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A CFD MODEL DEVELOPMENT AND
PERFORMANCE INVESTIGATION OF FROST FREE
REFRIGERATOR WITH NANOPARTICLES
SUSPENDED IN THE LUBRICANT
MUHAMMAD EHTESHAMUL HAQUE
DOCTOR OF PHILOSOPHY
UNIVERSITI MALAYSIA PAHANG
iii
SUPERVISOR’S DECLARATION
I hereby declare that I have checked this thesis and in my opinion, this thesis is adequate
in terms of scope and quality for the award of the degree of Doctor of Philosophy in
Mechanical Engineering.
__________________________________
Supervisor’s Signature
Full Name : PROF. DATO’ DR. ROSLI ABU BAKAR
Position : PROFESSOR
Date :
iv
STUDENT’S DECLARATION
I hereby declare that the work in this thesis is based on my original work except for
quotations and citation which have been duly acknowledged. I also declare that it has
not been previously or concurrently submitted for any other degree at Universiti
Malaysia Pahang or any other institutions.
________________________________
Author’s Signature
Full Name : MUHAMMAD EHTESHAMUL HAQUE
ID Number : PMM12007
Date :
i
A CFD MODEL DEVELOPMENT AND PERFORMANCE INVESTIGATION OF
FROST FREE REFRIGERATOR WITH NANOPARTICLES SUSPENDED IN THE
LUBRICANT
MUHAMMAD EHTESHAMUL HAQUE
Thesis submitted in fulfillment of the requirements for the award of the degree of
Doctor of Philosophy
Faculty of Mechanical Engineering
UNIVERSITI MALAYSIA PAHANG
MARCH 2019
ii
DEDICATION
“This thesis is dedicated to my wife Zareen, and kids Maheen, Rafay, and Zayan”
For their immense and endless love; support and encouragement throughout the study
iii
ACKNOWLEDGMENTS
In the name of Allah the most merciful, the most beneficent. All praise to Allah, the
Creator and Sustainer of the entire universe. Peace and blessings of Allah to his Last
messenger Prophet Muhammad صلى الله عليه وسلم. Thanks to Allah Almighty who granted me the
strength and ability to achieve this task.
I wish to express my sincere gratitude to my supervisor, Professor Dato’ Dr. Hj. Rosli
Bin Abu Bakar for his invaluable guidance, suggestion, and support throughout my
research. I would also like to thank my co-supervisor, Dr. Gan Leong Ming for his
timely support and assistance.
I am thankful to the Faculty of Mechanical Engineering and all staff. I would also like
to express my sincere gratitude to post grade students, faculty and staff of thermal
laboratory lab and HVAC lab in the mechanical faculty for their help in facilitation
during my experimental work. Special thanks to Billy Anak Anak for helping me in
making the test rig. I would also like to acknowledge the help and assistance provided
by Mr. Yousof Taib, and for providing me the refrigerator, tools, instrumentations, and
material for the project.
This research was financially supported by Universiti Malaysia Pahang under the grant
number GRS 140311. I wish to acknowledge the financial assistance provided by NED
University of Engineering and Technology and Higher Education Commission (HEC)
of Pakistan.
Finally, I would like to thank my wife and children for their patience and support during
my research project.
Muhammad Ehteshamul Haque
iv
ABSTRACT
In a refrigerator, airflow and temperature distribution along with the properties of the
lubricating oil defines its efficiency and performance. The purpose of this work is to
develop a numerical model to predict the airflow and temperature inside the refrigerated
space and use nanoparticles in the compressor lubricating oil to improve the efficiency
of the refrigerating system. The present research focuses to improve the performance
and efficiency of the refrigerator through the analysis by CFD and nanotechnology. The
objective is to develop a CFD model for airflow and temperature distribution inside the
refrigerator and validated it with experimental results. The model is then used for
parametric study to modify the inside geometry of the refrigerator to improve better
airflow and temperature distribution. To improve the cyclic efficiency of the refrigerator
Nano-particles are added into the compressor lubricant to improve the lubricity of
Polyol ester oil (POE), thereby improving the performance of the refrigerator. In this
research work, CFD model has been developed for a domestic no-frost refrigerator. The
conservation equations of energy mass and momentum are solved by using Finite
Volume Method (FVM) in an environment of three-dimensional unstructured mesh.
