Single Phase Heat Transfer with Nanofluids
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Transcript of Single Phase Heat Transfer with Nanofluids
Single Phase Convective Heat Transfer with
Nanofluids: An Experimental Approach
Ehsan Bitaraf Haghighi
Division of Applied Thermodynamics and RefrigerationDepartment of Energy TechnologyRoyal Institute of Technology
Contents
• Introduction
• Project Foundation and Backdrop
• Aim of the Study and Methodology
• Experimental Approach
• Theoretical and Empirical Formulas
• Summary of Results and Discussion
• Conclusion and Future Work
2
What is a Nanofluid?
Dilute dispersions of nanoparticles (NPs) with usually loading less than 5 vol%
in conventional heat transfer fluids or base fluids (BFs) are nanofluids (NFs)
(like metals, metal oxides, carbides, carbon nanotubes etc.)
(like water, ethylene glycol/water, oils etc.)
5
Why Nanofluids are Interesting?
6
490429
401
317
368.4 0.606 0.250 0.145
0
100
200
300
400
500
k (
W/m
K)
Material
Nanofluids in the Literature
499527
396
182
13090
6735 23 14 3 1 0 1 0 1 2 0 0 0 2
0
100
200
300
400
500
600
Re
co
rds
Year
Source: Engineering Village
Articles with term
“nanofluid” in their titles
7
Chip Heat Flux Trends & Prediction
Source: National Electronics Manufacturing Initiative (NEMI), 2000
Accommodate
q = 120 W/cm2
at ΔT = 50 K
Requires
h = 24 000 W/m2K
8
Attainable Heat Transfer Coefficient
Source: Lasance, C., Technical Data column, Electronics Cooling, January 1997
9
Project Foundation and Backdrop
• NanoHex (Enhanced Nanofluid Heat Exchange)
• A consortium of twelve leading European companies and
research centres
• Granted €8.3 million by the Seventh Framework
Programme (FP7)
• September 2009 - April 2013
• Aim: improve heat management in existing industries,
particularly data centres and power electronics
• The main goal: to develop a formulation and a production
pilot–line for a promising nanofluid as a coolant
10
Aim of the Study
• Answer to this question “if NFs can replace common
BFs?”
• Have a critical approach to previous literature
• Suggest rather rapid experimental and analytical
screening methods for evaluating the cooling performance
of NFs
• Find a simple, inexpensive and standardized method to
estimate the shelf stability of NFs
12
Methodology
Investigate thermophysical and transport properties of NFs
Theoretical analysis
Investigate shelf stability of NFs
Thermal conductivity
Viscosity
Density
Specific Heat
Heat transfer
coefficient Measurement
Formula
Measurement
screening setup
closed loop
13
Experimental Approach
• Thermal Conductivity
• Viscosity
• Convective Heat Transfer
• Screening setup
• Convective closed–loop
• Shelf Stability
• Material Characterisation
15
Screening Setup Test Section (din=0.5 mm, L=30 cm)
ℎ𝑥 =𝑞"
𝑇𝑠−𝑖𝑛,𝑥 − 𝑇𝑓,𝑥
𝑇𝑓,𝑥 = 𝑇𝑖𝑛𝑙𝑒𝑡 +𝑞"𝜋𝑑𝑥
𝑚𝐶𝑝
