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Thermal System Optimization, 1st ed. 2019 A Population-Based Metaheuristic Approach

Langue : Anglais

Auteurs :

Couverture de l’ouvrage Thermal System Optimization
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 fordifferent 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.

Introduction.- Meta-Heuristics Methods.- Thermal Design and Optimization of Heat Exchangers.- Thermal Design and Optimization of Heat Engines/Heat Pump.- Thermal Design and Optimization of Refrigerating System.- Thermal Design and Optimization of Power Generating Cycles.- Miscellaneous Systems.
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 hasalso 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 work
Outlines each of the varied meta-heuristic approaches to solve thermal system optimization problems Provides MATLAB codes for all of the meta-heuristic and thermal systems used in the text Presents a comparative analysis for all thermal systems, to identify the best performing approach

Date de parution :

Ouvrage de 477 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

158,24 €

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