Title Thermal system optimization : a population-based metaheuristic approach / Vivek K. Patel, Vimal J. Savsani and Mohamed A. Tawhid

Published Cham, Switzerland : Springer, [2019] ©2019

Click on the following:
Springer Engineering eBooks
Springer eBooks

Copies

Description 1 online resource Contents Intro; Preface; Contents; 1 Introduction; Abstract; References; 2 Metaheuristic Methods; Abstract; 2.1 Genetic Algorithm (GA); 2.1.1 Reproduction; 2.1.2 Crossover; 2.1.3 Mutation; 2.2 Particle Swarm Optimization (PSO) Algorithm; 2.3 Differential Evolution (DE) Algorithm; 2.4 Artificial Bee Colony (ABC) Algorithm; 2.5 Cuckoo Search Algorithm (CSA); 2.6 Teaching-Learning-Based Optimization (TLBO) Algorithm; 2.6.1 Teacher Phase; 2.6.2 Learner Phase; 2.7 Symbiotic Organism Search (SOS) Algorithm; 2.7.1 Mutualism Phase; 2.7.2 Commensalism Phase; 2.7.3 Parasitism Phase 2.8 Water Wave Optimization (WWO) Algorithm2.8.1 Propagation Operator; 2.8.2 Refraction Operator; 2.8.3 Breaking Operator; 2.9 Heat Transfer Search (HTS) Algorithm; 2.10 Passing Vehicle Search (PVS) Algorithm; 2.11 Sine Cosine Algorithm (SCA); 2.12 Parameter Tuning of Algorithms; References; 3 Thermal Design and Optimization of Heat Exchangers; Abstract; 3.1 Shell and Tube Heat Exchanger (STHE); 3.1.1 Thermal Model; 3.1.2 Case Study, Objective Function Description, and Constraints; 3.1.3 Results and Discussion; 3.2 Plate-Fin Heat Exchanger (PFHE); 3.2.1 Thermal Model 3.2.2 Case Study, Objective Function Description, and Constraints3.2.3 Results and Discussion; 3.3 Fin and Tube Heat Exchanger (FTHE); 3.3.1 Thermal Model; 3.3.2 Case Study, Objective Function Description, and Constraints; 3.3.3 Results and Discussion; 3.4 Regenerative Heat Exchanger (Rotary Regenerator); 3.4.1 Thermal Model; 3.4.2 Case Study, Objective Function Description, and Constraints; 3.4.3 Results and Discussion; 3.5 Plate Heat Exchanger (PHE); 3.5.1 Thermal Model; 3.5.2 Case Study, Objective Function Description, and Constraints; 3.5.3 Results and Discussion; References 4 Thermal Design and Optimization of Heat Engines and Heat PumpsAbstract; 4.1 Carnot Heat Engine; 4.1.1 Thermal Model; 4.1.2 Case Study, Objective Function Description, and Constraints; 4.1.3 Results and Discussion; 4.2 Rankine Heat Engine; 4.2.1 Thermal Model; 4.2.2 Case Study, Objective Function Description, and Constraints; 4.2.3 Results and Discussion; 4.3 Stirling Heat Engine; 4.3.1 Thermal Model; 4.3.2 Case Study, Objective Function Description, and Constraints; 4.3.3 Results and Discussion; 4.4 Brayton Heat Engine; 4.4.1 Thermal Model 4.4.2 Case Study, Objective Function Description, and Constraints4.4.3 Results and Discussion; 4.5 Ericsson Heat Engine; 4.5.1 Thermal Model; 4.5.2 Case Study, Objective Function Description, and Constraints; 4.5.3 Results and Discussion; 4.6 Diesel Heat Engine; 4.6.1 Thermal Model; 4.6.2 Case Study, Objective Function Description, and Constraints; 4.6.3 Results and Discussion; 4.7 Radiative-Type Heat Engine; 4.7.1 Thermal Model; 4.7.2 Case Study, Objective Function Description, and Constraints; 4.7.3 Results and Discussion; 4.8 Stirling Heat Pump; 4.8.1 Thermal Model Summary 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 Bibliography Includes bibliographical references and index Notes Online resource; title from PDF title page (EBSCO, viewed February 19, 2019) Subject Thermodynamics -- Mathematical models Heat -- Transmission -- Mathematical models Mathematical optimization. Metaheuristics. TECHNOLOGY & ENGINEERING -- Mechanical. Heat -- Transmission -- Mathematical models Mathematical optimization Metaheuristics Thermodynamics -- Mathematical models Form Electronic book Author Savsani, Vimal J., author. Tawhid, Mohamed A., author ISBN 9783030104771 303010477X 9783030104788 3030104788

  Permalink