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Laser Flash Method to Determine Thermal Coductivity
A today's philosophy to use Flash Experiments top determine Thermal Conductivity
Motivation & Requirements Theoretical RemarksMeasuring Techniques
Dr.-Ing. Wolfgang Hohenauer
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Content
• Motivation and Requirements• Basics
– Uncertainty in Measurement Results– Theoretical Remarks
• Laser Flash Technique– Prinziples of the Method– Uncertainty– Limitations of Flash Methods– Experimental results
• Dynamic Scanning Calorimetry• Push Rod Dilatometry• Combined Methods to Determine Thermal Conductivity
• Summary
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Motivation and Requirements
• It is an integral part of the description of a material.
• To understand the behaviour of a material.• To influence processing steps systematically.• To optimise processes.• Quality management.• Materials selection in technical Design.• Input data for mathematical simulations:
Temperature distribution, deformation of specimen, stress analysis, life time estimation, kinetics of processes, etc.
• Failure analysis.• Lots of other purposes …
Measuring Techniques have to be…
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Measurement Results & Uncertainty
GUM*) - ENV 13005 (1999) Guide to the expression of uncertainty in measurement:
The result of any measurement is an approximation of the real value and represents an estimate value only…… The best available estimate of the expected quantity is the mean value (of a number of measurement results).… The best estimate of the uncertainty is the positive square root of the experimental variance of the observations – termed: experimental standard deviation
*) ENV 13005; Guide to the expression of uncertainty in measurement (GUM)
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Measurement Results & UncertaintyENV 13005; Guide to the expression of uncertainty in measurement (GUM)
… The best representation of an estimated value is the mean value (of a number of individual measurement results).
… The uncertainty of an individual measurement result:
… The uncertainty of the estimated value(=mean value):
… The standard uncertainty of a function of input values: “Gaussian error propagation”
… To obtain the expanded uncertainty onemultiplies by an coverage factor U(y) = k . uc(y)
∑=
=n
kkq
nq
1.1
∑=
−−
=n
kkk qq
nqs
1)²(.
11)(
∑=
⎟⎟⎠
⎞⎜⎜⎝
⎛∂∂
=N
ii
ic xu
xfyu
1
22
2 )(.)(
)(:)(.1)( ik xuqsn
qu ==
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Direct Methods to Measure Thermal Conductivity
• Principle:They realise thermal conductivity situations which allow simple mathematical description.
• Methods:– Comparative method– Guarded Heat Flow method– Hot wire method– Hot strip method
• Problem:– These methods often suffer from
significantly high uncertainties
S
SeffA
S
effA
S TlTP
TTPT
ΔΔ
⋅=∇
= )(||
|)(|)( ./
./
r
λ
⎥⎥⎦
⎤
⎢⎢⎣
⎡
ΔΔ
+ΔΔ
⋅ΔΔ
⋅⋅=lR
lR
uR
uR
S
SRS l
TlT
TlTT
;
;
;
;)(21)( λλ
upper heater
lower heater
lowerreference
upperreference
specimen
TC 1
TC 3
TC 5
TC 2
TC 4
TC 6
ΔT
≅80
°C
upper heater
lower heater
lowerreference
upperreference
specimen
TC 1
TC 3
TC 5
TC 2
TC 4
TC 6
ΔT
≅80
°C
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Direct Methods to Measure Thermal Conductivity (3)
Real Conditions in Temperature Measurementcause minimum uncertainties of > 20% of λ
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Thermal Conductivity Equation
0.),(.),(),(),(),( =∇−∂
∂⋅⋅⋅ ∫∫∫
FVp fdtxTTx
ttxTTxcTxdV
rrrr
rr λρ
),()(),()()(
)(),( txTTatxTTcT
Tt
txT
p
rrr
Δ⋅=Δ⋅⎥⎥⎦
⎤
⎢⎢⎣
⎡
⋅=
∂∂
ρλ
{ 0
/ ),()(∑ ∑
=⋅+ −++∫∫
i jji SS
txPfddt
tdQA
F
rrr
Conservative systemLinear descriptionMaterial:
