Advances in Nanofluid Heat Transfer

By Hafiz Muhammad Ali

Advances in Nanofluid Heat Transfer covers the broad definitions, brief history, preparation techniques, thermophysical properties, heat transfer characteristics, and emerging applications of hybrid nanofluids. Starting with the basics, this book advances step-by-step toward advanced topics, with mathematical models, schematic diagrams and discussions of the experimental work of leading researchers. By introducing readers to new techniques, this book helps readers resolve existing problems and implement nanofluids in innovative new applications.

This book provides detailed coverage of stability and reliable measurement techniques for nanofluid properties, as well as different kinds of base fluids. Providing a clear understanding of what happens at the nanoscale, the book is written to be used by engineers in industry as well as researchers and graduate students.

• Covers new applications of nanofluids, along with key challenges encountered in the commercialization of this technology
• Highlights new nanofluid properties and associated numerical modeling methods 
• Addresses the very latest topics in nanofluids sciences, such as ionic nanofluids

• Language: English
• Publisher: Elsevier Science
• Release date: May 28, 2022
• ISBN: 9780323886420

Book preview

Front Cover for Advances in Nanofluid Heat Transfer - 1st edition - by Hafiz Muhammad Ali

Advances in Nanofluid Heat Transfer

Edited by

Hafiz Muhammad Ali

Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS), King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Table of Contents

Cover image

Title page

Copyright

Dedication

List of contributors

Acknowledgment

Chapter 1. Experimental correlations for Nusselt number and friction factor of nanofluids

Abstract

1.1 Introduction

1.2 Preparation of nanofluids

1.3 Experimental methods

1.4 Nusselt number correlations for single-phase fluid

1.5 Friction factor correlations for single-phase fluids

1.6 Factors influencing the development of correlations

1.7 Developed corrections for nanofliuids

1.8 Conclusion

References

Chapter 2. Preparation and evaluation of stable nanofluids for heat transfer application

Abstract

Nomenclature

2.1 Introduction

2.2 Preparation

2.3 Evaluation of nanofluid stability

2.4 Stabilization techniques

2.5 Stability mechanisms

2.6 Impact of nanofluid stability on thermophysical properties

2.7 Conclusion

References

Chapter 3. Synthesis, characterization, and measurement techniques for the thermophysical properties of nanofluids

Abstract

3.1 Introduction

3.2 Synthesis of nanofluid

3.3 Characterization of nanofluid

3.4 Thermophysical properties measurement techniques of nanofluid

3.5 Conclusion

Nomenclature

References

Chapter 4. Thermophysical and rheological properties of unitary and hybrid nanofluids

Abstract

4.1 Introduction

4.2 Thermophysical properties

4.3 Conclusion

Nomenclature

References

Chapter 5. Comparison of physical properties enhancement in various heat transfer nanofluids by MXene

Abstract

Nomenclature

5.1 Introduction

5.2 Methodology

5.3 Results and discussion

5.4 Conclusion

Acknowledgment

References

Chapter 6. Numerical modeling of nanofluids’ flow and heat transfer

Abstract

Nomenclature

6.1 Introduction

6.2 Heat transfer enhancement mechanism of nanofluid

6.3 Thermophysical properties of nanofluids

6.4 Mathematical models to simulate nanofluids

6.5 Numerical techniques to simulate nanofluid

6.6 Conclusion

References

Chapter 7. Recent advances in machine learning research for nanofluid heat transfer in renewable energy

Abstract

Nomenclature

7.1 Introduction

7.2 Machine learning techniques

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

Chapter 8. Heat transfer enhancement with nanofluids in automotive

Abstract

8.1 Historical background

8.2 Physical properties

8.3 The fundamental relation for computational fluid dynamics model

8.4 Heat transfer enhancement with nanofluids in automotive

Nomenclature

Problems

References

Chapter 9. The use of nanofluids in solar desalination of saline water resources as antibacterial agents

Abstract

Nomenclature

9.1 Harvesting solar energy by nanofluids

9.2 Antibacterial activity of some NFs

9.3 Conclusion

References

Chapter 10. Application of nanofluids in combustion engines with focusing on improving heat transfer process

Abstract

Nomenclature

10.1 Introduction

10.2 Parameters affecting the heat transfer of combustion engines

10.3 Type of lubricants

10.4 Using nanoparticles in internal combustion engines

10.5 Conclusion on threats and opportunities of applying nanoscience in combustion engines

References

Chapter 11. Applications of nanofluids in solar energy collectors focusing on solar stills

Abstract

Nomenclature

11.1 History of solar energy collectors

11.2 Classification of Solar energy collectors

11.3 Effective parameters on solar still performance

11.4 Application of nanofluids in solar stills

11.5 Most applied nanoparticles in solar stills

11.6 Challenges of nanofluid application in solar collectors

References

Chapter 12. Utilization of nanofluids (mono and hybrid) in parabolic trough solar collector: a comparative analysis

Abstract

12.1 Introduction

12.2 System description and thermodynamic modeling

12.3 Results and discussion

12.4 Conclusion

Nomenclature

Acknowledgment

References

Chapter 13. Electronics thermal management applying heat pipes and pulsating heat pipes

Abstract

13.1 Introduction

13.2 Design parameters

13.3 Heat pipes

13.4 Pulsating heat pipes

13.5 Nanofluids capabilities and models

13.6 Nanofluids in heat transfer systems: pros and cons

13.7 Concluding remarks

Nomenclature

References

Chapter 14. Role of nanofluids in microchannel heat sinks

Abstract

Nomenclature

14.1 Introduction

14.2 Key characteristics of nanofluids

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

14.7 Future advances and challenges

14.8 Conclusions

References

Chapter 15. Nanofluids for enhanced performance of building thermal energy systems

Abstract

15.1 Introduction

15.2 Overview of domain knowledge related to nanofluids

15.3 Role of nanofluids in efficiency enhancement of building energy systems

15.4 Barriers

15.5 Conclusions

References

Chapter 16. Ionic nanofluids: preparation, characteristics, heat transfer mechanism, and thermal applications

Abstract

Abbreviations

16.1 Introduction

16.2 Preparation methods

16.3 Characteristics

16.4 Heat transfer mechanism

16.5 Thermal applications

16.6 Future prospects and challenges

16.7 Conclusions

References

Chapter 17. Hybrid nanofluids towards advancement in nanofluids for heat sink

Abstract

Nomenclature

17.1 Introduction

17.2 Preparation of hybrid nanofluids

17.3 Various hybrid nanofluids used in different heat sinks

17.4 Conclusion

References

Index

Copyright

Elsevier

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This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein.

ISBN: 978-0-323-88656-7

For Information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Matthew Deans

Acquisitions Editor: Brian Guerin

Editorial Project Manager: Mariana L. Kuhl

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Cover Designer: Christian J. Bilbow

Typeset by MPS Limited, Chennai, India

Dedication

Hafiz Muhammad Ali dedicates this work to his beloved sons Muhammad Ibraheem Ali, Muhammad Ismaeel Ali, and Muhammad Ishaac Ali.

List of contributors

Naseem Abbas,     Department of Mechanical Engineering, Sejong University, Seoul, South Korea

Muhammad Abdullah,     Mechanical Engineering Department, Quaid-E-Azam College of Engineering and Technology, Sahiwal, Pakistan

Hafiz Muhammad Ali

Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS), King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Tehmina Ambreen,     School of Mechanical Engineering, Kyungpook National University, Bukgu Daegu, South Korea

Navid Aslfattahi,     Department of Fluid Mechanics and Thermodynamics, Faculty of Mechanical Engineering, Czech Technical University in Prague, Prague, Czech Republic

Awais Awan,     Mechanical Engineering Department, Quaid-E-Azam College of Engineering and Technology, Sahiwal, Pakistan

Muhammad Bilal Awan,     Department of Mechanical Engineering, University of Central Punjab, Lahore, Pakistan

Mohsin Ali Badshah,     Department of Chemical Engineering and Materials Science, The Henry Samueli School of Engineering, University of California, Irvine, CA, United States

Taha Baig

Mechanical Engineering Department, University of Wah, Wah Cantonment, Pakistan

Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan

Ali Celen,     Department of Mechanical Engineering, Faculty of Engineering, Erzincan Binali Yıldırım University, Erzincan, Turkey

Hailin Cen,     School of Mechanical and Automotive Engineering, South China University of Technology, GuangZhou, P.R. China

Saeed Esfandeh

Department of Mechanical Engineering, Jundi-Shapur University of Technology, Dezful, Iran

Department of Mechanical Engineering, Imam Hossein University, Tehran, Iran

Juncal Estella,     NAITEC—Centro Tecnológico en Automoción y Mecatrónica, Pamplona, Spain

Rong Fu,     Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, P.R. China

Mohammad Mustafa Ghafurian

Department of Mechanical Engineering, Bozorgmehr University of Qaenat, Qaen, Iran

Center for Nanotechnology in Renewable Energies, Ferdowsi University of Mashhad, Mashhad, Iran

Elaheh K. Goharshadi,     Department of Chemistry, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran

Faisal Hassan,     Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan

Mohammad Hemmat Esfe,     Department of Mechanical Engineering, Imam Hossein University, Tehran, Iran

Kuo Huang,     Faculty of Engineering, The University of Nottingham, Nottingham, United Kingdom

Asad Iqbal,     Mechanical Engineering Department, Quaid-E-Azam College of Engineering and Technology, Sahiwal, Pakistan

Ali Turab Jafry,     Faculty of Mechanical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan

Furqan Jamil,     Mechanical Engineering Department, University of Wah, Wah Cantonment, Pakistan

Kumaran Kadirgama

Faculty of Mechanical Engineering, Universiti Malaysia Pahang, Pekan, Malaysia

Automotive Engineering Centre, Universiti Malaysia Pahang, Pekan, Malaysia

Mohammad Hassan Kamyab

Department of Mechanical Engineering, Imam Hossein University, Tehran, Iran

Department of Mechanical Engineering, University of Kashan, Kashan, Iran

Muhammad Sajid Khan

Institute of Energy and Power Engineering, College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, P.R. China