Experiments were conducted on a no-frost domestic refrigerator to compare and
validate the results of the CFD model. Nano particles when added to the lubricating oil
is called Nano-lubricant. In the present study, three nanoparticles namely Al2O3, TiO2
and SiO2 have been added to the lubricant oil of a domestic refrigerator and experiments
have been performed to determine the enhancement in the performance of the
refrigerator. A CFD model for the selected refrigerator has been developed in Ansys
software. This CFD model has been validated by experimental results. A comparison of
CFD model and experimental results of surface temperature in freezer and refrigerator
compartment are within the acceptable range of 5% difference. In the freezer
compartment the difference in temperature on a vertical line at the center of freezer as
predict by the CFD model and experiment is less than one percent. Similarly, the
temperature difference, as measured by experiment and predicted by the CFD model, on
a central vertical line inside the refrigerator compartment, is less than three percent. The
result of the parametric study by using the developed CFD model showed improvement
in the temperature distribution inside the refrigerator compartment. Through this
research work, it is established that CFD can be used successfully to model the airflow
and temperature distribution inside the refrigerator. The results of experiments with
nanoparticles suspended in the lubricant oil of the compressor showed better
performance of the refrigerator as compared to pure Polyol Easter (POE) oil system.
The energy consumption of 0.05% SiO2 nanolubricant is 9.4% less than pure POE oil
system. Similarly, the energy consumption of compressor with 0.1% TiO2 nanoparticles
is 6.84% lower than the pure POE oil system. COP of the refrigerator increased by 29%
when 0.1% SiO2 nanoparticle was added to the compressor lubricant. Therefore, the
addition of nanoparticles in the refrigerator system has very good potential to improve
the energy consumption and COP of the unit.
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ABSTRAK
Dalam peti sejuk, aliran udara dan pengagihan suhu bersama-sama dengan sifat-sifat
minyak pelincir mentakrifkan kecekapan dan prestasinya. Tujuan kerja ini adalah untuk
membangunkan model berangka untuk meramalkan aliran udara dan suhu di dalam
ruang yang didinginkan dan menggunakan nanopartikel dalam minyak pelincir
pemampat untuk meningkatkan kecekapan sistem penyejukan. Penyelidikan kini
memberi tumpuan untuk meningkatkan prestasi dan kecekapan peti sejuk melalui
analisis oleh CFD dan nanoteknologi. Dalam kajian ini, model CFD telah dibangunkan
untuk peti sejuk beku domestik. Persamaan pemuliharaan jisim dan momentum energi
diselesaikan dengan menggunakan Kaedah Volum Hingga dalam persekitaran mesh tak
berstruktur tiga dimensi. Eksperimen dilakukan di peti sejuk domestik tanpa beku untuk
membandingkan dan mengesahkan keputusan model CFD. Nano zarah apabila
ditambah ke minyak pelincir dipanggil nanolubricant. Dalam kajian ini, tiga
nanopartikel iaitu Al2O3, TiO2 dan SiO2 telah ditambah kepada minyak pelincir kulkas
domestik dan eksperimen telah dilakukan untuk menentukan peningkatan dalam prestasi
peti sejuk. Model CFD untuk peti sejuk terpilih telah dibangunkan dalam perisian
Ansys. Model CFD ini telah disahkan oleh keputusan percubaan. Perbandingan model
CFD dan hasil eksperimen suhu permukaan dalam peti sejuk dan ruang peti sejuk
berada dalam julat yang boleh diterima. Dalam petak penyejuk beku perbezaan suhu
pada garis menegak di pusat beku seperti yang diramalkan oleh model CFD dan
eksperimen adalah kurang daripada satu peratus. Begitu juga, perbezaan suhu, seperti
yang diukur oleh percubaan dan diramalkan oleh model CFD, pada garis menegak pusat
di dalam petak peti sejuk, adalah kurang daripada tiga peratus. Hasil kajian parametrik
dengan menggunakan model CFD yang maju menunjukkan peningkatan dalam
pengedaran suhu di dalam ruang peti sejuk. Melalui kerja penyelidikan ini, didapati
CFD dapat digunakan dengan baik untuk memodelkan aliran udara dan pengedaran
suhu di dalam peti sejuk. Keputusan eksperimen dengan nanopartikel yang digantung di
minyak pelincir pemampat menunjukkan prestasi yang lebih baik dari peti sejuk
berbanding dengan sistem minyak Tulen Eolol (POE) tulen. Penggunaan tenaga 0.05%
SiO2 nanolubricant adalah 9.4% kurang daripada sistem minyak POE tulen. Begitu
juga, penggunaan tenaga pemampat dengan 0.1% TiO2 nanopartikel adalah 6.84% lebih
rendah daripada sistem minyak POE tulen. COP peti sejuk meningkat sebanyak 29%
apabila 0.1% SiO2 nanoparticle ditambah kepada pelincir pemampat. Oleh itu,
penambahan nanopartikel dalam sistem peti sejuk mempunyai potensi yang sangat baik
untuk meningkatkan penggunaan tenaga dan COP unit.