HomogeneousIsotropic
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Principles of a Flash Experiment
Specific experimental setup
1. One-dimensional experiment2. Homogeneous material3. Samples prepared in principle
axis of the material4. Adiabatic boundaries5. Infinite duration of heat impact
This leads to
( ))()(41ln)(
21
2
2 TtThTa ⋅−≅
π
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Physics / Mathematics of a Flash Experiment
),()(),()()(
)(),( txTTatxTTcT
Tt
txT
p
rrr
Δ⋅=Δ⋅⎥⎥⎦
⎤
⎢⎢⎣
⎡
⋅=
∂∂
ρλ
( ))()(41ln)(
21
2
2 TtThTa ⋅−≅
π
2
2 ),().(),(x
txTTat
txT∂
∂=
∂∂
⎥⎦
⎤⎢⎣
⎡⋅⋅+⋅⋅⋅= ⋅− x
acBx
acAetxT tc cossin),(
2
22
0cos),( h
tan
nn e
hxnBtxT
⋅⋅⋅−∞
=
⋅⎟⎠⎞
⎜⎝⎛ ⋅⋅
⋅= ∑ππ
( ) ⎥⎦
⎤⎢⎣
⎡⋅−⋅+⋅Δ==Δ ∑
∞
=∞
⋅⋅⋅⋅−
1
2
22
121),(n
n h
tan
eTthxTπ
D1 Problem
General solution
Adiabatic boundaries
Infinitesimal impact duration
Axial thermal flux
No heat flux at surfaces; coplanar specimen
Heat pulse
O(1)
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Experimental Data of a Flash Experiment
( ))()(41ln)(
21
2
2 TtThTa ⋅−≅
πΔ
T max
= Δ
T ∞
ΔT(
t 1/2)
t1/2
theoretical adiabatic curve
experimental curve
heat pulse
Modelled curve:based on theoretical models as- Parker, Clark, Taylor, Cowan- Cape & Lehmann- Radiation model- Finite heat pulse length
h
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The Laser Flash Method - Optimisations
• There are non-conservative systems• Local inhmogenities occur• Sometimes no easy interpretation of
transient temperature curve possible
• Adiabatic boundaries do not exist• Infinitesimal initial heat impacts
cannot be realised• First order solution does not describe
reality – BUT it helps to understandthe fundamentals!
• Up to date LF software calculates amodel of the experimental data
• and includes non adiabatic effectsand finite pulse durations as well
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The Laser Flash Method - Requirements
• There are non-conservative systems• Local inhmogenities occur• Sometimes no easy interpretation of
transient temperature curve possible
• Adiabatic boundaries do not exist• Infinitesimal initial heat impacts
cannot be realised• First order solution does not describe
reality – BUT it helps to understandthe fundamentals!
• Up to date LF software calculates amodel of the experimental data
• Models include non adiabatic effectsand finite pulse durations as well
Take it or leave it
• This causes limitations of the method- e.g. high conductivity thin layers
• Specific problems often do not allowautomatically controlled procedures
• Competent interpretation of thetemperature response is needed
• Experimentalist have to understand physics and the materials they measure
• Numeric models must be compatible with the measured material (glass !)
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To Interpret a Flash Measurement
Solid sample measurement
Liquid sample measurement
Curie transition
Phase transition
Melting area
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Diffusivity & Uncertainty – Thermal Insulators
∑=
⎟⎟⎠
⎞⎜⎜⎝
⎛∂∂
=N
ii
ic xu
xfyu
1
22
2 )(.)(
Data acquisitionTime step: 2 µs
a > 5 x 10-9 m²/s
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Diffusivity & Uncertainty – High Diffusivity
∑=
⎟⎟⎠
⎞⎜⎜⎝
⎛∂∂
=N
ii
ic xu
xfyu
1
22
2 )(.)(
Data acquisitionTime step: 12 µs
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Minimum Possible Sample Thickness
• Modern LFA performance:
– Assume perfect mathematical modelling of T(t)
– Infrared detector: Possible data acquisition rate ~1 MHz
– LFA :Possible data acquisition rate is ~500 kHz
– Time distance between the points is ~2 μs
– Approximately 250 points are required between the release of the laser flash and the half time t1/2.
