Revolutionizing Heat Transfer : Nanofluids, Turbulators, and Machine Learning for Sustainable Energy Efficiency.

Format:

Book

Author/Creator:

Said, Zafar.

Series:

Emerging Technologies and Materials in Thermal Engineering Series

Language:

English

Physical Description:

1 online resource (437 pages)

Edition:

1st ed.

Place of Publication:

Chantilly : Elsevier, 2025.

Summary:

Revolutionizing Heat Transfer: Nanofluids, Turbulators, and Machine Learning for Sustainable Energy Efficiency bridges the knowledge gap between traditional heat transfer enhancement techniques and innovative approaches employing nanofluids and turbulators. Users will find this to be an all-inclusive resource on the latest advancements in nanofluids, turbulators, and machine learning techniques for heat transfer enhancement that also includes detailed guidance on the synthesis, characterization, design, and optimization of these technologies. Using an interdisciplinary approach, this book serves as a valuable reference for researchers and practitioners working on heat transfer in energy applications and students studying related areas.There is a growing need for this resource as it addresses both the limitations of current heat transfer techniques while also providing sustainable solutions for a wide range of engineering applications.- Presents the synthesis, properties, and characterization of nanofluids and the design, optimization, and performance evaluation of turbulators- Provides insights into the mechanisms of heat transfer enhancement using nanofluids and turbulators, along with their applications in various heat transfer systems- Offers guidance on the environmental and economic impacts of nanofluids and turbulators, enabling readers to make informed decisions on their implementation- Highlights the challenges and future prospects of nanofluids and turbulators in renewable energy systems, waste heat recovery, and energy storage systems- Equips readers with the knowledge to address safety concerns, regulatory challenges, and develop standards and guidelines for nanofluid and turbulator applications

Contents:

Front Cover

Revolutionizing Heat Transfer

Copyright Page

Dedication

Contents

List of contributors

About the editor

Acknowledgments

1 Introduction to sustainable heat transfer enhancement techniques

Abbreviations

1.1 Introduction

1.2 Fundamentals of heat transfer

1.2.1 Conduction

1.2.2 Convection

1.2.3 Radiation

1.3 Enhancement of heat transfer through traditional practices

1.3.1 Extended surfaces

1.3.2 Forced convection strategies

1.3.3 Phase change materials

1.4 Limitations of traditional methods

1.5 Need for sustainable heat transfer techniques

1.6 Nanofluids and turbulators: the emerging technologies

1.6.1 Nanofluids

1.6.2 Turbulators

1.7 Emerging and sustainable technologies

1.8 Challenges and future outlook

1.9 Conclusions

AI disclosure

References

2 Nanofluids: synthesis, properties, and characterization

2.1 Introduction

2.2 Nanofluid: synthesis and stabilization

2.2.1 Preparation of nanofluid

2.2.2 Stabilization of nanofluids

2.3 Features of nanofluids

2.3.1 Thermal properties of nanofluids

2.3.1.1 Thermal conductivity

2.3.1.2 Viscosity

2.3.1.3 Specific heat capacity

2.3.1.4 Density of the substance

2.3.2 The solar spectrum splitters' optical characteristics in nanofluids

2.3.3 The impact of nanofluid stability on thermophysical characteristics is examined in this study

2.4 Comparisons and distinctions among assessment techniques for nanofluids

2.4.1 Relationships and distinctions among limitations

2.4.2 Relationships and variations among assessment indices

2.5 SBS implementation in a hybrid PV/T system

2.5.1 Nanoparticles of metals

2.5.2 Metal oxide nanoparticles

2.6 Conclusion

3 Turbulators: types, design, and performance

3.1 Introduction

3.1.1 Active method.

3.1.2 Passive method

3.1.3 Compound method

3.2 Types of turbulators

3.2.1 Twisted tape

3.2.2 Ball turbulator

3.2.3 Spring turbulator

3.2.4 Matrix turbulator

3.3 Turbulators in heat exchanger

3.3.1 Coiled wire/tubes

3.3.1.1 Coil-shaped tubes

3.3.1.2 Coiled wire

3.3.2 Rough surfaces (ribs, corrugated tubes)

3.3.3 Twisted tape

3.3.3.1 Typical twisted tape

3.3.3.2 Helically twisted tapes

3.3.3.3 TWT with varying lengths, pitches, and alternate axes

3.3.3.4 Multiple twisted tapes

3.3.3.5 Twisted tape with attached fins and baffles

3.3.3.6 twisted tapes with cuts, slots, holes

3.3.4 Conical/vertex ring

3.3.4.1 Conical ring

3.3.4.2 Vortex rings

3.4 Usage of turbulators in parabolic trough solar collector

3.4.1 Corrugated channels

3.4.1.1 Different corrugations

3.4.1.2 Literature review

3.4.2 Channels with obstacles

3.4.2.1 Different obstacles

3.4.2.2 Literature review

3.5 Summary

4 Nanofluids for heat transfer enhancement

4.1 Introduction

4.1.1 Overview

4.2 Unique properties of nanofluids

4.2.1 Thermal conductivity

4.2.2 Viscosity

4.2.3 Convective heat transfer coefficient

4.3 Type of nanoparticles and base fluid

4.3.1 Types of nanoparticles

4.3.1.1 Metallic nanoparticles

4.3.1.2 Metal oxide nanoparticles

4.3.1.3 Carbon-based nanoparticles

4.3.1.4 Ceramic and advanced nanomaterials

4.3.2 Type of base fluids

4.3.2.1 Water

4.3.2.2 Ethylene glycol

4.3.2.3 Propylene glycol

4.3.2.4 Oil

4.4 Applications of nanofluids

4.4.1 Nanofluids in automotive cooling systems

4.4.2 Nanofluids for electronic cooling

4.4.3 Nanofluids in industrial heat exchangers

4.4.4 Nanofluids in renewable energy systems

4.5 Challenges and limitations

4.6 Conclusion

References.

