Thermal System Optimization: A Population-based Metaheuristic Approach - Rilegato

Patel, Vivek K.; Savsani, Vimal J.; Tawhid, Mohamed A.

Rilegato

ISBN 10: 3030104761 ISBN 13: 9783030104764

Casa editrice: Springer Nature, 2019

Riassunto

This book presents a wide-ranging review of the latest research and development directions in thermal systems optimization using population-based metaheuristic methods. It helps readers to identify the best methods for their own systems, providing details of mathematical models and algorithms suitable for implementation.

To reduce mathematical complexity, the authors focus on optimization of individual components rather than taking on systems as a whole. They employ numerous case studies: heat exchangers; cooling towers; power generators; refrigeration systems; and others. The importance of these subsystems to real-world situations from internal combustion to air-conditioning is made clear.

The thermal systems under discussion are analysed using various metaheuristic techniques, with comparative results for different systems. The inclusion of detailed MATLAB® codes in the text will assist readers—researchers, practitioners or students—to assess these techniques for different real-world systems.

Thermal System Optimization is a useful tool for thermal design researchers and engineers in academia and industry, wishing to perform thermal system identification with properly optimized parameters. It will be of interest for researchers, practitioners and graduate students with backgrounds in mechanical, chemical and power engineering.

Su questo libro

Informazioni sull?autore

Dr. Vivek Patel is working as an assistant professor at P.D. Petroleum University, Gandhinagar, India. He has completed his Ph.D. in the filed of thermal system optimization from S.V. National Institute of Technology, Surat, India. His thesis titled, "Design Optimization of Thermal Systems Using Advanced Optimization Techniques". He has more than 13 years of academic experience. His research area includes thermal system design, advanced optimization techniques, solar thermal systems and energy management.

Dr. Vimal Savsani is working as an assistant professor at P.D. Petroleum University, Gandhinagar, India. He has completed his Ph.D. in the filed of mechanical design optimization from S.V. National Institute of Technology, Surat, India. His thesis titled, "Design Optimization of Mechanical Elements Using Advance Optimization Techniques ". He was a post-doctoral fellow at Thompson Rivers University, BC,Canada. He has also to his credit one book titled "Mechanical design optimization using advanced optimization techniques", published by Springer, London. He has more than 11 years of academic experience. His research area includes Advanced meta-heuristics, mechanical system desing and optimization, automobile suspension optimization, structure optimization and wind farm layout optimization.

Mohamed A. Tawhid received his PhD in Applied Mathematics from the University of Maryland Baltimore County, Maryland, USA. From 2000 to 2002, he was a Postdoctoral Fellow at the Faculty of Management, McGill University, Montreal, Quebec, Canada. Currently, he is a full professor at Thompson Rivers University. His recent research interests are best described as metaheuristic/ evolutionary computing/artificial intelligence algorithms and their applications in engineering and data science. He has served on editorial board several journals. He has also worked on several industrial projects in BC, Canada.

To reduce mathematical complexity, the authors focus on optimization of individual components rather than taking on systems as a whole. They employ numerous case studies: heat exchangers; cooling towers; power generators; refrigeration systems; and others. The importance of these subsystems to real-world situations from internal combustion to air-conditioning is made clear.

The thermal systems under discussion are analysed using various metaheuristic techniques, with comparative results for different systems. The inclusion of detailed MATLAB® codes in the text will assist readers—researchers, practitioners or students—to assess these techniques for different real-world systems.

Thermal System Optimization is a useful tool for thermal design researchers and engineers in academia and industry, wishing to perform thermal system identification with properly optimized parameters. It will be of interest for researchers, practitioners and graduate students with backgrounds in mechanical, chemical and power engineering.

Dettagli dell?edizione

• Editore: Springer Nature
• Data di pubblicazione: 2019
• ISBN 10: 3030104761
• ISBN 13: 9783030104764
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero edizione: 1
• Numero di pagine: 496
• Contatto del produttore: non disponibile