– The minimum theoretical half time of the sample is ~0,5 ms.
– Minimum possible sample thickness h can be calculated ….
atah ⋅≅⋅⋅≅ 06,04ln
(min)21
2
minπ
( ))()(41ln)(
21
2
2 TtThTa ⋅−≅
π
ΔT ma
x=
ΔT ∞
ΔT(
t 1/2)
t1/2
theoretical adiabatic curve
experimental curve
heat pulse
Modelled curve:based on theoretical models as- Parker, Clark, Taylor, Cowan- Cape & Lehmann- Radiation model- Finite heat pulse length
h
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Minimum Possible Sample Thickness
Material a(Tr) x 106 / m²/s hmin / mm
Diamond 1000 1,90Silver 174 0,79Copper 117 0,65POCO AXM 5Q 72 0,51Pure Iron 22 0,28Aluminia 10,5 0,19Stainless Steel; AISI 316 3,25 0,11Pyroceram 1,92 0,08Glass 0,7 0,05Filled Polymeres 0,5 0,04Polycarbonate 0,15 0,02Paper, PP, ÜTFE 0,1 0,02
65,0
67,5
70,0
72,5
75,0
0 200 400 600 800 1000 1200m / µm
Appa
rent
The
rmal
Diffu
sivity
: a /
mm
²/s
POCO AXM 5Q
Polynom. Approx. O(3)
T = 25°C<a> = 72,3 mm²/shmin = 0,52 mm
3,00
3,20
3,40
3,60
3,80
0 25 50 75 100 125 150 175 200 225T /°C
Appa
rent
Ther
mal D
iffus
ivity
: a / m
m²/s
Stainless Steel: AISI 316
Polynom. Approx. O(3)
h = 0,109 mm; hmin = 0,11 mma25°C; Touloukian = 3,25 mm²/s
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Minimum Possible Sample Thickness
( )
( )sWaermeatlaVDIsmma
smma
smmammdFilmPP
Lit
−=
±=
±=
=−
2.
22
21
142.0
005.0140.0
005.0142.0057.0
( )smma
mmdFilmLDPEStreched
21 002.0153.0
058.0±=
=−
( )
( )sWaermeatlaVDIsmmasmma
mmdFilmPVC
Lit −=
±=
=−
2.
2
125.0005.0126.0
072.0
Quelle: J. Blumm; NETZSCH Gerätebau GmbH
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Magnesium Foam Material
0
5
10
15
20
-200 -100 0 100 200 300 400 500T / °C
λ / W
/m.K
0
10
20
30
l - LFA l - LFA-corr. l - Comp. a
a x 1
06 /m²/s
22,00
22,25
22,50
22,75
23,00
23,25
0,0 0,5 1,0 1,5 2,0Time /s
Appa
rent
Tem
pera
ture
/K
T_Sensor T_Steg T_Fuellung
SensorMetal StructureCeramic Filler
φ = 20 mmh = 10 mmρ ≅ 0,49 g/cm³
Experimental:
Simulation: Cubic: 10 x 10 x 10 x mm³ρ ≅ 0,6 g/cm³
λ LFA λ LFA; corr. λ Comp.
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Diffusivity Results of a Steel Material
0,0
2,5
5,0
7,5
10,0
12,5
15,0
0 200 400 600 800 1000 1200 1400 1600T / °C
a x
106 /
m²/s
ecS 500 SF sample 1
S 500 SF sample 2
S 500 SF mean value
Melting AreaMelting area
Curie transition
Phase transition
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Dynamic Scanning Calorimetry: DSC (1)
Measurement principle:• To heat up any material needs time – this
depends from:– mass– Temperature difference between the
sample and its environment (furnace with respect to the heating rate)
– Specific heat of the sample• One heats a furnace with a defined heating
rate. The difference between the temperature dependent temperature of an empty crucible and a crucible filled with some specific material characterises the thermal consumption of this material.
• To quantify this temperature difference with the behaviour with a reference material results the specific heat and transformation enthalpies of the unknown material.