5 Turbulators for heat transfer enhancement

5.1 Introduction

5.2 Maximizing heat transfer efficiency: exploring turbulators within duct systems

5.3 Shape matters: exploring the influence of turbulator geometry on heat transfer

5.4 Types of solar collectors

5.4.1 Collector with flat shape

5.4.2 Tube collector equipped with parabolic concentrator

5.4.3 Collector equipped with linear Fresnel concentrator

5.4.4 Evacuated tube collectors

5.4.5 Collector with parabolic dish

5.5 Effective parameters in heat transfer

5.5.1 Functional changes with the presence of nanofluids

5.5.2 Impact of magnetic field in heat transfer performance

5.5.3 Simultaneous studies on magnetic fields and nanofluids

5.5.4 Influence of nanofluids on heat transfer in various systems

5.6 Conclusion

6 Synergistic effects of nanofluids, turbulators, and artificial intelligence

6.1 Introduction

6.2 Nanofluids: enhancing heat transfer efficiency

6.2.1 Thermal conductivity

6.2.2 Viscosity

6.2.3 Specific heat capacity

6.3 Turbulators: enhancing heat transfer surfaces

6.4 Application of artificial intelligence in heat transfer

6.4.1 Random Forest

6.4.2 Support vector machine

6.4.3 K-nearest neighbors

6.4.4 Extreme gradient boosting

6.4.5 Artificial neural network

6.4.6 Genetic algorithm

6.4.7 Non-dominated sorting genetic algorithm II

6.5 Synergistic effects: integration of artificial intelligence, nanofluids, and turbulators

6.5.1 Effects of artificial intelligence and nanofluids

6.5.2 Effects of artificial intelligence and turbulator

6.5.3 Effects of nanofluids and turbulator

6.5.4 Effects of nanofluids, turbulator and artificial intelligence

6.6 Conclusion

7 Nanofluids and turbulators in renewable energy systems

7.1 Introduction.

7.2 What are nanofluids

7.2.1 Nanofluid preparation

7.2.1.1 One-step

7.2.1.2 Two step

7.2.2 Types of nanofluids

7.2.3 Thermophysical properties

7.2.3.1 Viscosity

7.2.3.2 Thermal conductivity

7.2.3.3 Density

7.2.4 Mathematical models of convective heat transfer in nanofluids

7.2.4.1 Single-phase model

7.2.4.2 Two-phase model

7.2.4.3 Mixture model

7.2.5 Natural convection

7.2.6 Forced and mixed convection

7.3 What are turbolators

7.4 Renewable energy versus nonrenewable energy

7.5 Nanofluid utilization in renewable energy systems

7.6 Turbolators utilization in renewable energy systems

7.7 Conclusion

8 Machine learning and artificial intelligence in heat transfer enhancement

8.1 Potential applications of AI and ML in nanofluids heat transfer research

8.1.1 Machine learning and AI in heat transfer coefficient prediction of nanofluids

8.1.2 Machine learning and AI-assisted optimization of nanofluid formulation

8.1.3 Machine learning and AI in predicting the thermophysical properties of nanofluids

8.1.3.1 Artificial Neural Networks

8.1.3.2 Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

8.1.3.3 Radial Bias Function Networks

8.1.3.4 Least Square Support Vector Machines

8.1.4 Machine learning and AI in flow and heat transfer behavior analysis

8.1.4.1 Prediction of Convective Heat Transfer Coefficient

8.1.4.2 Modeling Boiling and Phase Change Phenomena

8.1.4.3 Pressure drop estimation

8.1.5 Integration of machine learning with CFD for nanofluids

8.2 Conclusions

9 Modeling, simulation, and artificial intelligence: a convergence in heat transfer systems

9.1 Introduction

9.2 Modeling and simulation

9.3 Modeling and simulation in heat transfer systems based on renewable energy sources.

9.4 Modeling and simulation in heat transfer systems based on fossil fuels

9.5 Artificial intelligence in heat transfer systems

9.5.1 Machine learning models for heat transfer

9.5.1.1 Types of machine learning models

9.5.1.2 Model training and validation

9.5.2 Applications of machine learning in heat transfer

9.6 Convergence of simulation and artificial intelligence

9.7 Conclusion

10 Fundamentals of turbulent flow enhancement techniques

10.1 Introduction

10.2 Passive methods

10.2.1 Inserts

10.2.1.1 Twisted tube inserts

10.2.1.2 Wire coil inserts

10.2.2 Extended surfaces

10.2.2.1 Baffles

10.2.2.2 Fins

10.2.3 Other methods

10.2.3.1 Ribbed tube

10.2.3.2 Conical rings

10.2.3.3 Turbulator rings

10.3 Active methods

10.3.1 Electric fields

10.3.2 Magnetic fields

10.3.3 Fluid vibration

10.3.4 Mechanical power

10.4 Summary

11 Environmental and economic impacts of nanofluids and turbulators

11.1 Introduction

11.2 Nanofluids

11.2.1 Properties of nanofluids

11.2.1.1 Thermal conductivity

11.2.1.2 Viscosity

11.2.1.3 Specific heat

11.2.2 Application of nanofluids

11.2.3 Economic and environmental impact of nanofluid

11.3 Turbulators

11.3.1 Application of turbulators

11.3.2 Economic and environmental impact of turbulators

11.4 Economic and environmental impact of nanofluids and turbulators

11.5 Conclusion

11.6 Future work

12 Future perspectives: emerging technologies and innovations

12.1 Introduction

12.2 Advanced energy storage technologies

12.2.1 Dominance of lithium-ion technology

12.2.2 Solid-state batteries

12.2.3 Grid-scale storage

12.2.4 Vehicle-to-grid integration

12.2.5 Hybrid energy storage systems

12.3 Carbon capture and utilization

12.4 Energy-efficient buildings.

12.4.1 Advancements in building materials.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

0-443-31531-0

OCLC:

1521500011