Advances in Nanofluid Heat Transfer

Advances in Nanofluid Heat Transfer
Copyright
Dedication
Contents
List of contributors
Acknowledgment
1 Experimental correlations for Nusselt number and friction factor of nanofluids
1.1 Introduction
1.2 Preparation of nanofluids
1.2.1 One- step method
1.2.2 Two-step method
1.3 Experimental methods
1.3.1 Nusselt number
1.3.2 Friction factor
1.3.3 Nondimensional numbers
1.4 Nusselt number correlations for single-phase fluid
1.4.1 Laminar flow
1.4.2 Turbulent flow
1.5 Friction factor correlations for single-phase fluids
1.5.1 Laminar flow
1.5.2 Turbulent flow
1.6 Factors influencing the development of correlations
1.6.1 Nusselt number
1.6.2 Friction factor
1.7 Developed corrections for nanofliuids
1.7.1 Nusselt number
1.7.2 Friction factor
1.8 Conclusion
References
2 Preparation and evaluation of stable nanofluids for heat transfer application
Nomenclature
2.1 Introduction
2.2 Preparation
2.2.1 Two-step method
2.2.2 One-step method
2.3 Evaluation of nanofluid stability
2.3.1 Zeta potential analysis
2.3.2 Sedimentation and centrifugation methods
2.3.3 Spectral analysis method
2.3.4 3ω method
2.3.5 Electron microscopy and light scattering
2.3.6 pH measurement
2.4 Stabilization techniques
2.4.1 Physical method
2.4.1.1 Mechanical stirring
2.4.1.2 Ultrasonic vibration
2.4.1.3 Ball milling
2.4.2 Chemical stabilization
2.4.2.1 Surfactant
2.4.2.2 Surface modification
2.4.2.3 pH control of nanofluids
2.5 Stability mechanisms
2.5.1 Electrostatic stabilization
2.5.2 Steric stabilization
2.5.3 Electrosteric stabilization
2.6 Impact of nanofluid stability on thermophysical properties
2.6.1 Effects of stability on density
2.6.2 Effects of stability on viscosity
2.6.3 Effects of stability on specific heat capacity of nanofluids
2.6.4 Effects of stability on thermal conductivity
2.7 Conclusion
References
3 Synthesis, characterization, and measurement techniques for the thermophysical properties of nanofluids
3.1 Introduction
3.2 Synthesis of nanofluid
3.2.1 One-step method
3.2.1.1 Vapor deposition
3.2.1.2 Submerged arc method
3.2.1.3 Laser ablation method
3.2.1.4 Chemical method
3.2.2 Two-step method
3.2.2.1 Nanoparticles preparations
3.2.2.1.1 Milling process
3.2.2.1.2 Precipitation processes
3.2.2.1.3 Sol–gel method
3.2.2.2 Nanofluid preparation
3.2.2.2.1 Ultrasonication method
3.2.2.2.2 Magnetic stirring
3.3 Characterization of nanofluid
3.3.1 Zeta potential
3.3.2 Fourier-transform infrared spectroscopy
3.3.3 Transmission electron microscopy
3.3.4 X-ray crystallography
3.3.5 UV–Vis technique
3.4 Thermophysical properties measurement techniques of nanofluid
3.4.1 Thermal conductivity
3.4.1.1 Transient hot-wire method
3.4.1.2 3ω method
3.4.1.3 Thermal constants analyzer technique
3.4.2 Viscosity of nanofluids
3.4.3 Specific heat
3.4.4 Density
3.5 Conclusion
Nomenclature
References
4 Thermophysical and rheological properties of unitary and hybrid nanofluids
4.1 Introduction
4.2 Thermophysical properties
4.2.1 Thermal conductivity
4.2.2 Specific heat capacity
4.2.3 Density
4.2.4 Viscosity
4.3 Conclusion
Nomenclature
References
5 Comparison of physical properties enhancement in various heat transfer nanofluids by MXene
Nomenclature
5.1 Introduction
5.2 Methodology
5.2.1 Preparation of MXene nanomaterial as an additive to heat transfer nanofluids
5.2.2 Preparation of various heat transfer nanofluids by MXene
5.2.2.1 MXene-based new class of silicone oil heat transfer nanofluid
5.2.2.2 Olein palm oil with MXene as new class of heat transfer nanofluid
5.2.2.3 Soybean oil/MXene heat transfer nanofluid
5.2.2.4 Aqueous poly (ethylene) glycol (PEG)-based MXene nanofluid
5.2.2.5 Aqueous ionic liquid/MXene nanofluid
5.2.2.6 Palm oil methyl ester-based MXene heat transfer nanofluid
5.2.2.7 Water-based MXene nanofluid
5.2.2.8 Diethylene glycol and ionic liquid mixture-based MXene nanofluid
5.2.2.9 Ethylene glycol (EG)-based MXene heat transfer nanofluid
5.2.3 Physical properties
5.2.3.1 Thermal conductivity measurement
5.2.3.2 Viscosity measurement of various heat transfer nanofluids by MXene
5.2.3.3 Thermal stability test using thermal stability analysis
5.3 Results and discussion
5.3.1 Thermal conductivity of various heat transfer nanofluids by MXene
5.3.2 Viscosity analysis of various heat transfer nanofluids by MXene
5.3.3 Thermal Stability of various heat transfer nanofluids by MXene
5.4 Conclusion
Acknowledgment
References
6 Numerical modeling of nanofluids’ flow and heat transfer
Nomenclature
6.1 Introduction
6.2 Heat transfer enhancement mechanism of nanofluid
6.2.1 Particle–particle interactions
6.2.2 Particle–liquid interactions
6.2.3 External forces on particles
6.3 Thermophysical properties of nanofluids
6.3.1 Thermal conductivity
6.3.2 Viscosity
6.3.3 Specific heat
6.3.4 Density
6.4 Mathematical models to simulate nanofluids
6.4.1 Single-phase model
6.4.1.1 Homogenous model
6.4.1.2 Thermal dispersion model
6.4.1.3 Buongiorno model
6.4.2 Multiphase Eulerian–Eulerian model
6.4.2.1 Mixture model
6.4.3 Eulerian model
6.4.4 Volume of fluid model
6.4.5 Multiphase Eulerian–Lagrangian model
6.5 Numerical techniques to simulate nanofluid
6.5.1 Macroscale techniques
6.5.1.1 Finite difference method
6.5.1.2 Finite volume method
6.5.1.3 Finite element method
6.5.1.4 Control volume finite element method
6.5.2 Microscale techniques
6.5.3 Mesoscale techniques
6.5.3.1 Lattice Boltzmann method
6.5.3.2 Dissipative particle dynamics
6.6 Conclusion
References
7 Recent advances in machine learning research for nanofluid heat transfer in renewable energy
Nomenclature
7.1 Introduction
7.1.1 Data collection and representation
7.1.2 Model selection and validation
7.1.3 Model optimization
7.2 Machine learning techniques
7.2.1 Multilayer perception artificial neural network
7.2.2 Adaptive neuro fuzzy inference system
7.2.3 Radial basis function network
7.2.4 Least square support vector machine
7.3 Nanofluid heat transfer and machine learning
7.4 Machine learning of nanofluids’ thermophysical properties and thermal performance
7.5 Challenges and future opportunities
7.6 Conclusion
References
8 Heat transfer enhancement with nanofluids in automotive
8.1 Historical background
8.1.1 Applications of computational fluid dynamics in nanofluids studies
8.1.2 Applications of nanofluid in automotive system
8.2 Physical properties
8.2.1 Thermal conductivity of nanofluids
8.2.2 Viscosity of nanofluids
8.3 The fundamental relation for computational fluid dynamics model
8.3.1 Macroscopic models
8.3.1.1 Single-phase models
8.3.1.2 Two-phase models
8.3.1.3 Control equation
8.3.2 Lattice Boltzmann method
8.4 Heat transfer enhancement with nanofluids in automotive
8.4.1 Utilization in engine coolant
8.4.1.1 Determination of nanofluid parameters
8.4.1.1.1 Thermal conductivity
8.4.1.1.2 Density, specific heat capacity, and viscosity
8.4.1.2 Computational fluid dynamics of water jackets
8.4.1.2.1 Geometric model and mesh generation
8.4.1.2.2 Computational models and boundary conditions
8.4.1.2.3 Computational fluid dynamics calculation and result analysis
8.4.2 Utilization in refrigerant of automotive air conditioning
8.4.2.1 Determination of nanofluid parameters
8.4.2.1.1 Thermal conductivity
8.4.2.1.2 Viscosity
8.4.2.1.3 Density and specific heat capacity
8.4.2.2 The Boltzmann model of nanofluid
8.4.2.3 Computational fluid dynamics of nanorefrigerant based on lattice Boltzmann method
8.4.2.3.1 The physical model
8.4.2.3.2 Numerical simulation results
Nomenclature
Problems
References
9 The use of nanofluids in solar desalination of saline water resources as antibacterial agents
Nomenclature
9.1 Harvesting solar energy by nanofluids
9.1.1 Introduction
9.1.2 Solar steam generation experiments by the nanofluids
9.1.3 Effective parameters on light harvesting capability of the nanofluids
9.1.3.1 Concentration of NFs
9.1.3.2 Stability and optical properties of NFs
9.1.3.3 Effect of solar illumination intensity
9.1.3.4 The effect of size of NPs
9.1.4 Effect of NFs on heat localization
9.1.5 Comparison of economic performance of NFs
9.1.6 Photocatalytic experiments by NFs
9.1.6.1 Kinetic of photocatalytic activity of NFs
9.1.6.2 The photocatalytic mineralization by NFs
9.2 Antibacterial activity of some NFs
9.2.1 Introduction
9.2.2 Effect of NFs on prevention of Escherichia coli proliferation
9.2.3 Mechanisms of antibacterial activity of NFs
9.2.4 Effective parameters on antibacterial activity of NFs
9.2.4.1 Effect of concentration of NPs
9.2.4.2 Effect of size of NPs
9.2.4.3 Effect of the presence of a stabilizer
9.2.4.4 Effect of pH, temperature, and pressure
9.2.5 Rate of antibacterial activity of NPs
9.2.6 The effect of NFs on the bacteria morphology
9.3 Conclusion
References
10 Application of nanofluids in combustion engines with focusing on improving heat transfer process
Nomenclature
10.1 Introduction
10.1.1 History of heat transfer in combustion engines
10.2 Parameters affecting the heat transfer of combustion engines
10.2.1 Engine size and dimension
10.2.2 Engine speed
10.2.3 Engine load
10.2.4 Inlet air temperature
10.2.5 Coolant temperature
10.2.6 Engine materials
10.2.7 Friction coefficient
10.2.8 Heat transfer coefficient
10.2.9 Conduction heat transfer coefficient
10.3 Type of lubricants
10.3.1 Lubrication of combustion engines
10.3.1.1 Single-grade engine oils
10.3.1.2 Multigrade engine oils
10.3.2 Basic engine oils and challenges
10.3.2.1 Engine oils additives to improve lubrication process
10.4 Using nanoparticles in internal combustion engines
10.4.1 Adding nanoparticles to engine oils (nano oil)
10.4.2 Adding nanoparticles to fuel (nanofuel)
10.4.3 Effects of nanoparticles additives on friction
10.4.4 Effects of nanoparticles additives on engines power
10.4.5 Effects of nanoparticle additives on the cooling cycle of combustion engines
10.5 Conclusion on threats and opportunities of applying nanoscience in combustion engines
References
11 Applications of nanofluids in solar energy collectors focusing on solar stills
Nomenclature
Abbreviation
Latin letters
11.1 History of solar energy collectors
11.2 Classification of Solar energy collectors
11.2.1 Classification based on solar energy application
11.2.2 Classification based on concentration level ability
11.2.3 Classification based on tracking or nontracking solar collectors
11.2.4 Passive and active solar systems
11.2.4.1 Benefits and drawbacks of active solar systems
11.2.4.2 Benefits and drawbacks of passive solar systems
11.2.5 Main types of solar collectors
11.2.5.1 Flat plate solar collectors
11.2.5.2 Evacuated tube collectors
11.2.5.3 Concentrating collectors
11.3 Effective parameters on solar still performance
11.3.1 Various design parameters
11.3.2 Climatic parameters
