Smart Heat Transfer and Thermal Management: Leveraging AI, Machine Learning, and Soft Computing

by Raj Kumar Arya (Editor), George D. Verros (Editor), J. Paulo Davim (Editor)

Overview

Smart Heat Transfer and Thermal Management: Leveraging AI, Machine Learning, and Soft Computing revolutionizes heat transfer engineering by integrating artificial intelligence (AI), machine learning (ML), and soft computing. This groundbreaking book delves into state-of-the-art research and practical applications, providing a holistic approach to optimize thermal management. By deepening the understanding of heat transfer principles while explaining AI, ML, and soft computing methodologies, it offers innovative solutions for heat transfer challenges across various industries. The synergy between these disciplines results in enhanced predictive modeling, system optimization, and thermal control for improved energy efficiency and cost-effectiveness.

Soft computing techniques, including fuzzy logic and neural networks, expand traditional heat transfer methods, allowing for adaptive and intelligent thermal systems. Through case studies, simulations, and real-world examples, the book demonstrates how AI and ML-driven algorithms can lead to sustainable and eco-friendly thermal management solutions, making it a valuable resource for engineers, researchers, and students alike.

Product Details

ISBN-13:	9780443338816
Publisher:	Elsevier Science
Publication date:	11/01/2025
Series:	Woodhead Publishing Reviews: Mechanical Engineering Series
Pages:	750
Product dimensions:	6.00(w) x 9.00(h) x 0.00(d)

About the Author

Raj Kumar Arya is currently serving as an Associate Professor in the Department of Chemical Engineering at Dr. B R Ambedkar National Institute of Technology, Jalandhar, Punjab, India. Prior to this role, he held positions at Thapar Institute of Engineering & Technology, Patiala, Punjab, India; Jaypee University of Engineering & Technology, Guna, India; and BITS-Pilani, Goa Campus, India. His educational background includes a Ph.D. from IIT Bombay, India, M. Tech. from IIT Delhi, India, and B. Tech. from HBTI Kanpur, India. With over 14 years of research and teaching experience, he specializes in diffusion and drying of thin film polymeric coatings, process engineering, and process modeling & simulation. Notably, he has published ~70 journal papers, secured 2 international patents, presented 22 conference papers, contributed to 29 books chapters, authored 5 books, edited 3 books, and organized the International Chemical Engineering Conference (ICHEEC 2021).

Dr. George D. Verros graduated in 1989 from the Chemical Engineering Department at Aristotle University of Thessaloniki (AUTH), following a family tradition in Chemistry and Engineering. He earned his 1995 Doctorate in polymer reaction engineering from the same department, receiving fellowships and working on research programs sponsored by EXXON and Novo Nordisk S.A. His focus includes polymer science, particularly polymer reaction engineering, membrane and coating formation, and applying non-equilibrium thermodynamics. With around forty publications in journals like Polymer and J. Membrane Sci., and over sixty in conference proceedings, he is an active member of scientific organizations and serves on the Editorial Board of Crystals (MDPI). Since 1999, he has been actively involved in environmental applications for the Greek Government, overseeing projects in water purification, sewage plants, landfills, recycling, air pollution monitoring, and thermal waste treatment. He is also a Fellow in the Department of Chemistry at Aristotle University, Greece.

Prof. (Dr.) J. Paulo Davim is a Full Professor at the University of Aveiro, Portugal, with over 35 years of experience in Mechanical, Materials, and Industrial Engineering. He holds multiple distinguished academic titles, including a PhD in Mechanical Engineering and a DSc from London Metropolitan University. He has published over 300 books and 600 articles, with more than 36,500 citations. He is ranked among the world's top 2% scientists by Stanford University and holds leadership positions in numerous international journals, conferences, and research projects.

Table of Contents

SECTION 1: FUNDAMENTALS OF HEAT TRANSFER:
1. Introduction to Heat Transfer
2. Heat Transfer Mechanisms: Conduction, Convection, Radiation, and Extended Surfaces
3. Convection Heat Transfer Correlations
4. Composite Wall Heat Transfer Analysis
5. Advanced Methods in Heat Transfer Analysis: Mathematical Modeling, Numerical Techniques, Finite Element Analysis, and Computational Fluid Dynamics

SECTION 2: AI AND MACHINE LEARNING APPLICATIONS IN HEAT TRANSFER:
6. Foundations and Introduction to AI in Heat Transfer
7. AI-Enhanced Design and Optimization
8. Machine Learning Applications for Heat Transfer Systems

SECTION 3: ADVANCED COMPUTATIONAL APPROACHES IN HEAT TRANSFER:
9. Introduction to Soft Computing Techniques
10. Soft Computing Applications in Heat Transfer Optimization

SECTION 4: COMBINED APPROACHES AND HYBRID TECHNIQUES:
11. Hybrid AI-ML Algorithms for Heat Transfer
12. Chapter: AI-Optimized and Enhanced Heat Transfer Systems
13. Integrating Soft Computing and Machine Learning

SECTION 5: HEAT EXCHANGERS:
14. Heat Exchanger Fundamentals, Design, and Optimization
15. Shell-and-Tube Heat Exchangers
16. Plate Heat Exchangers
17. Finned-Tube Heat Exchangers
18. Regenerative Heat Exchangers
19. Air-Cooled Heat Exchangers

SECTION 6: ADVANCED HEAT EXCHANGERS
20. Microchannel Heat Exchangers
21. Phase Change Heat Exchangers

SECTION 7: CASE STUDIES IN HEAT TRANSFER AND HEAT EXCHANGERS:
22. Case Study: Heat Transfer in Electronics Cooling
23. Case Study: Heat Transfer in AutomotiveRadiators
24. Case Study: Heat Exchanger Performance in Power Plants
25. Case Study: Heat Transfer in Biomedical Devices
26. Case Study: Heat Pipes in Spacecraft Thermal Control
27. Case Study: Energy-Efficient HVAC Systems
28. Case Study: Nanofluid Dynamics and Its Heat Transfer Enhancement Capability
29. Case Study: AI and Machine Learning In Thermal Management

What People are Saying About This

From the Publisher

Explores the synergy between AI, machine learning, and soft computing techniques to revolutionize heat transfer engineering and optimize thermal management