Artificial intelligence in heat transfer / edited by J.P. Abraham, J.M. Gorman.
| Other author | Abraham, J. P. (John P.) |
| Other author | Gorman, J. M. (John M.) |
| Format | Electronic |
| Publication Info | Boca Raton, FL : CRC Press, 2025. |
| Description | pages cm |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Series | Advances in numerical heat transfer ; volume VI |
| Contents | Physics-informed neural networks for solving partial differential equations / Prakhar Sharma, Michelle Tindall, and Perumal Nithiarasu -- Multi-objective optimization of heat transfer problems / Andrea Fragnito, Marcello Iasiello, Gerardo Maria Mauro, Wilson K. S. Chiu, and Nicola Bianco -- CFD/HT simulations and DNN modelling of conjugate heat transfer in metal foams / Ubade Kemerli, Muhsin Gokhan Gunay, and Yogendra Joshi -- Integrating artificial intelligence in nanofluid heat transfer : a deep dive into artificial intelligence applications / Andaç Batur Çolak -- Developing an artificial neural network algorithm for heat and mass transfer assessment in ternary hybrid nanofluid flow / Shilpa B and Naveen Kumar R -- Physics informed deep learning approaches for industrial heat exchangers / Vishal Jadhav, Ritam Majumdar, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, and Venkataramana Runkana -- AI based analysis for optimizing radiative Jeffery-Hamel flow for cross-diffusion effects : a physics informed machine learning / Muhammad Naeem Aslam, Nadeem Shaukat, Arshad Riaz -- Artificial neural network for effective predicting design model of heat transfer rate in the bi-directional flow of magnetized tangent hyperbolic nanomaterial with non-uniform heat source / Rupa Baithalu, S.R. Mishra, Subhajit Panda. |
| Abstract | "Artificial Intelligence in Heat Transfer shows how AI tools and techniques, such as artificial neural networks, machine learning algorithms, genetic algorithms, etc., provide practical benefits specific to thermal sciences. It presents case studies involving heat and mass transfer, multi-objective optimization, conjugate heat transfer, nano-fluids, thermal radiation, heat transfer through porous media (metal foam), and more. Drawing on the collective expertise of leading researchers and experts in multiple fields, the book provides an in-depth understanding of the possibilities that emerge when these tools are applied to problems related to thermal sciences. Artificial Intelligence (AI) is an ever-evolving discipline that has created new and groundbreaking opportunities to advance the mechanical engineering field, particularly in the area of numerical heat transfer. This volume of Advances in Numerical Heat Transfer explores various ways AI is used in heat transfer to solve engineering problems. This book will serve as an important resource for upper-level undergraduate students, researchers, engineers, and professionals, equipping them with the knowledge and inspiration to push the boundaries of the thermal sciences through AI-driven tools and techniques"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2024055847 |
| ISBN | 9781032688107 (hardback) |
| ISBN | 9781032688114 (paperback) |
| ISBN | (ebook) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |