Revolutionizing Heat Transfer: Nanofluids, Turbulators, and Machine Learning for Sustainable Energy Efficiency
| AUTHOR | Said, Zafa; Said, Zafar; Said, Zafar |
| PUBLISHER | Elsevier (06/03/2025) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
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.
Show More
Product Format
Product Details
ISBN-13:
9780443315305
ISBN-10:
0443315302
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
320
Carton Quantity:
24
Product Dimensions:
5.98 x 0.47 x 8.98 inches
Weight:
0.95 pound(s)
Country of Origin:
US
Subject Information
BISAC Categories
Technology & Engineering | Power Resources - General
Technology & Engineering | Energy
Descriptions, Reviews, Etc.
publisher marketing
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.
Show More
Your Price
$198.00