Only laminar, very quick 18
Convective Closed–loop Test Section (din=3.7 mm, L=1.5 m)
P
HD Developing Region
thermostat bath
Gear Pump
Tubular Heat Exchanger (THE)
Plate Heat Exchanger
DC Power Supply
Differential Pressure Sensor
Insulation
Glass tube
Tube Wall’s TCs
Discharge
Tap Water
Charge
Flow Meter
Blue: Plastic pipe
Bypass
Static mixer
Inlet test section TC Outlet test section TC
Laminar and turbulent, time consuming 19
Material Characterisation
Nanofluid
Source NP Type
Concentration
BFSize
pH
Additives
ItN Nanovation, Germany
Al2O3
(wt%/vol%)
3 – 40 / 1 – 14
DW
9.1
(g surfactant/g solid)
1.5% – 1.8%
Two types
21
Particle Size
Analysis the morphology and dry size of particles
Analysis the hydrodynamic particle size
0
5
10
15
20
25
0 250 500
Inte
ns
ity (
%)
Diameter (nm)
Scanning Electron Microscopy (SEM)
Transmission Electron Microscopy (TEM)
Dynamic Light Scattering (DLS)
22
Al2O3
Al2O3
Additives (Surfactants)
23Source: http://omicsonline.org/2157-7048/2157-7048-2-e101.php
Hydrophobic
Hydrophilic
Base fluid
Theoretical and Empirical Formulas
• Thermophysical Properties
• Pressure Drop and Pumping Power
• Convective Heat Transfer
• Suggested Model
• Stokes’ Law
24
Thermal Conductivity
Maxwell (1873)𝑘𝑛𝑓
𝑘𝑏𝑓=
𝑘𝑝 + 2𝑘𝑏𝑓 + 2 𝑘𝑝 − 𝑘𝑏𝑓 ∅
𝑘𝑝 + 2𝑘𝑏𝑓 − 𝑘𝑝 − 𝑘𝑛𝑓 ∅= 𝑓(𝑘𝑝, 𝑘𝑏𝑓, ∅)
0.0
20.0
40.0
60.0
80.0
0 50 100
kn
f/kb
f
wt. (%)
1.00
1.02
1.04
1.06
1.08
0 50 100 150 200kn
f/kb
f
kp (W/mK)
Al2O3 in DW
25
Viscosity
𝜇𝑛𝑓
𝜇𝑏𝑓= 1 −
∅𝑎∅𝑚
−2.5∅𝑚
= 𝑓(∅, 𝑎, 𝑎𝑎)
∅𝑚 = 0.62, ∅𝑎 = ∅ 𝑎𝑎/𝑎3−𝐷,
𝐷 is typically 1.6 – 2.5 for NFs
𝜇𝑛𝑓
𝜇𝑏𝑓= 1 + 2.5∅ = 𝑓(∅)Einstein (1906)
Modified Krieger–Dougherty (2007)
0.0
2.0
4.0
6.0
8.0
10.0
0 50 100
µn
f/µ
bf
wt. (%)
Einstein
Modified Krieger-Dougherty
𝑎 ⇒ 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝑠𝑖𝑧𝑒𝑎𝑎 ⇒ 𝑎𝑔𝑔𝑟𝑒𝑔𝑎𝑡𝑒 𝑠𝑖𝑧𝑒
Al2O3 in DW26
Density & Specific Heat
Density
Specific Heat
𝜌𝑛𝑓 = ∅𝜌𝑝 + 1 − ∅ 𝜌𝑏𝑓 = 𝑓(𝜌𝑝, 𝜌𝑏𝑓, 𝜙)
𝐶𝑃,𝑛𝑓 =∅𝜌𝑝𝐶𝑃,𝑝 − (1 − ∅)𝜌𝑏𝑓𝐶𝑃,𝑏𝑓
𝜌𝑛𝑓= 𝑓(𝜌𝑝, 𝜌𝑏𝑓, 𝐶𝑃,𝑝, 𝐶𝑃,𝑏𝑓, 𝜙)
0.0
1.0
2.0
3.0
4.0
5.0
0 50 100
ρn
f/ρ
bf
wt. (%)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 50 100
Cp
nf/
Cp
bf
wt. (%)
Al2O3 in DW Al2O3 in DW27
Pressure Drop and Pumping Power
∆𝑝 = 𝑓𝜌𝑢2
2𝑑𝐿Darcy equation
𝑓𝐿𝑎𝑚𝑖𝑛𝑎𝑟 =64
𝑅𝑒
𝑓𝑇𝑢𝑟𝑏𝑢𝑙𝑒𝑛𝑡 = 1.82 𝑙𝑜𝑔10 𝑅𝑒 − 1.64 −2
𝑓𝑇𝑢𝑟𝑏𝑢𝑙𝑒𝑛𝑡 = 0.316𝑅𝑒−14 𝑅𝑒 ≤ 2 × 104
Blasius equation
0
0.1
0.2
0.3
0.4
0 5000 10000 15000
fric
tio
n f
acto
r (-
)Re (-)
64/Re
Filonenko
Blasius
𝑃 = ∆𝑝 ∀
Laminar
Turbulent
Filonenko equation
28
Convective Heat Transfer (Laminar)
𝑁𝑢𝑥 = 𝑓 𝑥∗ , 𝑥∗ =𝑥/𝑑
𝑅𝑒𝑃𝑟𝑁𝑢𝑎𝑣𝑔 = 𝑓(𝐿∗), 𝐿∗ =
𝐿/𝑑
𝑅𝑒𝑃𝑟
4
5
6
7
8
9
10
0 0.1 0.2N
u (
-)
L* (-)
4
5
6
7
8
9
10
0 0.1 0.2
Nu
(-)
x* (-)
Shah (1978) Shah (1975)
29
Convective Heat Transfer (Turbulent)
𝑁𝑢𝑥 = 𝑓 𝑅𝑒, 𝑃𝑟, 𝑃𝑟𝑤𝑓, 𝑑, 𝐿 𝑁𝑢𝑥 = 𝑓(𝑅𝑒, 𝑃𝑟)
Gnielinski (1975) Dittus-Boelter (1930)
0
20
40
60
80
100
2000 7000 12000
Nu
(-)
Re (-)
Dittus-BoelterGnielinski
DW, Tave=20 °C
30
Suggested Model