Department of Mechanical Engineering, Mirpur University of Science & Technology (MUST), Mirpur, AJK, Pakistan

Shahab Khushnood,     Mechanical Engineering Department, University of Wah, Wah Cantonment, Pakistan

Amit Kumar,     Mechanical Engineering Department, Institute of Engineering & Technology, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India

Zeyu Liu

Marine Engineering College, Dalian Maritime University, Dalian, Liaoning, P.R. China

Faculty of Engineering, The University of Nottingham, Nottingham, Nottinghamshire, United Kingdom

Omid Mahian

Center for Nanotechnology in Renewable Energies, Ferdowsi University of Mashhad, Mashhad, Iran

School of Chemical Engineering and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, P.R. China

Sohail Malik,     Faculty of Mechanical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan

Jesús Esarte San Martin,     NAITEC—Centro Tecnológico en Automoción y Mecatrónica, Pamplona, Spain

Roya Mehrkhah,     Department of Chemistry, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran

Hatice Mercan,     Department of Mechatronics Engineering, Yildiz Technical University, Istanbul, Turkey

Hamid Niazmand,     Center for Nanotechnology in Renewable Energies, Ferdowsi University of Mashhad, Mashhad, Iran

Cheol Woo Park,     School of Mechanical Engineering, Kyungpook National University, Bukgu Daegu, South Korea

E. Venkata Ramana,     Department of Physics, University of Aveiro, Aveiro, Portugal

Waseem Raza,     Department of Mechanical Engineering, Jeju National University, Jeju, South Korea

Roger R. Riehl,     GamaTech Thermal Solutions, São José dos Campos, Brazil

Hafiz Muhammad Rizwan,     Faculty of Mechanical Engineering, GIK Institute of Engineering Sciences and Technology, Topi, Pakistan

Zafar Said

U.S.-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), Islamabad, Pakistan

Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah, United Arab Emirates

R. Saidur

Research Center for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University, Selangor Darul Ehsan, Malaysia

Department of Engineering, Lancaster University, Lancaster, United Kingdom

Uzair Sajjad,     Department of Energy and Refrigerating Air-Conditioning Engineering, National Taipei University of Technology, Taipei, Taiwan

Arslan Saleem,     School of Engineering, Cardiff University, Cardiff, Wales, United Kingdom

M. Samykano,     Faculty of Mechanical Engineering, Universiti Malaysia Pahang, Pekan, Malaysia

Lingenthiran Samylingam,     Research Center for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University, Selangor Darul Ehsan, Malaysia

Tayyab Raza Shah,     College of Engineering, Peking University, Beijing, P.R. China

Muhammad Shehryar,     Mechanical Engineering Department, University of Engineering and Technology, Taxila, Pakistan

Maham Sohail,     Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah, United Arab Emirates

Antonio C.M. Sousa,     Department of Mechanical Engineering, Prince Mohammad Bin Fahd University, Al-Khobar, Saudi Arabia

L. Syam Sundar,     Department of Mechanical Engineering, Prince Mohammad Bin Fahd University, Al-Khobar, Saudi Arabia

Tolga Taner,     Department of Motor Vehicles and Transportation Technology, Aksaray University, Aksaray, Turkey

Arun Kumar Tiwari,     Mechanical Engineering Department, Institute of Engineering and Technology, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India

Chi-Chuan Wang,     Department of Mechanical Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

Xihui Wang,     School of Mechanical and Automotive Engineering, South China University of Technology, GuangZhou, P.R. China

Mi Yan,     Institute of Energy and Power Engineering, College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, P.R. China

Yan Yuying,     Faculty of Engineering, The University of Nottingham, Nottingham, Nottinghamshire, United Kingdom

Chao Zhou,     College of Engineering, Peking University, Beijing, P.R. China

Acknowledgment

Hafiz Muhammad Ali acknowledges the support received from the King Fahd University of Petroleum and Minerals, Dhahran, 31261, Kingdom of Saudi Arabia.

Chapter 1

Experimental correlations for Nusselt number and friction factor of nanofluids

L. Syam Sundar¹, E. Venkata Ramana², Hafiz Muhammad Ali³, ⁴ and Antonio C.M. Sousa¹,    ¹Department of Mechanical Engineering, Prince Mohammad Bin Fahd University, Al-Khobar, Saudi Arabia,    ²Department of Physics, University of Aveiro, Aveiro, Portugal,    ³Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia,    ⁴Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS), King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Abstract

The recent developments in nanotechnology have generated a lot of interest for researchers, scientists and engineers. By using nanotechnology, the preparation of high thermal conductivity fluids called nanofluids is possible and they may be used in heat exchange devices. The nanofluids are dilutions of nanometer sized particles in single-phase fluids of water, oil, and ethylene glycol, etc. The nanofluids offer the great advantage of heat transfer over the single-phase fluids. The lower dispersion of nanoparticles in single-phase fluids can significantly improve the thermal transport properties. This chapter addresses the available experimental correlations for Nusselt number and friction factor while the nanofluids flow in a tube under laminar and turbulent flow conditions. The Nusselt number and friction factor correlations are important while the nanofluids flow in a tube because of not valid of the available single-phase fluids correlations. Hence, this chapter gives the developed Nusselt number and friction factor correlation of various nanofluids and also factors affecting the development of correlations. The wide range of literature related to the experimental correlations in the laminar and turbulent flow is discussed.

