Artificial intelligence and machine learning in heat transfer optimization for sustainable energy systems /

Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus...

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Bibliographic Details
Corporate Author: Taylor & Francis
Other Authors: Heeraman, Jatoth (Editor), Barmavatu, Praveen (Editor)
Format: eBook
Language:English
Published: Boca Raton : CRC Press, 2026.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:Artificial Intelligence and Machine Learning in Heat Transfer Optimization for Sustainable Energy Systems examines how to use AI/ML-driven methodologies to enhance heat transfer processes in energy systems, such as industrial heat recovery, HVAC systems, and renewable energy generation, with a focus on sustainability.Exploring applications in sustainable energy systems, renewable resources, and smart grids, the book presents intelligent control methodologies, predictive modeling, real-time data analysis, and thermal management with deep learning. It covers AI-driven heat transfer monitoring, which is critical for a variety of applications beyond sustainability, including industrial production, aerospace, automotive, and electronics cooling. The chapters feature numerous case studies of AI/ML implementation in heat exchangers, power plants, and renewable energy systems.This book will interest researchers and graduate students studying the intersection of AI, ML, and heat transfer optimization as applied to energy systems.
Physical Description:1 online resource (370 pages) : illustrations (black and white)
ISBN:9781040622544
1040622542
9781003647782
1003647782
104056464X
9781040564646