𝑇𝑠−𝑜𝑢𝑡 = 𝑇𝑓−𝑖𝑛 + 𝛥𝑇 + 𝜗
𝑄 = 𝑚𝑐𝑝𝛥𝑇 𝑄 = ℎ𝜗𝐴𝑝
𝑇𝑠−𝑜𝑢𝑡 = 𝑇𝑓−𝑖𝑛 +𝑄
𝑚𝑐𝑝+
𝑄
ℎ𝐴𝑝
𝜆 = (𝑇𝑠−𝑜𝑢𝑡 𝑏𝑓− (𝑇s−𝑜𝑢𝑡 𝑛𝑓
𝜆 = 𝑄1
𝑚𝑐𝑝 𝑏𝑓
1 −𝜌𝑏𝑓
𝜌𝑛𝑓×𝑐𝑝,𝑏𝑓
𝑐𝑝,𝑛𝑓×𝑢𝑏𝑓
𝑢𝑛𝑓+
1
𝜋𝑑𝐿ℎ𝑏𝑓1 −
ℎ𝑏𝑓
ℎ𝑛𝑓
Critical temperature
Tf-in Tf-out
Ts-in Ts-out
Tem
pera
ture
Distance from inlet
Wall
Fluid
ΔT
ν
Includes both thermophysical and transport properties
Positive
Negative
31
Summary of Results and Discussion
• Papers 1, 2 and 3: Thermophysical and transport
properties of three NFs
• Paper 4: Cooling performance of NFs in a small-diameter
tube
• Paper 5: Laminar heat transfer in a horizontal tube (closed
loop)
• Paper 6: Turbulent heat transfer in a horizontal tube
(closed loop)
• Paper 7: A method predicting the cooling efficiency of NFs
combining the effect of physical and transport properties
• Paper 8: Shelf stability of NFs and its effect on thermal
conductivity
33
NFs characterisation
NFs’ source NP
Solid
concentration (wt%/vol%)
BF pHSEM or TEM
particle size (nm)
Most common
DLS particle size (nm)
Additives type or
amount (g surfactant/g solid)
Dispersia Ltd, UK
Al2O3 9 / 2.4 DW 3.6 20 68 No info
ItN Nanovation, Germany
TiO2 9 / 2.3 DW 8.1 20 – 30 160Ammonium polyacrylate
ItN Nanovation, Germany
ZrO2 9 / 1.7 DW 8.1 30 – 40 237Ammonium polyacrylate
0 100 200
Inte
ns
ity (
a.u
)
Diameter (nm)
0 500 1000 1500
Inte
nsit
y (
a.u
)
Diameter (nm)
0 250 500 750
Inte
ns
ity (
a.u
)
Diameter (nm)
Al2O3 TiO2 ZrO2
35
Thermal Conductivity & Viscosity
0.550
0.570
0.590
0.610
0.630
0.650
0.670
0.690
10 20 30 40 50 60
k (W
/mK
)
T (ºC)
Al2O3ZrO2TiO2Maxwell Eq. For Al2O3Maxwell Eq. For ZrO2Maxwell Eq. For TiO2
1.00
1.02
1.04
1.06
1.08
10 20 30 40 50 60
kr (
-)
T (ºC)
Al2O3
ZrO2
TiO2
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0 10 20 30 40
µ (
cP)
T (˚C)
Al2O3
ZrO2
TiO2
1.00
1.40
1.80
2.20
2.60
0 10 20 30 40
µr
(-)
T (˚C)
Al2O3
ZrO2
TiO2
• Thermal conductivity: Maxwell can predict
• Relative viscosity is much higher than relative thermal conductivity36
Convective Heat Transfer & Pressure Drop
0
2
4
6
8
10
12
0 500 1000 1500 2000
Nu
(-)
Re (-)
Shah DW Shah TiO2Shah ZrO2 Shah Al2O3DW TiO2ZrO2 Al2O3
0.00
0.05
0.10
0.15
0.20
0.25
0 1000 2000
f (-
)
Re (-)
DWTiO2ZrO2Al2O364/Re64/Re (+/-) 10%
-20
-15
-10
-5
0
5
10
15
20
0 5000 10000
Dev
iati
on
(%
)
Re (-)
DWAl₂O₃TiO₂ZrO₂
Screening set-up Closed Loop
Convective heat transfer & pressure drop:
traditional equations can predict
37
Comparison: Screening Set-up
3000
5000
7000
9000
200 700 1200 1700
h (
W/m
2K
)
Re (-)
3000
5000
7000
9000
10.00 20.00 30.00 40.00
h (
W/m
2K
)
Q (ml/min)
3000
5000
7000
9000
0.500 1.000 1.500 2.000
h (
W/m
2K
)m (kg/hr)
3000
5000
7000
9000
0.2000 0.7000 1.2000
h (
W/m
2K
)
ΔP (Bar)
3000
5000
7000
9000
0.0 20.0 40.0 60.0
h (
W/m
2k)
P (mW)
38
Comparison at Constant Re
Renf = Rebfunfubf
=μnfμbf
×ρnfρbf
−1
μnfμbf
≫ρnfρbf
unfubf
> 1 More pumping power!