Keywords

Heat transfer coefficient; friction factor; Nusselt number; correlations

1.1 Introduction

Heat transfer augmentation is necessary for each and every industry. Heat transfer augmentation can be achieved by using active techniques and passive techniques. An active method of heat transfer enhancement is possible by using mechanical stirring, surface vibrations, electrostatic fields, jet impingement, spray, etc. [1–3]. To achieve the active method of heat transfer enhancement it needs extra devices, which means that it requires extra power. So, this type of heat transfer enhancement is not advisable, because it needs more power. A passive method of heat transfer enhancement is possible by providing surface texturing [4], extended surfaces [5], and flow turbulence [6,7] and adding additives to the fluid [8,9]. Just adding additives (metal or nonmetal particles) to the base fluid may get heat transfer enhancement, since the additives have more thermal conductivity than the fluids. This type of heat transfer enhancement does not require any extra accessories. The initial research work was related to the dispersion of micron-size particles in the fluid and it gives the enhanced heat transfer but faced the problem of particle agglomeration in the base fluid [10].

Due to the development in nanotechnology, the microsize particles are further reduced to nanosize . The dilution of nanosized particles with some treatment on the particle surface can avoid particle agglomeration in the base fluid. Diluted nanosized particles in the base fluid are called nanofluid, and were first invented by Choi [11]. Improved thermal conductivity was observed for nanofluids compared with the base fluid. The problem of particle clogging, sedimentation, and erosion is minimized with the use of nanofluids while they flow in a tube or minichannel.

Discussion has been going on for more than 20 years but the mechanism behind the improvement of heat transfer for these nanofluids is still doubtful [12–16]. However, these nanofluids possess augmented thermal conductivity, which is the key parameter for heat transfer intensification. Many theories have been available in the open literature to know about the thermal conductivity augmentation of these nanofluids [17,18].

The diluted nanoparticles Brownian motion, liquid–particle interface, microconvection play a significant vital role in thermal conductivity augmentation [19]. The influence of Brownian motion of nanoparticles causes the heat transfer augmentation of nanofluids [20]. Based on the static model of Maxwell, particle conduction is the mode of heat transfer augmentation, but based on the dynamic model, the particle–particle and particle–liquid interactions is the mode for heat transfer enhancement.

When using these nanofluids in heat exchanger devices, heat transfer is important. Several studies are available in the literature for heat transfer characteristics of various nanofluids. Since the single-phase correlations for Nusselt number and friction factor are not valid for nanofluids, the authors have developed their own correlations based on the use of the nanofluids. Until now there is no standard Nusselt number and friction factor correlation applicable for all type of nanofluids. Developing a single correlation for all the nanofluids is difficult because the heat transfer augmentation depends on several parameters, such as particle size, shape, concentration, geometry, and operating conditions.

This chapter covers the Nusselt number and friction correlations for different nanofluids in various geometrical and operating conditions. These developed equations are helpful to identify the necessity of developing another kind of equation for forthcoming research.

1.2 Preparation of nanofluids

The preparation of nanofluids is necessary before they are used in any equipment. There are two methods to prepare the nanofluids: (1) one-step method and (2) two-step method. Stable nanofluids are important for heat transfer applications. The nanofluids are stable with the use of surfactants. If the nanofluids are not stable, there may be a clogging of larger particles in pumps, pipes, and also fouling in the tubes may occur using these nanofluids in thermal equipments.

1.2.1 One- step method

The one-step method of nanofluids is that the nanoparticles are directly made and diluted in the base fluid. This method is advantageous because the nanoparticles cannot react with oxygen in the atmosphere. Most of the research has been used this one-step method of nanofluid preparation technique. The accessories like dryers and storage are not required for this method. This method also has the advantage of less nanoparticles aggregation in the base fluid, resulting in an increase in nanofluid stability. The laser ablation method and submerged arc nanoparticles synthesis system are the commonly used methods for the preparation of nanofluids by the one-step method.

