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.
1. 1. Introduction to sustainable heat transfer enhancement techniques - p. 1 2. 2. Nanofluids: synthesis, properties, and characterization - p. 25 3. 3. Turbulators: types, design, and performance - p. 59 4. 4. Nanofluids for heat transfer enhancement - p. 83 5. 5. Turbulators for heat transfer enhancement - p. 99 6. 6. Synergistic effects of nanofluids, turbulators, and artificial intelligence - p. 135 7. 7. Nanofluids and turbulators in renewable energy systems - p. 163 8. 8. Machine learning and artificial intelligence in heat transfer enhancement - p. 189 9. 9. Modeling, simulation, and artificial intelligence: a convergence in heat transfer systems - p. 201 10. 10. Fundamentals of turbulent flow enhancement techniques - p. 223 11. 11. Environmental and economic impacts of nanofluids and turbulators - p. 243 12. 12. Future perspectives: emerging technologies and innovations - p. 257 13. Index - p. 289
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.
1. 1. Introduction to sustainable heat transfer enhancement techniques - p. 1 2. 2. Nanofluids: synthesis, properties, and characterization - p. 25 3. 3. Turbulators: types, design, and performance - p. 59 4. 4. Nanofluids for heat transfer enhancement - p. 83 5. 5. Turbulators for heat transfer enhancement - p. 99 6. 6. Synergistic effects of nanofluids, turbulators, and artificial intelligence - p. 135 7. 7. Nanofluids and turbulators in renewable energy systems - p. 163 8. 8. Machine learning and artificial intelligence in heat transfer enhancement - p. 189 9. 9. Modeling, simulation, and artificial intelligence: a convergence in heat transfer systems - p. 201 10. 10. Fundamentals of turbulent flow enhancement techniques - p. 223 11. 11. Environmental and economic impacts of nanofluids and turbulators - p. 243 12. 12. Future perspectives: emerging technologies and innovations - p. 257 13. Index - p. 289