Unfortunately it is dominant in the literature!
40
Higher “cost” to run the system due
to this increased pumping power
Comparison at Constant Re
Author Nanofluid Dimension, ReMethod ofComparison
Enhancement of hnf
and comments
Wen and Ding [66]Al2O3/water1.6 vol%
D = 4.5 mm
L = 972Re = 500 – 2100
Same Re47 % near the inlet
region, 14% near the discharge region.
Hwang et al. [67]Al2O3/water0.3 vol%
D = 1.8 mm
L = 2502Re = 400 – 700
Same Re
8% in the developed
region, k increase by
1.44%, viscosity increase by 3%
Rea et al. [68]
Al2O3/water
6 vol%
ZrO2/water1.32 vol%
D = 4.5 mm
L = 1008Re = 140 – 1888
Same velocity
27% for alumina and
3% for zirconia.
Nunf followed single–phase correlation.
Anoop et al. [41]Al2O3/water4 wt%
D = 4.75 mm
L = 1202Re = 700 – 2000
Same Re25% for 45 nm particle
size and 11% for 150 nm particle size.
Liu and Yu [69]Al2O3/water5 vol%
D =1.09 mm
L = 305Re=600 – 4500
Same Re
19% near the entrance
region, 9% near the
discharge region.
Nunf followed single–phase correlation
Vafaei and Wen [70]Al2O3/water1–7 vol%
D = 0.51 mmL = 306
Same velocity
100% at high flow rate,
but no enhancement at low flow rate
He et al. [39]TiO2/water1.1 vol%
D =3.97 mm
L = 1834Re=900 – 5900
Same Re12% in laminar flow and 40% in turbulent flow
Ding et al. [5]CNT/water0.5 wt%
D =4.5 mm
L = 972Re=800 – 1200
Same Re350% in the developed region
Garg et al. [71]CNT/water1 wt%
D =1.55 mm
L = 915Re=600 – 1200
Same Re32% in the developed region
Author Nanofluid Dimension, ReMethod ofComparison
Enhancement of hnf
and comments
Pak and Cho [62]γ-Al2O3/water
and TiO2/water1–3 vol%
D=10.66 mm,
L=4800 mm, Re=104–105
Same velocity
12% lower for γ-Al2O3/water at 3 vol %
He et al. [39]TiO2/water0.2–1.1 vol%
D=3.97 mm,
L=1834 mm, Re=2000–6000
Same ReMaximum 40%
enhancement for 1.1 vol % at Re=5900
Kulkarni [72]
TiO2/(EG–
water 60:40
wt%) 2–10 vol%
D=3.14 mm,
L=1000 mm, Re=3000–12000
Same Re16% enhancement for 10 vol % at Re=10000
Yu et al. [73]SiC/water3.7 vol%
D=2.27 mm, L=580
mm, Re=3300–13000
Same velocity
7% lower
Duangthongsuk and Wongwises [74]
TiO2/water
0.2 – 2.0 vol%
D=9.53 mm,
L=1500 mm,
Re=3000 – 18000
Same Re20–32% enhancement
at 1.0 vol %
Fotukian and Nasr
Esfahany [75]
γ–Al2O3/water
less than 0.2
vol%
D=5 mm, L=1000
mm, Re=6000 –
31000
Same Re48% enhancement at
Re= 10000 and 0.054
vol%
Suresh et al [76]Al2O3/water
0.3 – 0.5 vol%
D=4.85 mm, L=800
mm, Re=700 –
2050
Same Re10 – 48%
enhancement
Fotukian and Nasr
Esfahany [77]
CuO/water
less than 0.24
vol%
D=5 mm, L=1000
mm, Re=6000 –
31000
Same ReMaximum 25%
enhancement
Sajadi and Kazemi
[78]
TiO2/water
less than 0.25
vol%.