1.2.2 Two-step method

In the two-step method of nanofluids the nanoparticles, nanotubes, and other nanomaterials are primarily prepared in the form of dry powers by using chemical, physical, and mechanical methods. The prepared nanoparticles are dispersed in the base fluid. This method is the most economical method for the preparation of nanofluids. Nanoparticle agglomeration and sedimentation are the main difficulties in this type of nanofluids preparation. Ultrasonication or the stirring process will decrease the nanoparticle sedimentation in the base fluid. Because of the van der Waals forces, the nanoparticles aggregate very easily in the base fluids. By using the surfactant in the base fluid nanoparticle sedimentation is avoided. Nanoparticle agglomeration will affect the thermophysical properties of the nanofluid. However, this method of nanofluids preparation is most economical and also suitable for large-scale nanofluids preparation. For preparing the oxides-based nanofluids, this method is more suitable. Commonly used methods for the synthesis of nanoparticles are the direct synthesis method, sol–gel method, and chemical precipitation method. Commonly used surfactants are gum Arabic, SDBS, chitosan, polyvinylpyrolidine, and cetyl trimethyl ammonium bromide.

One can use either the one-step method or two-step method for the preparation of nanofluids, but the nanofluids should be stable to avoid the particle agglomeration in the tubes and channel. Therefore for nanofluid application in engineering systems new technology is required to increase the stability of nanofluid.

1.3 Experimental methods

The experimental equations to evaluate the heat transfer coefficient, Nusselt number, and friction factor are given below. Sundar et al. [21] experimental schematic diagram of forced convection equipment is shown in Fig. 1.1.

Figure 1.1 Schematic diagram of forced convection apparatus [21].

1.3.1 Nusselt number

The Newton’s law of cooling equation is used to estimate the heat transfer coefficient.

a. Heat supplied to the test tube,

(1.1)

b. Heat absorbed by the fluid,

(1.2)

c. Heat transfer coefficient,

(1.3)

Where,

d. Nusselt number,

(1.4)

e. Prandtl number,

(1.5)

1.3.2 Friction factor

The fluid pressure drop for both water and nanofluids between inlet and outlet is measured through the pressure gauge. When the fluid is flowing inside the tube, the resistance between the fluid and tube wall provides the pressure drop.

f. Pressure drop,

(1.6)

The terms in Eq. (1.6) are density of the fluid (kg/m³), acceleration due to gravity (m/s²), and manometric fluid height (m). The manometric fluid height is converted into equivalent working fluid height for pressure drop calculations.

The pumping power of water and nanofluids can be given as:

g. Pumping power

(1.7)

From the pressure drop, the friction factor of water and nanofluid is estimated.

h. Friction factor,

(1.8)

where

1.3.3 Nondimensional numbers

The nondimensional numbers such as Reynolds number, Nusselt number, Prandtl number, and Peclet number are generally used to develop correlations.

i. Reynolds number,

(1.9)

j. Prandtl number,

(1.10)

k. Nusselt number,

(1.11)

l. Peclet number,

(1.12)

The thermal diffusivity is:

1.4 Nusselt number correlations for single-phase fluid

Different correlations are available to estimate the Nusselt number for the case of single-phase fluids flow in a tube. The fluid flow may be defined as laminar and turbulent flow. When the Reynolds number is less than or equal to 2300, the flow is called laminar flow; when the Reynolds number is greater than 2300, the flow is called as turbulent flow. The generally used correlations are compiled below.

1.4.1 Laminar flow

a. Shah [22]:

(1.13)

b. Churchill and Ugasi [23]

(1.14)

=Laminar Nusselt number

=Nusselt number at critical Reynolds number of 2200

=Turbulent Nusselt number

c. Tam and Ghajar [24]

(1.15)

d. Sider-Tate [25]

(1.16)

1.4.2 Turbulent flow

e. Dittus-Boelter [26]

(1.17)

f. Gnelinski’s [27]

(1.18)

Another Gnelinski [27] equation is,

(1.19)

g. Petukhov [28]

(1.20)

h. Notter-Sleicher [29]

(1.21)

1.5 Friction factor correlations for single-phase fluids

The friction factor is estimated based on the pressure drop, and velocity of the fluid. Various correlations are available to predict the friction factor for the case of single-phase fluid flow in a tube. The fluid flow may be defined as laminar or turbulent flow.

1.5.1 Laminar flow

a. Hagen-Poiseuille [30]

(1.22)

1.5.2 Turbulent flow

a. Moody [31]

(1.23)

b. Blasius [32]

(1.24)

c. Petukhov [28]

(1.25)

d. Filonenko [33] for smooth tubes

(1.26)

1.6 Factors influencing the development of correlations

1.6.1 Nusselt number

The Nusselt number of nanofluid is a function of Reynolds number, Prandtl number, and particle volume loadings.

(1.27a)

By releasing the functionality limit, the Eq. (1.27a) becomes Eq. (1.27b)

(1.27b)

where C is a constant; a, b, and c are the exponents.

1.6.2 Friction factor

The friction factor is a function of Reynolds number and particle volume loadings.

(1.28a)

By releasing the function, the Eq. (1.28a) becomes Eq. (1.28b)

(1.28b)

where C is a constant; a and b are exponents.

1.7 Developed corrections for nanofliuids

1.7.1 Nusselt number

Based on the experimental data of nanofluids, many researchers have developed Nusselt number correlations. Fig. 1.2 indicates the experimental Nusselt number of Al2O3/water at different Reynolds numbers and particle loadings [21]. The Nusselt number of 0.5% volume concentration of Al2O3/water nanofluid is enhanced by 22.76% and 30.30% at Reynolds number of 10,000 and 22,000, compared with water data, respectively.