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TABLE OF CONTENTS
DECLARATION
TITLE PAGE
DEDICATION ii
ACKNOWLEDGMENTS iii
ABSTRACT iv
ABSTRAK v
TABLE OF CONTENTS vi
LIST OF TABLES xi
LIST OF FIGURES xiii
LIST OF SYMBOLS xvii
LIST OF ABBREVIATIONS
xix
CHAPTER 1 INTRODUCTION 1
1.1 BACKGROUND 1
1.2 Vapor Compression Refrigeration Cycle 2
1.2.1 Refrigerants 5
1.3 Nanofluid 6
1.3.1 Nanofluid Preparation 6
1.3.2 Thermal Conductivity of Nanofluids 7
1.3.3 Viscosity of Nanofluid 7
1.3.4 Pressure Drop Caused By Nanoparticles 8
1.3.5 Coefficient Of Friction and Wear Rate of Nanofluids 8
1.4 CFD study of refrigerator 8
1.5 Problem statement 9
1.6 Research Objective 10
1.7 Statement of Novelty and Contribution 10
1.8 Scope of study 11
CHAPTER 2 LITERATURE REVIEW 12
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2.1 Introduction 12
2.2 CFD modeling of refrigerator 13
2.2.1 Steps involved in CFD 13
2.2.1.1 Pre-Processing 13
2.2.1.2 Solving 14
2.2.1.3 Post-Processing 14
2.3 Mathematical models 18
2.3.1 Laminar Flow 18
2.3.2 Turbulent Flow 19
2.3.2.1 Direct Numerical Simulation (DNS) 19
2.3.2.2 Reynolds Averaged Navier-Stokes Model (RANS) 19
2.3.2.3The k-ε model 20
2.3.2.4 Large Eddy Simulation 21
2.4 Numerical Techniques 21
2.4.1 Discretization Procedure 21
2.4.2 Spatial Discretization of Conservation Equations 23
2.4.3 Central Differencing Scheme 24
2.4.4 First-Order Upwind Scheme 25
2.4.5 Second-Order Upwind Scheme 25
2.4.6 QUICK Scheme 26
2.4.7 Equations’ temporal discretization 26
2.4.8 Pressure-Velocity Coupling Algorithms 28
2.4.9 SIMPLE Algorithm 28
2.4.10 SIMPLEC Algorithm 33
2.4.11 Solution methods of Algebraic Equations 34
2.5 CFD And experimental studies of refrigerators and refrigerating
systems
34
2.5.1 Static Refrigerator 35
2.5.2 Ventilated Refrigerator 43
2.6 Nanofluid application in refrigerating systems 50
2.6.1 Preparation of Nanofluids 51
2.6.2 One-Step Method 52
2.6.3 Two-Step Method 52
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2.6.4 Thermophysical Properties of Nanofluids 53
2.6.5 Thermal Conductivity (k) 54
2.6.6 Viscosity (µ) 55
2.7 Effect of nanofluid on performance of refrigerating systems 58
2.7.1 Heat Transfer Enhancement 59
2.7.2 Pool Boiling and Flow Boiling 59
2.7.3 Viscosity and pressure drop 62
2.7.4 Solubility of Refrigerant into Lubricating Oil 63
2.7.5 Friction Coefficient and Wear Rate 64
2.7.6 Effect of Surfactants 64
2.7.7 COP Enhancement 65
CHAPTER 3 METHODOLOGY 67
3.1 Numerical simulation of refrigerator 67
3.1.1 Importance of Numerical Simulation 67
3.1.2 Physical Model for Simulation 69
3.1.3 Geometry for the CFD Domain Development 72
3.1.4 Mesh Generation and Grid Independence 74
3.1.5 Solution Methods and Solution Controls 78
3.1.6 Convergence Criteria and Solution Monitoring 80
3.1.7 Solution Control and Under-Relaxation Factors 81
3.2 Assumptions and Boundary Conditions 82
3.2.1 Governing Equations of CFD 83
3.2.2 Continuity Equation 83
3.2.3 Momentum Equation 83
3.2.4 Energy Equation 84
3.3 Boundary Conditions 84
3.4 Experimental Setup and Procedure 94
3.4.1 Experimental Apparatus 94
3.4.2 Pressure Measurement 96
3.4.3 Temperature Measurement 98
3.4.4 Velocity Measurement 103
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3.4.5 Energy and Power Measurement 103
3.4.6 Experimental Procedure for CFD model validation 104
3.5 Application of Nanoparticles 105
3.5.1 Preparation of Nanolubricants 106
3.5.2 Thermal Conductivity 109
3.5.3 Viscosity 109
3.5.4 System Evacuation 110
3.5.5 System Charging 112