D=5 mm, L=1800
mm, Re=5000 –
30000
Same Re~22% enhancement at
Re=5000 and 0.25
vol%
Kayhani et al [79]TiO2/water
0.1 – 2.0 vol%
D=5 mm, L=2000
mm, Re=6000 –
16000
Same Re8% enhancement at
Re= 11800 and 2.0
vol%
Laminar Turbulent
7 out of 9! 8 out of 10!
41
NFs characterisation
NFs’ source NP
Solid
concentration (wt%/vol%)
BF pH
SEM or
TEM
particle size (nm)
Most
common
DLS
particle size (nm)
Additives type or amount (g surfactant/g solid)
Dispersia Ltd, UK Al2O3 (I) 9 / 2.4 DW 5 ~ 10 180Polyacrylic acid copolymer
sodium salt (0.5 %)
Dispersia Ltd, UK Al2O3 (II) 9 / 2.4 DW 5 ~ 10 60 No additives
Dispersia Ltd TiO2 (I) 9 / 2.3 DW 7.4 20 – 25 170polyacrylic acid
ammonium salt (10.45 %)
ItN Nanovation TiO2 (II) 9 / 2.3 DW 7.4 20 – 25 170polyacrylic acid
ammonium salt (10.45 %)
Nano Grade,
SwitzerlandCeO2 9 / 1.3 DW 7 –8 50 – 100 200 No additives
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 250 500 750
Dif
f. In
ten
sit
y (
%)
Diameter (nm)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 75 150 225
Dif
f. In
ten
sit
y (
%)
Diameter (nm)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0 200 400 600
Inte
ns
ity (
%)
Diameter (nm)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0 250 500
Inte
ns
ity (
%)
Diameter (nm)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 250 500 750
Inte
ns
ity (
%)
Diameter (nm)Al2O3 (I) Al2O3 (II)
TiO2 (I) TiO2 (II)
CeO2
43
Thermal Conductivity & Viscosity
• Thermal conductivity: Maxwell can predict
• Relative viscosity is much higher than relative thermal conductivity
Same conclusion as before
44
Convective Heat Transfer & Pressure Drop
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
0.000 0.100 0.200 0.300
Nu
L*
ShahShah +/- 15%DWAl2O3 (I)Al2O3 (II)TiO2 (I)TiO2 (II)CeO2
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
200 400 600 800 1000 1200
f
Re
DWAl2O3 (I)Al2O3 (II)TiO2 (I)TiO2 (II)CeO2DarcyDarcy +/- 15%
Convective heat transfer and pressure drop: traditional equations can predict
45
Comparison
4000
4500
5000
5500
6000
6500
7000
200 700 1200
h (
W.m
-2.K
-1)
Re
DWAl2O3 (I)Al2O3 (II)TiO2 (I)TiO2 (II)CeO2
4000
4500
5000
5500
6000
6500
7000
0.5 1.0 1.5
h (
W.m
-2.K
-1)
m (kg/hr)
DWAl2O3 (I)Al2O3 (II)TiO2 (I)TiO2 (II)CeO2
4000
4500
5000
5500
6000
6500
7000
0.5 1.0 1.5 2.0 2.5
h (
W.m
-2.K
-1)
V (m/s)
DWAl2O3 (I)Al2O3 (II)TiO2 (I)TiO2 (II)CeO2
4000
4500
5000
5500
6000
6500
7000
0.0 10.0 20.0 30.0 40.0
h (
W.m
-2.K
-1)
P (mW)
DWAl2O3 (I)Al2O3 (II)TiO2 (I)TiO2 (II)CeO2
46
NFs characterisation
NFs’ source NP
Solid
concentration (wt%/vol%)
BF pH
SEM or
TEM
particle size (nm)
Most
common
DLS
particle size (nm)
Additives type or amount (g surfactant/g solid)
ItN Nanovation,
GermanyAl2O3 (I) 9 / 2.4 DW 9.1 100 – 200 200 1.5% – 1.8%
Evonik (Aerodisp
440)Al2O3 (II) 9 / 2.4 DW 4.1 10 – 20 150 1.4 %
ItN Nanovation TiO2 (I) 9 / 2.3 DW 7.8 15 – 50
220 nm or
140 nm
(ultrasonica
ted)
20.8 %
Evonik (Aerodisp
W740X)TiO2 (II) 9 / 2.3 DW 6.7 15 – 50 130 3.0 %