Figure 1.2 Nusselt number of Al2O3/water at different Reynolds numbers and particle loadings [21].

The experimental heat transfer coefficient and Nusselt number of Ni/water nanofluids at various Reynolds numbers and particle loadings are shown in Fig. 1.3A and 1.3B [34]. The Nusselt number is enhanced to 10% and 9.5% at 0.02% vol. of Ni/water nanofluid at Reynolds numbers of 3000 and 22,000, respectively; while for the 0.6% vol. of Ni/water nanofluid it is approximately enhanced to 29.12% and 39.18% at the same Reynolds numbers compared to water.

Figure 1.3 Ni/water nanofluid at different Reynolds numbers and particle loadings: (A) heat transfer coefficient and (B) Nusselt number [34].

The proposed Nusselt number correlations of various researchers are mentioned below. Anoop et al. [35] developed a Nusselt number for Al2O3/water nanofluid flow in a tube and they also noticed that the heat transfer enhancement is about 25% and 11% for 45 and 150 nm size nanoparticles at a weight concentration of 4%.

(1.29)

Li and Xuan [36] developed a Nusselt number correlation for Cu/water nanofluid and also revealed heat transfer enhancement of 60% at =2% of Cu/water nanofluid.

(1.30)

Yang et al. [37] proposed a Nusselt number correlation for graphite/commercial automatic transmission fluid-based nanofluid and also observed 22% of heat transfer enhancement at 2.5 wt.% and at Re of 120.

(1.31)

where a and b are the constant and exponent, respectively.

Similarly, Rea et al. [38] developed a regression equation based on the experimental data of alumina/water nanofluid and zirconia/water and achieved heat transfer enhancements of 27% and 3% at =6% and =1.32%, respectively.

(1.32)

For Al2O3/water nanofluid

Based on the experimental data of Al2O3/water and TiO2/water nanofluid, Pak and Cho [39] have developed Nusselt number correlation.

(1.33)

Turbulent convective heat transfer for Cu/water nanofluid flow in a tube has been estimated by Xuan and Li [40] experimentally and they also proposed a Nusselt number correlation.

(1.34)

From the experimental data of TiO2/water nanofluid, Duangthongsuk and Wongwises [41] have noticed heat transfer coefficient enhancement of 26% at =1% and also observed 14% enhancement for =2% and proposed a correlation.

(1.35)

Numerical study was performed by Maiga et al. [42] for heat transfer of water/Al2O3 and ethylene glycol/Al2O3 nanofluids and they presented a correlation under laminar flow.

(1.36)

(1.37)

Maiga et al. [43] also proposed a correlation for Nusselt number from the data of water/Al2O3 and ethylene glycol/Al2O3 mixtures under turbulent flow.

(1.38)

Sajadi and Kazemi [44] used TiO2/water nanofluid in a tube and revealed an increase of of 22% and a pressure drop increase of 25% at =0.25% under turbulent flow (Fig. 1.4).

(1.39)

Figure 1.4 Nusselt number of TiO2/water at different Reynolds numbers and particle loadings [44].

Sundar et al. [45] also estimated the Nusselt number of Fe3O4/water nanofluid flow in a tube—the data are shown in Fig. 1.5—and they observed that the Nusselt number enhancement of 0.6% volume concentration of Fe3O4/water nanofluid is 20.99% and 30.96% at Reynolds number of 3000 and 22,000, respectively, compared to water, and they proposed a Nusselt number correlation.

(1.40)

Figure 1.5 Nusselt number of Fe3O4/water at different Reynolds numbers and particle loadings [45].

Buongiorno [46] proposed an alternative explanation for the abnormal heat transfer coefficient increment by considering viscosity within the boundary layer.

(1.41)

=Thickness, that is, 15.5

=friction factor correlation for turbulent flow

For Al2O3 nanofluid

For ZrO2 nanofluid

Based on the silver/water nanofluid, Asirvatham et al. [47] proposed a Nusselt number correlation.

(1.42)

The 60:40% of EG/W based Al2O3, CuO, SiO2 nanofluids have been used by Vajjha and Das [48] and presented a Nusselt number equation.

(1.43)

For CuO and SiO2 nanofluid

For Al2O3 nanofluid

Yang et al. [37] developed a Nusselt number equation for graphite/water nanofluid in laminar flow.

(1.44)

Moraveji et al. [49] proposed a correlation for Nusselt number based on the single-phase model of Al2O3/water nanofluid in the developing region.

(1.45)

Moraveji et al. [50] developed a correlation based on the experimental data of non-Newtonian Al2O3/XAS (Xanthan Aqueous Solution) nanofluid.

(1.46)

Keshavarz et al. [51] developed a correlation for Al2O3/water nanofluid under laminar flow.

(1.47)

Hejazian et al. [52] presented an equation for TiO2/water nanofluid based on the numerical analysis.

