffusion Gases want to reach equilibrium

35

DiffusionIF POROUS

Graham’s LawRate1

Rate2

M2

M1

=

M2 M1

134 18

Gas245f

a H2O

Rate1 / Rate2 = 2.73

Rigid Foams NOT Porous !

Fick’s Law: Solubility Factors

Water 3X greater Diffusion !

36

Blowing Agent LossAHAM Study

Negligible!

Amount of CFC-11 Blowing Agent in Sampled Refrigerators

Sample When Produced, Pre-1993

At End of Life, Prior to Shredding, 2004

A-1 15.2 % 15.4 %

A-2 14.1 % 13.0 %

B-1 15.9 % 16.0 %

B-2 16.7 % 15.2 %

C-1 16.0 %* 16.0 %

C-2 13.0 – 14.0 % * 13.8 %

D-1 14.0 – 16.0 % * 15.7 %

D-2 14.0 – 16.0 % * 14.3 %

37

REAL LIFE EXAMPLES BEST EVALUATIONS

Run side-by-side Use Actual CABINETS Use Actual Conditions Measure

Energy used Ice melt over time Compressor cycles, or Temperature change w time

38

Ice Melt TestsDrink Dispenser Tests

Ice Melt @ 75 FIdentical results !

0

1000

2000

3000

4000

0 1000 2000 3000

minutes

ice

rem

ain

ing

(g

)

134a

ecomate

39

CONTROL 18% more energy

20% more energy

BTU LOAD TEST – Refrigerated Display case, Maintain 40F

ecomate, 245fa nearly same

40

40 F CHILLER

40 F CHILLER

%Time ON for 95 F: %Time ON for 95 F:

DUTY CYCLE – 39” VENDOR CABINETS

5-100 watt bulbs to keep 95F

36.8% 37.4%

ecomate, 245fa nearly same !

41

BLENDING BAs Ecomate very compatible

Why spend extra money?

Ecomate / 245fa Blends PAT APP 20060160911

Exp-1 Exp-2 Exp-3 Exp-4

Ecomate, mol% 90 75 50 25

HFC 245fa, mol% 10 25 50 75

K-factor, init 0.165 0.161 0.158 0.153

CS// , psi 31 25 33 24

Dim Stab Cold, [28d,-29C, V%] 2 3 5 9

42

Handmix v MachineSame ecomate Formulations

0.14

0.15

0.16

0.17

0.18

0.19

0.2

J91-5 J91-6 J91-8

HAND

MACHINE

Machine ALWAYS Superior !

Ecomate machine k values respectable

43

Thermal Conductivity

Not dependant solely on: MW Gas λ K-Factor at standard conditions

Depends on many additional factors, including: Formulation Processing Configuration Protection

44

Conclusions Thermal Improvements available

Thru formulation Thru processing

Protect foams from Moisture Ecomate nearly equals 245fa

in Hand mix data in Side-by-side Performance Tests

Compare for Yourself!

Compare for Yourself !

factors contributing to k-factor optimization with ecomate ® blown foams cpi orlando 2007

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