0
5
10
15
20
25
0 500
Inte
ns
ity (
%)
Diameter (nm)
0
5
10
15
20
0 500
Inte
ns
ity (
%)
Diameter (nm)
0
5
10
15
0 500
Inte
ns
ity (
%)
Diameter (nm)
0
5
10
15
0 500
Inte
ns
ity (
%)
Diameter (nm)
Al2O3 (I)
Al2O3 (II)
TiO2 (I)
TiO2 (II)
48
Convective Heat Transfer and Pressure Drop
Convective heat transfer & pressure drop: traditional equations can predict
49
NFs characterisation
NFs’ source NP
Solid
concentration (wt%/vol%)
BF pH
SEM or
TEM
particle size (nm)
Most
common
DLS
particle size (nm)
Additives type or amount (g surfactant/g solid)
ItN Nanovation,
GermanyAl2O3 9 / 2.4 DW 9.1 100 – 200 200 1.5% – 1.8%
Evonik (Aerodisp
W740X)TiO2 9 / 2.3 DW 6.7 15 – 50 130 3.0 %
0
5
10
15
20
25
0 500
Inte
ns
ity (
%)
Diameter (nm)
0
5
10
15
0 500
Inte
ns
ity (
%)
Diameter (nm)
Al2O3 TiO2
52
Thermal Conductivity & Viscosity
• Thermal conductivity: Maxwell can predict
• Relative viscosity is much higher than relative thermal conductivity
Same conclusion as before
53
Convective Heat Transfer
0
20
40
60
80
2000 4000 6000 8000 10000
Nu
(-)
Re (-)
KTH (Al₂O₃)UBHAM (Al₂O₃)GnielinskiGnielinski +/- 10%
0
20
40
60
80
2000 4000 6000 8000 10000
Nu
(-)
Re (-)
KTH (Al₂O₃)UBHAM (Al₂O₃)GnielinskiGnielinski +/- 10%
0
20
40
60
80
2000 4000 6000 8000 10000
Nu
(-)
Re (-)
KTH (TiO₂)UBHAM (TiO₂)GnielinskiGnielinski +/- 10%
0
20
40
60
80
2000 4000 6000 8000 10000
Nu
(-)
Re (-)
KTH (TiO₂)UBHAM (TiO₂)GnielinskiGnielinski +/- 10%
25 °C
40 °C
25 °C
40 °C
Convective heat transfer: traditional equations can predict 54
Pressure Drop
0.02
0.03
0.04
0.05
0.06
4000 6000 8000 10000
f (-
)
Re (-)
KTH (DW)KTH (Al₂O₃) KTH (TiO₂)FilonenkoFilonenko +/- 10%
Pressure drop: traditional equations can predict
55
Comparison
-5
0
5
10
15
20
3000 4500 6000 7500 9000
Incr
eas
e (
%)
Re (-)
-5
0
5
10
15
20
3000 4500 6000 7500 9000
Incr
eas
e (
%)
Re (-)
-25
-20
-15
-10
-5
0
5
10
0 500 1000
Incr
eas
e (
%)
P (mW)
-25
-20
-15
-10
-5
0
5
10
0 500 1000
Incr
eas
e (
%)
P (mW)
25 °C
40 °C
25 °C
40 °C
56
Paper 7: A method predicting the cooling efficiency of NFs combining the effect of physical and transport properties
57
NFs characterisation
NFs’ source NP
Solid
concentration (wt%/vol%)
BF pH
SEM or
TEM
particle size (nm)
Most common
DLS particle size (nm)
Additives type or
amount (g surfactant/g solid)
ItN Nanovation,
Germany
Al2O3
(ITN-AL)3 – 40 / 1 – 14 DW 9.1 100 – 200 200 1.5% – 1.8%
Evonik (Aerodisp
440)
Al2O3
(EVO-AL)3 – 40 / 1 – 17 DW 4.1 10 – 20 150 1.4 %
Alafa Aesar
(Nanodur X1121W)
Al2O3
(AA-AL)3 – 40 / 1 – 14 DW 4.0 10 – 80 160 12.7 %
ItN NanovationTiO2
(ITN-TI)3 – 20 / 1 – 6 DW 7.8 15 – 50
220 nm or
140 nm
(ultrasonicated)
20.8 %
Evonik (Aerodisp
W740X)
TiO2
(EVO-TI)3 – 40 / 1 – 15 DW 6.7 15 – 50 130 3.0 %
Eka Chemical
Levasil 100SiO2
(LEVASIL-SI)3 – 45 / 1 – 27 DW 10
30 nm
spherical90 0 %
Alfa Aesar (Nanotek
CE6042)CeO2
(AA-CI)3 – 20 / 0.5 – 3 DW 2.5
30 nm
(cubic)160 0.5 %
58
Thermal Conductivity (1)
1.0
1.1
1.2
