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Thermal System Optimization : A Population-Based Metaheuristic Approach / by Vivek K. Patel, Vimal J. Savsani, Mohamed A. Tawhid

By: Patel, Vivek K.
Contributor(s): Savsani, Vimal J., autor | Tawhid, Mohamed A., autor | SpringerLink (Online service)
Series: (Engineering (Springer-11647)).Publisher: Cham : Springer, 2019Description: 1 recurso en línea (XVI, 477 páginas) : 174 ilustraciones.ISBN: 9783030104771.Subject: Termodinámica -- Modelos matemáticos | Calor -- Transmisión -- Modelos matemáticos | Optimización matemáticaOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
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.
Abstract: 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.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TJ265 2019 EB (Browse shelf(Opens below)) Acceso electrónico eBooks24062357
Total holds: 0

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.

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.

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