High-temperatureFurnace
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Dynamic Scanning Calorimetry: DSC (2)
Measurement procedure:1. Basis-line:
Characterises the behaviour of the empty DSC (zero-line)
2. Reference-line: Quantifies the response of the DSC when a reference material is measured:
1. Empty Reference crucible 2. Sapphire in sample crucible
3. Sample-line: measurement of a specimen:
1. Empty Reference crucible2. Sample in sample crucible
Calculation of the specific heat
High-temperatureFurnace
RP
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Dynamic Scanning Calorimetry: DSC (3)
Calculation of the specific heat:• Heat input of δQ causes an increase of temperature
in any substance:
• These equations can be transformed to express dT. With dT(Sa) = dT(Pr) one obtains:
• From this it follows the evaluating equation of a dynamic calorimeter:
)()()(
)()()(
)()(
)()(
)()(
)()(
TcmTDSCTDSC
TcmTDSCTDSC
Sp
S
BS
Rp
R
BR
⋅−
=⋅
−
)()()()( )()()()()()( TDSCTDSCdTTcmTQ BRRRP
RR −=⋅⋅=δ
)()()()( )()()()()()( TDSCTDSCdTTcmTQ BSSSP
SS −=⋅⋅=δ
( ) ( )Tcmm
TDSCTDSCTDSCTDSCTc R
pS
R
BR
BSS
p)(
)(
)(
)()(
)()()(
)()()()(
⋅⋅−−
=
RP
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Dynamic Scanning Calorimetry: DSC (4)
0
1
2
3
4
5
0 200 400 600 800 1000 1200 1400 1600T [ °C ]
c p [
J/g.
K ]
Alloy: Probe (1)Alloy: Probe (2)Alloy: Probe (3)Alloy: Mittelwert
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Push Rod Dilatometry (1)
Position encoder Flushing Gas Sample Holder Furnace Sample Ventilator
Thermostat Touch Bed Furnace Tube (gas-proof)
DIL 402 C
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Push Rod Dilatometry (2)
Measurement principle:• The position encoder detects the temperature
dependent position P(T). This is the superposition of the unknown expansion of the specimen ΔL(T) and the intrinsic expansion of the internals of the dilatometer.
• The intrinsic expansion behaviour of dilatometer can be quantified by a correction function K(T).
• This correction function depends on:– Heating rate of the furnace,– Initial length of the sample L0– Material of the internals– Gas conditions in the dilatometer
• To determine the correction function K(T),one correlates the position curves P(T) of a reference-material with it’s recommended expansion data.
DIL 402 C
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Push Rod Dilatometry (3)
Measurement procedure:
• Examination of the intrinsic expansion behaviour of the dilatometer:– Reference-materials
• Calculation of the correction function K(T): • Measurements of samples:
– specimen
• calculations:– Thermal expansion of the material– CTE
⎟⎟
⎠
⎞
⎜⎜
⎝
⎛−
Δ=
R
R
LitRR L
PL
LK;0;0
⎟⎟
⎠
⎞
⎜⎜
⎝
⎛−
Δ+=+=
Δ
R
R
LitRSR
S
S
S
S
LP
LL
LPSK
LP
LL
;0;0;0;0;0
S
SSS L
TLT
TCTET;0
)(1:)()( ΔΔ
=≡α
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Push Rod Dilatometry (4)
0
5
10
15
20
0 200 400 600 800 1000 1200 1400 1600T [ °C ]
L/L 0
x 1
03
Alloy: Probe (1)
Alloy: Probe (2)
Alloy: Mittelwert
0
5
10
15
0 200 400 600 800 1000 1200 1400 1600T [ °C ]
CTE
[ K
-1 ]
x 10
6
Alloy: Probe (1)
Alloy: Probe (2)
Alloy: Mittelwert
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Combined Methods to Determine the Thermal Conductivity
• Thermal conductivity equation correlates the relevant thermophysical material properties.
– Thermal density ρ(x,T)and thermal expansion
– Specific heat cp(x,T)and Enthalpy H; Entropy S
– Thermal conductivity λ(x,T)– Thermal diffusivity a(x,T)
• Thermal conductivity λ(x,T) can be calculated out of the properties ρ(x,T), cp(x,T), and a(x,T).