3.5.6 Data Collection and Analysis 112
3.5.6.1 Coefficient of Performance (COP) 112
3.5.6.2 Performance Test 113
3.6 Summary 113
CHAPTER 4 RESULTS AND DISCUSSION 115
4.1 Introduction 115
4.2 Temperature and Velocity Simulations 115
4.2.1 Airflow Simulation in the Refrigerator and Freezer
Compartments
115
4.2.2 Temperature Simulation in Refrigerator and Freezer
Compartments
124
4.3 Validation of numerical model with experimental Results 131
4.3.1 Comparison of Temperature in Freezer Compartment 132
4.3.2 Comparison of Temperature in Refrigerator Compartment 133
4.3.3 Study of Nusselt Number 134
4.4 Parametric Study 138
4.4.1 Comparing temperature on a vertical line for parametric study 140
4.5 Performance of the refrigerator with nanoparticles based lubricants 142
4.5.1 Thermophysical Properties of Nanoparticles based Lubricants 142
4.5.1.1 Thermal Conductivity 143
4.5.1.2 Viscosity 145
4.5.2 POE Oil and Nanolubricant with 0.05% Nanoparticles 146
4.5.3 POE Oil and Nanolubricant with 0.1% Nanoparticles 151
x
4.5.4 Results of Power and Energy Consumption 155
4.5.5 Results of Pressure Measurement 157
4.5.6 Coefficient of Performance of the Refrigerator with POE Oil
and Nanolubricant
159
4.6 Summary 162
CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS 165
5.1 Recommendations for future work 168
REFERENCES 170
LIST OF PUBLICATIONS 188
APPENDICES 190
xi
LIST OF TABLES
Table 2.1 CFD application for refrigerator 16
Table 2.2 CFD simulations of refrigerators 49
Table 2.3 Models for thermal conductivity of nanofluids 55
Table 3.1 Specification of the refrigerator 69
Table 3.2 Parameters setting for mesh sizing 77
Table 3.3 Parameter settings for inflation layers 77
Table 3.4 Mesh Statistics and Mesh Metric for Skewness and Aspact Ratio 77
Table 3.5 Basic settings for CFD simulation 79
Table 3.6 Solution Method Settings 80
Table 3.7 Residual Monitors Settings 81
Table 3.8 Under Relaxation Factors 81
Table 3.9 Walls of refrigerator and freezer used for calculations 86
Table 3.10 Physical and thermal properties of wall materials 87
Table 3.11 Inside and outside temperatures of air and surfaces 87
Table 3.12 Thermal resistances of walls and overall heat transfer coefficient 93
Table 3.13 List of Instruments used and their specifications 104
Table 3.14 Thermophysical properties of Nanoparticles 107
Table 3.15 Test conditions for energy consumption procedures 114
Table 4.1 Comparison of numerical and experimental temperatures at
selected points on a vertical line in freezer
133
Table 4.2 Comparison of numerical and experimental temperatures at
selected points on a vertical line in refrigerator
134
Table 4.3 Empirical calculation for Nusselt number variation along the
height of the refrigerator
137
Table 4.4 The design parameter values 139
Table 4.5 Temperature values at three points of all parametric study 142
Table 4.6 Comparison of temperature on different surfaces inside the
freezer compartment with 0.05% by volume of nanoparticles
added to POE oil
148
Table 4.8 Comparison of temperatures on different surfaces inside the
freezer compartment with 0.1% by volume of nanoparticles
added to POE oil
152
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Table 4.9 Comparison of temperatures on different surfaces inside the
refrigerator with 0.1% by volume of nanoparticles added to POE
oil
154
Table 4.10 Energy consumption of the systems with Lubricant and
nanolubricants
156
Table 4.11 Experimental data of system parameters 160
