Elsevier Revolutionizing Heat Transfer: Nanofluids, Turbulators, and Machine Learning for Sustainable Energy Efficiency (Emerging Technologies and Materials in Thermal Engineering)

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