Combined thermophysical measuring methods
),()(),()()(
)(),( txTTatxTTcT
Tt
txT
p
rrr
Δ⋅=Δ⋅⋅
=∂
∂ρ
λ
xxpxx TTcTaT rrrr |)(|)(|)(|)( ρλ ⋅⋅=
H Scp
aCTEλ
DSC DSCDSC (Kalorimetrie)
Laser Flash VerfahrenDilatometrie
λ(T) = a(T) . cp(T) . ρ(T)DSC DSCDSC DSC
DSC (Kalorimetrie)
Laser Flash VerfahrenDilatometrie Laser Flash VerfahrenDilatometrie
λ(T) = a(T) . cp(T) . ρ(T)
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Diffusivity Results of a Steel Material
0,0
2,5
5,0
7,5
10,0
12,5
15,0
0 200 400 600 800 1000 1200 1400 1600T / °C
a x
106 /
m²/s
ecS 500 SF sample 1
S 500 SF sample 2
S 500 SF mean value
Melting AreaMelting area
Curie transition
Phase transition
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Thermal Conductivity of a Steel Material
0,00
1,00
2,00
3,00
4,00
5,00
0 200 400 600 800 1000 1200 1400 1600T / °C
c p /
J/g
.K
S 500 SF DSC (deconvoluted)
S 500 SF DSC (not deconvoluted)
S 500 SF Specific Heat
0
25
50
75
100
0 200 400 600 800 1000 1200 1400 1600T / °C
π / W
/m.K
S 500 SF
S 500 SF
Polynom. Approx. O(3)
Melting Area
Curieu Transition
Phase Transition Phase Transition
0
5
10
15
20
25
0 200 400 600 800 1000 1200 1400 1600T / °C
⎠L/
L 0 x
103
S 500 SF sample (1)S 500 SF sample (2)S 500 SF CTE . 10e6S 500 SF mean value
Melting Area
uc(λ) ≅ 5%
)()()()( TcTTaT p⋅⋅= ρλ
CTE
x 106
/ 1/K
Uncertainty Budget ESU*)
u(a)*) /% 1,00%u(cp)*) /% 1,50%u(ρ0) /% 1,00%u(CTE)*) /% 3,00%u(ΔT) /K 5*) Equipment Specific Uncertainty
uc( ) /% 3,22%
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Summary (1)
• The thermal conductivity equation defines the structure of the transient spatial temperature field in a body.
• The thermal conductivity equation correlates the fundamental thermophysical properties.– Thermal density ρ(x,T); thermal expansion ΔL(x,T)/L0 or CTE(x,T)– Specific heat cp(x,T)– Thermal conductivity λ(x,T)– Thermal diffusivity a(x,T)
• The thermal conductivity equation - more or the less - points out how to measure thermophysical material properties.
),()(),()()(
)(),( txTTatxTTcT
Tt
txT
p
rrr
Δ⋅=Δ⋅⋅
=∂
∂ρ
λ
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Summary (2)
• There exists a simple solution of the thermal conductivity equation for a special system:– Conservative …….– Homogeneous …..– Isotropic ……….....
• This solution can be specified to describe flash experiments by a simple formalism:– Adiabatic boundaries ………….…..– Infinitesimal initial heat impact …..
– First order series expansion ….…..( )
)()(41ln)(
21
2
2 TtThTa ⋅−=
π
Sample requirements
Sample and equipment requirements
Numericalrequirements
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36
Summary (3)
• The most relevant thermophysical material properties are:– Thermal density and thermal expansion– Specific heat– Thermal diffusivity and thermal conductivity
• The most common measurement methods to determine these thermophysical properties are:
– Push rod dilatometry– Dynamic scanning calorimetry - DSC– (Laser) Flash methods - LFA– Calculation of the thermal conductivity out of these measurement results
• All these measurement methods enable uncertainties in measurement results near 1% of the analysed value (k=2; Conf.Int. 95% in accordance with DIN-V ENV13005). Thermal conductivities can be calculated with an level of uncertainty near 5%.
• Direct methods to measure the thermal conductivity are comparable expansive, time consuming and inaccurate.