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    Smart Heat Transfer and Thermal Management

    Leveraging AI, Machine Learning, and Soft Computing

    AvRaj Kumar Arya,George D. Verros

    Häftad, Engelska, 2025

    Del i serien Woodhead Publishing Reviews: Mechanical Engineering Series

    2 499 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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.

    • Offers a comprehensive exploration of the integration of AI, machine learning, and soft computing techniques in heat transfer engineering
    • Includes real-world examples and case studies that showcase how smart heat transfer approaches have been successfully applied in various industries and systems
    • Incorporates the latest advancements and cutting-edge research in the field, ensuring that readers stay up-to-date with the most recent developments and emerging trends in smart heat transfer technologies
    • Focuses on application-oriented insights, offering practical guidance on how to implement AI, machine learning, and soft computing methods in heat transfer engineering, equipping readers with the tools to effectively tackle complex heat transfer challenges

    Produktinformation

    • Utgivningsdatum:2025-11-07
    • Mått:152 x 229 x 28 mm
    • Vikt:1 000 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Woodhead Publishing Reviews: Mechanical Engineering Series
    • Antal sidor:552
    • Förlag:Elsevier Science
    • ISBN:9780443338816

    Utforska kategorier

    • Elektronik och kommunikationer inom Naturvetenskap och teknik
    • Fysik inom Naturvetenskap och teknik
    • Maskinteknik och material inom Naturvetenskap och teknik

    Mer om författaren

    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.

    Innehållsförteckning

    • SECTION 1: FUNDAMENTALS OF HEAT TRANSFER:1. Introduction to Heat Transfer2. Heat Transfer Mechanisms: Conduction, Convection, Radiation, and Extended Surfaces3. Convection Heat Transfer Correlations4. Composite Wall Heat Transfer Analysis5. Advanced Methods in Heat Transfer Analysis: Mathematical Modeling, Numerical Techniques, Finite Element Analysis, and Computational Fluid DynamicsSECTION 2: AI AND MACHINE LEARNING APPLICATIONS IN HEAT TRANSFER: 6. Foundations and Introduction to AI in Heat Transfer7. AI-Enhanced Design and Optimization8. Machine Learning Applications for Heat Transfer SystemsSECTION 3: ADVANCED COMPUTATIONAL APPROACHES IN HEAT TRANSFER: 9. Introduction to Soft Computing Techniques10. Soft Computing Applications in Heat Transfer OptimizationSECTION 4: COMBINED APPROACHES AND HYBRID TECHNIQUES: 11. Hybrid AI-ML Algorithms for Heat Transfer12. Chapter: AI-Optimized and Enhanced Heat Transfer Systems13. Integrating Soft Computing and Machine LearningSECTION 5: HEAT EXCHANGERS: 14. Heat Exchanger Fundamentals, Design, and Optimization15. Shell-and-Tube Heat Exchangers16. Plate Heat Exchangers17. Finned-Tube Heat Exchangers18. Regenerative Heat Exchangers19. Air-Cooled Heat ExchangersSECTION 6: ADVANCED HEAT EXCHANGERS 20. Microchannel Heat Exchangers21. Phase Change Heat ExchangersSECTION 7: CASE STUDIES IN HEAT TRANSFER AND HEAT EXCHANGERS: 22. Case Study: Heat Transfer in Electronics Cooling23. Case Study: Heat Transfer in AutomotiveRadiators24. Case Study: Heat Exchanger Performance in Power Plants25. Case Study: Heat Transfer in Biomedical Devices26. Case Study: Heat Pipes in Spacecraft Thermal Control27. Case Study: Energy-Efficient HVAC Systems28. Case Study: Nanofluid Dynamics and Its Heat Transfer Enhancement Capability29. Case Study: AI and Machine Learning In Thermal Management