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.
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Dr. Jatoth Heeraman is an Assistant Professor of Mechanical Engineering at Malla Reddy (MR) Deemed to be University, Hyderabad, India. He received his Ph.D. in Mechanical Engineering from Lovely Professional University, India in 2024 and earned his M.Tech (Thermal Engineering) and B.Tech (Mechanical Engineering) degrees from JNTUH, Hyderabad, India. With over eight years of academic and research experience, his doctoral work focused on experimental heat transfer enhancement in heat exchangers. He has contributed over 25 journal articles and holds 25 Indian patents (published) and one UK patent. His research interests include high-speed flows, renewable energy systems, and AI/ML-enabled CFD.
Dr. Praveen Barmavatu is an Assistant Professor of Mechanical Engineering at Universidad Tecnológica Metropolitana (UTEM), Santiago, Chile. He earned his Ph.D. in Mechanical Engineering in 2019 and holds M.Tech and B.Tech degrees from JNTUH, Hyderabad, India, along with a Diploma in Mechanical Engineering. His research focuses on heat exchangers, thermal energy storage, solar thermal systems, and AI/ML-based optimization. He has published over 110 journal articles, holds several patents, and has contributed to international projects funded by ANID FONDECYT (Chile), DRDO (India), and KFUPM (Saudi Arabia).
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Hardcover. Condizione: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781041089698
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Hardcover. Condizione: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781041089698
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