Table 4.12 COP calculation and analysis for all systems 160
Table 4.13 Comparison table for performance improvement of refrigeration
systems
163
xiii
LIST OF FIGURES
Figure 1.1 Schematic diagram of vapor compression refrigeration system 3
Figure 1.2 T-s and p-h chart of Vapor compression cycle 4
Figure 2.1 Cell P and its neighbor cells 24
Figure 2.2 Face e and its interpolated value 25
Figure 2.3 Face e and its interpolated value (QUICK Scheme) 26
Figure 2.4 One dimensional grid point cluster 29
Figure 2.5 Wavy or zigzag velocity or pressure field 30
Figure 3.1 Flow chart for CFD simulation 68
Figure 3.2 Refrigerator used for the experiment 70
Figure 3.3 Air flow and heat transfer in refrigerator 71
Figure 3.4 A detail view of the simulated refrigerator 72
Figure 3.5 Inside detail view of the simulated refrigerator 73
Figure 3.6 Fluid Domain (a) Full domain (b) half domain 74
Figure 3.7 Mesh generation for the refrigerator 76
Figure 3.8 Temperature profile for Mesh A, B, and C along a vertical line 78
Figure 3.9 Designation of each wall 85
Figure 3.10 Schematic diagram of refrigerator walls 86
Figure 3.11 Thermal resistance network for walls of freezer compartment 88
Figure 3.12 Thermal resistance network for walls of refrigerator compartment 88
Figure 3.13 (a) Freezer back wall (b) Air box (c) Ducts for air inlet and outlet
from the refrigerator section (d) Air distributor for refrigerator
compartment
95
Figure 3.14 Evaporator and Defrost heater 96
Figure 3.15 Pressure Transducers 97
Figure 3.16 Pressure Meters 97
Figure 3.17 (a) Lutron temperature data logger (b) Pico temperature data
logger
99
Figure 3.18 Schematic diagram of inside and outside locations for
thermocouples to record temperatures
99
Figure 3.19 Inside surfaces at which temperature readings were recorded 100
Figure 3.20 Thermocouple settings in (a) freezer (b) refrigerator sections 101
xiv
Figure 3.21 Thermocouple settings in refrigerator with shelf 102
Figure 3.22 Sealing the refrigerator to prevent air leakage 102
Figure 3.23. Velocity measurement with handheld anemometer 103
Figure 3.24 (a) Power Analyzer (b) Clamp meter 104
Figure 3.25 Flow diagram for experiment 106
Figure 3.26 FeSEM image of (a) TiO2 and (b) SiO2 nanoparticles 107
Figure 3.27 Electronic balance 108
Figure 3.28 (a) Stirring hotplate (b) Ultrasonic homogenizer 108
Figure 3.29 Thermal conductivity and specific heat measuring apparatus 109
Figure 3.30 Brookfield LVDV 11 Viscometer 110
Figure 3.31 Robinair model 15601 vacuum pump 111
Figure 3.32 Schematic sketch for charging and evacuation 111
Figure 4.1 (a) Velocity contour on symmetry plane (b) Velocity vector on
symmetry plane
117
Figure 4.2 (a) Velocity contour (b) Velocity vector, on XZ plane in freezer
compartment at Y=1.25 m
118
Figure 4.3 (a) Velocity contour (b) Velocity vector, on XZ plane in freezer
compartment at Y=0.7 m
118
Figure 4.4 Velocity in freezer along a vertical line (x=0.23, z=0.425) 119
Figure 4.5 Velocity in refrigerator along a vertical line (x=0.23,z=0.425) 120
Figure 4.6 Velocity variations in freezer at the line(y = 1.1, 1.2, 1.3 m, z =
0.425 m)
121
Figure 4.7 Velocity variations in freezer at the line (y = 1.2 m, x = 0.23 m) 122
Figure 4.8 Velocity variations in refrigerator at the line(y = 0.7m, z= 0.425
m)
123
Figure 4.9 Velocity variations in refrigerator at the line (y = 0.7 m, x = 0.23
m)
123
Figure 4.10 (a) Velocity streamlines (b) Velocity volume rendering 124
Figure 4.11 Temperature contour on Z=0.54 m plane 125
Figure 4.12 Temperature contour on Y=1.152 m plane 126