11.4 Application of nanofluids in solar stills
11.4.1 Solar stills without nanofluids
11.4.2 Solar stills with nanofluids
11.5 Most applied nanoparticles in solar stills
11.6 Challenges of nanofluid application in solar collectors
References
12 Utilization of nanofluids (mono and hybrid) in parabolic trough solar collector: a comparative analysis
12.1 Introduction
12.2 System description and thermodynamic modeling
12.2.1 Energy and exergy analysis of parabolic trough collector
12.2.2 Heat transfer analysis
12.2.3 Hybrid and mono nanofluids specifications
12.2.4 Performance evaluation criteria
12.2.5 Validation of parabolic trough collector model
12.3 Results and discussion
12.4 Conclusion
Nomenclature
Greek Letters
Subscripts and superscripts
Abbreviations
Acknowledgment
References
13 Electronics thermal management applying heat pipes and pulsating heat pipes
13.1 Introduction
13.2 Design parameters
13.3 Heat pipes
13.3.1 Heat pipe designs
13.3.2 Application of heat pipes
13.4 Pulsating heat pipes
13.4.1 Application of pulsating heat pipes
13.5 Nanofluids capabilities and models
13.6 Nanofluids in heat transfer systems: pros and cons
13.6.1 Types of nanoparticles used in nanofluids
13.6.2 Nanofluid preparation
13.6.3 Nanofluid stability strategies
13.6.4 Nanofluid stability mechanisms
13.6.5 Nanofluid stability evaluation
13.6.6 Nanofluids after operation cycles
13.6.7 Nanofluids applications
13.7 Concluding remarks
Nomenclature
References
14 Role of nanofluids in microchannel heat sinks
Nomenclature
Greek Letters
Subscripts
14.1 Introduction
14.2 Key characteristics of nanofluids
14.2.1 Thermophysical properties
14.2.2 Effect of nanoparticle concentration
14.2.3 Effect of nanoparticle size
14.2.4 Effect of nanoparticle shape
14.2.5 Effect of nanoparticle thermal conductivity
14.2.6 Effect of base fluid
14.2.7 Effect of nanofluid temperature
14.2.8 Effect of preparation technique
14.2.9 Summary
14.3 Flow of nanofluids in microchannels
14.4 Thermal performance of nanofluids in microchannels
14.5 Entropy analysis of nanofluid-based microchannel heat sinks
14.6 Geometry effect of microchannels
14.6.1 Changing shape of channels
14.6.2 Adding geometrical inclusions/exclusions in the cross section
14.6.3 Varying path of the fluid
14.7 Future advances and challenges
14.8 Conclusions
References
15 Nanofluids for enhanced performance of building thermal energy systems
15.1 Introduction
15.2 Overview of domain knowledge related to nanofluids
15.3 Role of nanofluids in efficiency enhancement of building energy systems
15.3.1 Nanofluids for performance enhancement of photovoltaic thermal systems
15.3.2 Nanofluids for performance enhancement of heating, ventilation, and air conditioning systems
15.3.3 Nanofluids for performance enhancement of thermal storage systems
15.4 Barriers
15.5 Conclusions
References
16 Ionic nanofluids: preparation, characteristics, heat transfer mechanism, and thermal applications
Abbreviations
16.1 Introduction
16.2 Preparation methods
16.3 Characteristics
16.3.1 Thermal conductivity
16.3.2 Viscosity
16.3.3 Specific heat
16.3.4 Density
16.4 Heat transfer mechanism
16.5 Thermal applications
16.6 Future prospects and challenges
16.7 Conclusions
References
17 Hybrid nanofluids towards advancement in nanofluids for heat sink
Nomenclature
17.1 Introduction
17.2 Preparation of hybrid nanofluids
17.2.1 Two-step method
17.2.2 One-step method
17.3 Various hybrid nanofluids used in different heat sinks
17.3.1 Thermal management of electronics using other fluids
17.4 Conclusion
References
Index