(1.48)

Hejazian et al. [53] developed Nusselt number correlations based on their numerical study on forced convection of alumina/water nanofluid.

(1.49)

Minea [54] presented a Nusselt number expression of Al2O3/water nanofluid using the Brinkman number.

(1.50)

where

Moghadassi et al. [55] presented a correlation for Al2O3/water nanofluid based on the numerical models.

(1.51)

Fig. 1.6 represents the experimental data of Hemmat Esfe [56] who showed Nusselt number enhancement of MgO/water nanofluid flow in a tube at particle concentrations of 0.0625%, 0.125%, 0.25%, 0.5%, and 1%.

Figure 1.6 Nusselt number of MgO/water at different Reynolds numbers and particle loadings [56].

Iyahraja et al. [57] conducted the heat transfer experiments for silver/water nanofluids flow in a tube under laminar flow conditions and they observed Nusselt number ratio increased up to 1.128 for 0.1% volume fraction at the Reynolds number of 2300 and they also proposed a Nusselt number correlation.

(1.52)

Heris et al. [58] have conducted experiments for Al2O3/water nanofluid flow inside a circular tube under laminar flow, they have observed that, at 2.5% vol. of nanofluid, at Peclet number from 2560 to 6000, the ratio increases from 1.08 to 1.22. Also for Peclet numbers 2500 and 6000 as the nanofluid concentration changes from 0.2% to 2.5% the ratio increases from 1.01 to 1.09 and 1.07 to 1.22, respectively, and their data are presented in Fig. 1.7.

Figure 1.7 The heat transfer coefficient ratio of Al2O3/water nanofluid vs. Peclet number at different volume concentrations [58].

1.7.2 Friction factor

The experimental data of nanofluids are used to develop a friction factor correlaton. Available correlations are presented here. From a study of Fe3O4/water nanofluid, Sundar et al. [45] proposed a friction factor correlation under turbulent flow and the data are shown in Fig. 1.8. They have observed the enhancement of friction factor in a plain tube with 0.6% vol. of Fe3O4 nanofluid when compared to water is 1.09 times and 1.10 times for Reynolds number of 3000 and 22,000 respectively.

(1.53)

Figure 1.8 Friction factor of Fe3O4/water at different Reynolds numbers and particle loadings [45].

Vajjha and Das [94] experimentally investigated Al2O3, CuO, and SiO2 nanofluid in a tube under turbulent flow condition. They observed an increase of 10.0% pressure drop of Al2O3 nanofluid at a Reynolds number of 6700.

(1.54)

Hejazian et al. [53] developed a friction factor correlation for Al2O3/water nanofluid based on the numerical study.

(1.55)

Moghadassi et al. [55] a performed similar study on the laminar forced convection of Al2O3/water nanofluid based on the numerical models.

(1.56)

Sundar et al. [34] developed a friction factor correlation for Ni/water nanofluid based on an experimental study, which is shown in Fig. 1.9. They noted that the friction factor of Ni/water nanofluid is increased to 19.12% at 0.6% vol. and at a Reynolds number of 22,000 compared to water.

(1.57)

Figure 1.9 Friction factor of Ni/water at different Reynolds numbers and particle loadings [45].

Iyahraja et al. [57] conducted the friction factor experiments for silver/water nanofluids flow in a tube under laminar flow conditions and their data are mentioned in Fig. 1.10. They found that the friction factor increases by 4.05%, 6.8%, and 10.9%, respectively, for the particle volume concentrations of 0.01%, 0.05%, and 0.1%. Their friction factor correlation is shown below.

(1.58)

Figure 1.10 (A) Pressure drop of SiO2 nanofluid and (B) friction factor of SiO2/water nanofluid [59].

Azmi et al. [59] conducted heat transfer and friction factor experiments for SiO2/water nanofluid flow in a tube up to 4% particle loadings at constant heat flux boundary condition. In the Reynolds number range of 5000–27,000, they have observed Nusselt number and friction factor at 3.0% nanofluid particle loading is greater than the values of water by 32.7% and 17.1% and their pressure drop and friction factor data are shown in Fig. 1.10A and B.

1.8 Conclusion

This chapter focuses on the available Nusselt number and friction correlations of various kinds of nanofluids. The chapter also explains the developed correlations under various flow and boundary conditions. The heat transfer and pressure drop characteristics of nanofluids are dependent on several factors, such as shape, size, material, base fluid, temperature, particle loading, geometry, etc. Major research reports indicate that the heat transfer augmentation is dependent on the particle loading. The majority of the developed Nusselt number and friction factor correlations are dependent on the Reynolds number, Prandtl number, and particle loading; some of the correlations include the Peclet number, Stefan number, and viscosity terms.

Despite the heat transfer augmentation with nanofluids and potential applications in various sectors, a deficiency is the lack of a theoretical approach for the heat transfer mechanism and the poor stability of the nanoparticles in the base fluid. There need to be further investigations to establish a detailed heat transfer mechanism for nanofluids. A proper and standard nanoparticle synthesis method is required so that the stable nanofluids are achieved. Moreover, it is necessary to develop a common Nusselt number and friction factor correlation that is applicable for all type of nanofluids for ease of use.

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Chapter 2

Preparation and evaluation of stable nanofluids for heat transfer application

Zeyu Liu¹, ², Rong Fu³ and Yan Yuying²,    ¹Marine Engineering College, Dalian Maritime University, Dalian, Liaoning, P.R. China,    ²Faculty of Engineering, The University of Nottingham, Nottingham, Nottinghamshire, United Kingdom,    ³Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, P.R. China

Abstract

Nanofluids are prepared by dispersing nanosize particles (less than 100 nm) into base liquid. They are expected to be widely used in heat transfer due to their excellent thermophysical and rheological properties. Nanofluid stability, as the prerequisite in the study of nanofluids, is a critical bottleneck in the advances of nanofluids in heat transfer. Poor colloidal stability leads to particle aggregations and even precipitation, which result in corrosion of components, clogging of flow channels, and pressure drops. Therefore it is necessary to synthesize long-term stable and reusable nanofluids for successful industrial utilization. This chapter systematically reviews different aspects that can potentially improve nanofluid stability. Respectively, they are the preparation of nanofluids, evaluation of nanofluid stability, stabilization techniques, stability mechanisms, and effects of nanofluid stability on thermal properties. We hope this work can highlight nanofluid stability and the challenges related to industrial feasibility in heat transfer.

Keywords

Nanofluid; stability; thermophysical properties; stabilization techniques; stability mechanisms

Nomenclature

Particle Hamaker constants (-)

Medium Hamaker constants (-)

Absorbance (-)

Specific heat capacity of base liquid ( )

Specific heat capacity of nanofluids ( )

Specific heat capacity of nanoparticles ( )

Diameter of nanoparticle (

Gibbs free energy of attraction ( )

Gibbs free energy of osmotic repulsion (

Gibbs free energy of steric repulsion (

Total Gibbs free energy (

Gibbs free energy of volume restraint interaction (

Intensity of incident laser light ( )

Hydrodynamic radius (

Radius of gyration (

Transmittance (-)

van der Waals attractive potential ( )

Electrostatic repulsive potential ( )

Total potential (

Settlement velocity (

Boltzmann constant (-)

Thermal conductivity of base liquid ( )

Thermal conductivity of nanofluids ( )

Thermal conductivity of nanoparticles ( )

Ratio of to (-)

Radius of aggregates (

Radius of particles (

Density of base liquid ( )

Density of nanofluids ( )

Density of nanoparticle ( )

Volume fraction of aggregates (-)

Volume fraction of densely packed particles (-)

Radius of nanoparticles ( )

Permittivity ( )

Vacuum permittivity ( )

Zeta potential ( )

Hamaker constant (-)

Intensity of laser beam ( )

Absolute temperature ( )

Distance between specific location of tube and rotation in the centrifuge ( )

Particle concentration ( )

Thermal conductivity ( )

Optical path length ( )

Empirical shape factor (-)

Absorptivity (-)

Viscosity ( )

Volume fraction (-)

Angular velocity of the centrifuge ( )

2.1 Introduction

Heat transfer is becoming a core challenge with an increasing degree of integration and boosting of novel technology [1] that is encouraging researchers to explore new generation working fluids. In this progress, nanofluids present great potential for heat transfer performance due to their excellent thermal physical and rheology properties. Many studies have reported the heat transfer enhancement of nanofluids [2,3]. For instance, Xuan and Li [4] found a 78% enhancement in thermal conductivity in Cu nanofluid. Yu et al. [5] experimentally studied the thermal conductivity of Fe3O4-kerosene nanofluid, which showed an increase of 34%. Both studies also tried to decrease frictional loss and pumping power for nanofluids. Additionally, some authors also found drag reduction of nanofluids [6–8]. Nakhchi et al. [9] found that water-based copper nanofluid reduced the friction factor by 23.6% in a circular pipe.

The performance and functionality of nanofluids are closely dependent on their stability. Therefore the long-term nanofluid stability should be investigated prior to practical application for high heat flux components. The collision of nanoparticles in the suspension leads to agglomeration that causes nanofluid destabilization. The high surface activity is a dominating factor for the agglomeration tendency of nanoparticle suspension. Moreover, the precipitation phenomenon is an important obstacle to the industrial production of nanofluids. In microfluidics, the cluster negates the beneficial properties of nanofluids and leads to clogging of the microchannel. According to the study of Lin et al. [10], nanofluid instability affects both thermal and mechanical performance, resulting in the inefficiency of heat transfer performance. For hybrid nanofluids, nanofluid instability is a big challenge for optimizing the combination of different types of nanoparticles, base liquid, and surfactant. Unexpected changes in thermophysical properties are attributed to the precipitations of nanofluids. In addition, agglomeration also affects the exergy due to the increase of viscosity and pumping cost. Therefore instability must be eliminated for industrial applications.

However, limited understanding of the anomalous behavior of nanofluids