1.3
1.4
1.5
1.6
0.0 10.0 20.0 30.0 40.0
kr-E
xp
wt.%
EVO-AL (KTH)EVO-AL (UBHAM)ITN-AL (KTH)ITN-AL (UBHAM)AA-AL (KTH)AA-AL (UBHAM)EVO-TI (KTH)EVO-TI (UBHAM)ITN-TI (KTH)ITN-TI (UBHAM)LEVASIL-SI (KTH)LEVASIL-SI (UBHAM)AA-CI (KTH)AA-CI (UBHAM)
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.0 1.1 1.2 1.3 1.4 1.5 1.6
kr-E
xp
kr-Maxwell
EVO-AL (KTH)EVO-AL (UBHAM)ITN-AL (KTH)ITN-AL (UBHAM)AA-AL (KTH)AA-AL (UBHAM)EVO-TI (KTH)EVO-TI (UBHAM)ITN-TI (KTH)ITN-TI (UBHAM)LEVASIL-SI (KTH)LEVASIL-SI (UBHAM)AA-CI (KTH)AA-CI (UBHAM)kr-Exp=kr-Maxwell(+/-) 10%
20 °C
59
Thermal Conductivity (2)
1.00
1.05
1.10
1.15
10 20 30 40 50 60
kr-E
xp
T (˚C)
EVO-ALITN-ALAA-ALEVO-TIITN-TILEVASIL-SIAA-CI
1.00
1.05
1.10
1.15
1.00 1.05 1.10 1.15kr
-Exp
kr-Maxwell
EVO-ALITN-ALAA-ALEVO-TIITN-TILEVASIL-SIAA-CIkr-Exp=kr-Maxwell(+/-) 10%
60
9 wt%
Viscosity (1)
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
0.0 10.0 20.0 30.0 40.0
µr-
Exp
wt.%
EVO-AL (KTH)EVO-AL (UBHAM)ITN-AL (KTH)ITN-AL (UBHAM)AA-AL (KTH)AA-AL (UBHAM)EVO-TI (KTH)EVO-TI (UBHAM)ITN-TI (KTH)ITN-TI (UBHAM)LEVASIL-SI (KTH)LEVASIL-SI (UBHAM)AA-CI (KTH)AA-CI (UBHAM)
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
1.0 3.0 5.0 7.0
µr-
Exp
µr-KD
EVO-AL (KTH)EVO-AL (UBHAM)ITN-AL (KTH)ITN-AL (UBHAM)AA-AL (KTH)AA-AL (UBHAM)EVO-TI (KTH)EVO-TI (UBHAM)ITN-TI (KTH)ITN-TI (UBHAM)LEVASIL-SI (KTH)LEVASIL-SI (UBHAM)AA-CI (KTH)AA-CI (UBHAM)µr-Exp=µr-KD(+/-) 10%
20 °C
61
Viscosity (2)
1.0
1.1
1.2
1.3
1.4
1.5
1.6
10 20 30 40 50
µ-r
el-
Exp
T (˚C)
EVO-ALITN-ALAA-ALEVO-TIITN-TILEVASIL-SIAA-CI
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.0 1.2 1.4 1.6
µ-r
el-
Exp
µ-rel-KD
EVO-ALITN-ALAA-ALEVO-TIITN-TILEVASIL-SIAA-CIµr-Exp=µr-KD(+/-) 10%
62
9 wt%
Thermal Conductivity & Viscosity
• Thermal conductivity: Maxwell can predict even at elevated temperature
• Viscosity: modified Krieger–Dougherty can predict even at elevated temperature
• Relative viscosity is much higher than relative thermal conductivity
63
Comparison
-1.0
0.0
1.0
2.0
3.0
0 10 20 30
λ (˚
C)
wt.%
Equal Re
Equal V
Equal P
-1.0
0.0
1.0
2.0
3.0
0 10 20 30
λ (˚
C)
wt.%
Equal Re
Equal V
Equal P
Laminar Turbulent
ITN-AL
64
𝜆 = 𝑄1
𝑚𝑐𝑝 𝑏𝑓
1 −𝜌𝑏𝑓
𝜌𝑛𝑓×𝑐𝑝,𝑏𝑓
𝑐𝑝,𝑛𝑓×𝑢𝑏𝑓
𝑢𝑛𝑓+
1
𝜋𝑑𝐿ℎ𝑏𝑓1 −
ℎ𝑏𝑓
ℎ𝑛𝑓
NFs characterisation
NFs’ source NP
Solid
concentrati
on (wt%/vol%)
BF pH
SEM or
TEM
particle size (nm)
Most
common
DLS particle size (nm)
Additives type or
amount (g surfactant/g solid)
Clay I (CPI, UK) Clay (I) 9 / 3.8 DW 8 – 8.5 20 – 40* 1420 No info
Clay II (CPI, UK) Clay (II) 9 / 2.7 DW 8 – 8.5 40 – 400 490 No info
Clay III
(ItN Nanovation, Germany) Clay (III) 1.75 / 0.4 DW 7 80 – 250 320 No additives
ItN Nanovation, Germany Al2O3 9 / 2.4 DWNo
info40 – 200 220 No info
0
1
2
3
4
5
0 2000 4000 6000
Inte
nsi
ty (
%)
Diameter (nm)
0
2
4
6
8
10
0 200 400 600 800
Inte
nsi
ty (
%)
Diameter (nm)
0
2
4
6
8
10
12
0 200 400
Inte
nsi
ty (
%)
Diameter (nm)
0
2
4
6
8
10
0 200 400 600
%In
ten
sity
Diameter (nm)
Clay (I) Clay (II)