Figure 4.13 Temperature contour on Y=0.45 m plane
127
Figure 4.14 Temperature variations in freezer at the line (x = 0.23 m, z =
0.425 m)
128
xv
Figure 4.15 Temperature variations in refrigerator at the line (x = 0.23 m, z =
0.425 m)
128
Figure 4.16 Temperature variations in freezer at line (y =1.152 m, z=0.425 m) 129
Figure 4.17 Temperature variations in freezer at the line (x = 0.23 m, y =
1.152 m)
130
Figure 4.18 Temperature variations in refrigerator at the line (y = 0.51 m, z =
0.425 m)
130
Figure 4.19 Temperature variations in refrigerator at the line (x = 0.23 m, y =
0.51 m)
131
Figure 4.20 Comparison of numerical and experimental temperature results at
symmetry plane of freezer (x=0.23 and z=0.425)
132
Figure 4.21 Comparison of numerical and experimental results at symmetry
plane of refrigerator (x=0.23 and z=0.425)
134
Figure 4.22 Points and lines used for Nusselt number calculation 135
Figure 4.23 Nusselt number variation along the length of the refrigerator 137
Figure 4.24 L-Shaped air distributor 138
Figure 4.25 Dimensions of L-shaped air distributor 139
Figure 4.26 Refrigerators with original and modified air distributors 140
Figure 4.27 Location of vertical line (dash line) in the refrigerator 141
Figure 4.28 Temperature variations along a vertical line at the center for
refrigerator
142
Figure 4.29 Al2O3 nanoparticles suspended in POE oil 144
Figure 4.30 TiO2 nanoparticles suspended in POE oil 144
Figure 4.31 SiO2 nanoparticles suspended in POE oil 145
Figure 4.32 Room temperature 146
Figure 4.33 Temperature variations on freezer floor and ceiling 147
Figure 4.34 Temperature variations on shelf of the freezer compartment 148
Figure 4.35 Temperature variations on two shelves of refrigerator
compartment
149
Figure 4.36 Temperature variations on vegetable shelf and back wall of
refrigerator compartment
150
Figure 4.37 Temperature variations on floor and ceiling of the freezer
compartment
151
xvi
Figure 4.38 Temperature variations on shelf and back wall of the freezer
compartment
152
Figure 4.39 Temperature variations on two shelves of refrigerator
compartment for 0.1% nanoparticles by volume added to POE oil
153
Figure 4.40 Temperature variations on vegetable shelf and back wall of
refrigerator compartment with the addition of 0.1% nanoparticles
by volume into POE oil
154
Figure 4.41 Comparison of power consumption over a period of one hour 155
Figure 4.42 Comparison of average power consumption for lubricant and
nanolubricants
156
Figure 4.43 Compressor discharge pressure for POE oil and POE oil mix with
0.05% nanoparticles
158
Figure 4.44 Compressor discharge pressure for POE oil and POE oil mix with
0.1% nanoparticles
158
Figure 4.45 Compressor suction pressure for POE oil and POE oil mix with
0.05% nanoparticles
159
Figure 4.46 Compressor suction pressure for POE oil and POE oil mix with
0.1% nanoparticles
159
Figure 4.47 Comparison of COP values 161
xvii
LIST OF SYMBOLS
g Acceleration due to gravity (m/s2)
h Specific enthalpy (kJ/kg K)
k turbulent kinetic energy
Lref Characteristic length of geometry. (m)
Ma Mach number
Nu Nusselt Number
p Pressure (Pa)
Q̇̇cond Conductive heat transfer rate (kW)
Q̇̇conv Convective heat transfer rate (kW)
QH Heat rejected from Condenser (kJ)
qH Heat rejected from condenser per unit mass (kJ/kg)
QL Heat absorbed in the evaporator (kJ)
qL Heat absorbed in evaporator per unit mass (kJ/kg)
Q̇̇rad Radiation heat transfer rate (kW)
R-11 Trichlorofluoromethane
R113 Trichlorotrifluoroethane.
R134a Refrigerant Tetrafluoroethane
R-744 Refrigerant grade Carbon Dioxide
Ra Rayleigh Number
RABS Thermal resistance of ABS plastic against heat conduction, (kW-1)
Rcond Thermal resistance of a layer against heat conduction, (kW-1)
RCV,i Thermal resistance by convection between the internal wall surfaces
and inside air (kW-1)
RCV,O Thermal resistance by convection between the outside air and
external wall surfaces (kW-1 )
RPU Thermal resistance of polyurethane foam against conduction, (kW-1)
RRAD,i Thermal resistance between the internal wall surfaces of the
refrigerator-freezer, (kW-1)
RRAD,O Thermal resistance between each external wall surface and the
neighbor surfaces, (kW-1)
RST Thermal resistance of steel against heat conduction, (kW-1)
Rtotal Total thermal resistance (m2 kW-1)
xviii
re, rp, and rw Displacement vectors
s Specific entropy
S_∅ the source term for the general property
SiO2 Silicon dioxide
T Temperature
T∞ Ambient temperature (K)
Tb Bulk air temperature
TiO2 Titanium dioxide
TNS Absolute temperature of the neighboring surface (K)
Ts Surface temperature (K)
u Velocity in x-direction
v Velocity in y-direction
w Velocity in z-direction
wc Work done by compressor per unit mass
α Thermal diffusivity (m2/s)
β Coefficient of volume expansion (K-1)
ε turbulent kinetic energy dissipation rate
μ and μt Viscosity and turbulent viscosity
ν Kinematic viscosity of air (m2/s)
ρ Density (kg/m3)
σ_k Constant
σ_ε Constant
ϕ For a general fluid property such as temperature or pressure
Cμ, Cε1, Cε2 Coefficients in approximated turbulent transport equations
xix
LIST OF ABBREVIATIONS
ABS Acrylonitrile Butadiene Styrene
AC Alternating Current
AHAM American Household Appliance Manufacturers
ANN Artificial Neural Network
ANSI American National Standards Institute
CFC Chlorofluorocarbons
CFCS CFCs
CFD Computational Fluid Dynamics
CNT Carbon Nano Tube
COP Coefficient of performance
CPU Central Processing Unit
CS Convection Scheme
CTAB Cetyltrimethyl Ammonium Bromide
DNS Direct Numerical Simulation
DO Discrete Ordinates
DOE Department of Energy
DTAB Dodecyltrimethylammonium Bromide
EFD Experimental Fluid Dynamics
EG Ethylene Glycol
EES Engineering Equation Solver
FDM Finite Difference Method
FEM Finite Element Method
FVM Finite Volume Method
GA Genetic Algorithm
GAMBIT Geometry and Model Building Intelligent Toolbox
GWP Global warming potential
GRS Graduate Research Scholarship
HC Hydrocarbon
HCFC Hydrochlorofluorocarbon
HCTAB Hexadecyltrimethylammonium bromide
HEC Higher Education Commission
xx
HFC Hydro fluorocarbon
HVAC Heating Ventilation and Air-conditioning
IPCC Intergovernmental Panel on Climate Change
ISO International Organization For Standardization
JIS Japanese Industrial Standards
KWH Kilowatt Huor
LBM Lattice Boltzmann method
LES Large-Eddy Simulation
MD Molecular dynamic
MNRO mineral based refrigeration oil
MO Mineral oil
NS Not Specified
ODP Ozone depletion potential
Pe Peclet number
PVP Polyvinyl Pyrrolidone
PISO Pressure-Implicit Split-Operator
PIV particle image velocimetry
POD Proper Orthogonal decomposition
POE Polyol ester oil
PRESTO PREssure STaggering Options
PU Polyurethane
PVD Physical vapor deposition
QUICK Quadratic Upwind Interpolation for Convective Kinetics
RNG Renormalization group
RANS Reynolds Averaged Navier-Stokes
SAE Society Of Automotive Engineers
SDBS Sodium Dodecyl Benzene Sulphonate
SDS Sodium Dodecyl Sulfate
SIMPLE Semi-Implicit Method for Pressure Linked Equation
SIMPLEC SIMPLE-Consistent
ST Steel
UNEP United Nations Environment Program
USA The United States of America
170
REFERENCES
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