Clay (III) Al2O3
66
Photography Method
A sample of photographs for of
Clay (I), (II) and (III) NFs at the
beginning (a), after 30 minutes (b),
1 hour (c), 5 hours (d), 10 hours
(e), 20 hours (f), 30 hours (g) and
40 hours (h) of measurement
After eight days
Clay (I), (II), (III)
68
Conclusion
• Adding NPs to common BFs essentially changes the
thermophysical properties of BFs in either a positive (+) or
a negative (-) way:
• Thermal conductivity increases (+)
• Viscosity increases (-)
• Density increases (-)
• Specific heat decreases (-)
• The effects of all of the thermophysical properties (not just
one) must be taken into consideration while discussing the
advantages or disadvantages of replacing NFs with BFs in
cooling systems
71
Conclusion
• The Maxwell model can predict thermal conductivity of
most of the NFs tested within 10% uncertainty
• The modified Krieger–Dougherty (K-D) model can predict
the viscosity of most of these NFs within 10% error
• The success of (K-D) model is highly dependent on
knowing the ratio of aggregated to primary particles, as
well as on an experimental determination of another
variable called the fractional index
• When correct thermophysical properties, either from
experiments or trustable models, are used, the classical
correlations traditionally used for common fluids are still
valid for NFs with acceptable error
72
Conclusion
• Mechanisms such as nanoparticle migration due to Brownian motion or thermophoresis seem to have negligible effects on thermophysical and transport properties of NFs
• Comparing the results at the same Reynolds numbers, although the most popular method employed in the literature, is not relevant in practical applications
• The evaluation of the heat transfer performance of the NFs at equal pumping power is the most appropriate and correct approach from an industrial point of view
• Based on this criterion, the experimental results of this study show only a small benefit for some NFs in laminar flow for cooling applications. In turbulent flow, however, NFs evidenced no benefit at all
73
Conclusion
• To quickly check the feasibility of replacing BFs with NFs,
a method of analysis was suggested based on the
calculation of the highest wall temperature in a heat sink
• The applicability of the sedimentation balance method to
analysing the sedimentation behaviour of NFs was
illustrated successfully
• Commercialisation of NFs for cooling applications is still a
relevant question
• The focus of future research must move towards the
material synthesis of NFs with the purpose to reduce the
viscosity increases experienced by BFs due to the addition
of NPs
74
Future Work
Nanofluid synthesis
Measure viscosity
Calculate thermal conductivity (Maxwell) and heat transfer coefficient (traditional eqns)
Suggested Model
Change synthesis parameters in order to reduce viscosity
Yes
No
Measure shelf stability
Try to suggest a
trustable model
75