Chapter 14 Optimization techniques in flow dynamics and heat transfer
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P. Balakrishnan
Abstract
This chapter comprehensively explores optimization methodologiesoptimization methodologies in flow dynamics and heat transfer, addressing critical challenges in energy efficiency, system performance, and sustainability. It examines both classical approaches (gradient-based, Lagrangian, and variational methodsvariational methods) and modern techniques (genetic algorithms, particle swarm optimizationoptimization, and simulated annealing). Classical methodsclassical methods provide systematic frameworks for problems with smooth, differentiable functions, while modern approaches effectively handle complex, multi-objective scenarios. Applications demonstrate significant performance improvements: tube bundle configurations optimized with GAsgenetic engines (GAs) showed heat flux improvements of 2,708.27–3,641.25 W/m2 with pressure drops of 380.32–1,117.74 Pa; plate-fin heat exchangers optimized via NSGA-II achieved oil pressure drops of 13.63 kPa with heat transfer rates of 9.79 kW; and integrated AIartificial intelligence (AI) solutions reduced computational demands by 30% while improving accuracy by 20–25%. Despite these advancements, challenges persist in computational scalability, handling nonlinearity, and balancing competing objectives. Hybrid methodologies combining traditional techniquestraditional techniques with AIartificial intelligence (AI) offer promising solutions, with implementations demonstrating improvements in thermal and structural performance by 20.44% and 9.25%, respectively, while significantly reducing computational costs. This chapter establishes a foundation for addressing future challenges in flow dynamics and heat transfer optimization, emphasizing the integration of established theories with emerging technologies to drive sustainable engineering innovation.
Abstract
This chapter comprehensively explores optimization methodologiesoptimization methodologies in flow dynamics and heat transfer, addressing critical challenges in energy efficiency, system performance, and sustainability. It examines both classical approaches (gradient-based, Lagrangian, and variational methodsvariational methods) and modern techniques (genetic algorithms, particle swarm optimizationoptimization, and simulated annealing). Classical methodsclassical methods provide systematic frameworks for problems with smooth, differentiable functions, while modern approaches effectively handle complex, multi-objective scenarios. Applications demonstrate significant performance improvements: tube bundle configurations optimized with GAsgenetic engines (GAs) showed heat flux improvements of 2,708.27–3,641.25 W/m2 with pressure drops of 380.32–1,117.74 Pa; plate-fin heat exchangers optimized via NSGA-II achieved oil pressure drops of 13.63 kPa with heat transfer rates of 9.79 kW; and integrated AIartificial intelligence (AI) solutions reduced computational demands by 30% while improving accuracy by 20–25%. Despite these advancements, challenges persist in computational scalability, handling nonlinearity, and balancing competing objectives. Hybrid methodologies combining traditional techniquestraditional techniques with AIartificial intelligence (AI) offer promising solutions, with implementations demonstrating improvements in thermal and structural performance by 20.44% and 9.25%, respectively, while significantly reducing computational costs. This chapter establishes a foundation for addressing future challenges in flow dynamics and heat transfer optimization, emphasizing the integration of established theories with emerging technologies to drive sustainable engineering innovation.
Chapters in this book
- Frontmatter I
- Contents V
- Aim and scope VII
- Preface IX
- Acknowledgments
- About editors XIII
- List of contributing authors XV
- Chapter 1 Introduction to flow dynamics and heat transfer 1
- Chapter 2 Compressible fluid flow and heat transfer 29
- Chapter 3 Non-Newtonian fluid flow and heat transfer 59
- Chapter 4 Heat transfer in forced and natural convection 81
- Chapter 5 Numerical study of coupled partial differential equations in heat transfer problems with imprecisely defined parameters 91
- Chapter 6 Numerical approach to study the effect of uncertain spectrum of field variables in a porous cavity 107
- Chapter 7 Investigation of the thermal fluid system using direct numerical simulation 123
- Chapter 8 Dynamics of shock-accelerated V-shaped gas interface 139
- Chapter 9 Nonlinear and linear analyses of partially ionized plasma 155
- Chapter 10 Thermo-fluid behavior of electroosmotic flow in a hydrophobic microchannel under Joule heating and external fields 185
- Chapter 11 The study of oscillating water column energy device in a two-layer fluid system of finite impermeable depth 219
- Chapter 12 Data-driven prediction of thermal conductivity ratio in nanoparticle-enhanced 60:40 EG/water nanofluids 239
- Chapter 13 Industrial applications of flow dynamics and heat transfer 261
- Chapter 14 Optimization techniques in flow dynamics and heat transfer 301
- Chapter 15 Advanced optimization methods in flow dynamics 335
- Index 353
- De Gruyter Series in Advanced Mechanical Engineering
Chapters in this book
- Frontmatter I
- Contents V
- Aim and scope VII
- Preface IX
- Acknowledgments
- About editors XIII
- List of contributing authors XV
- Chapter 1 Introduction to flow dynamics and heat transfer 1
- Chapter 2 Compressible fluid flow and heat transfer 29
- Chapter 3 Non-Newtonian fluid flow and heat transfer 59
- Chapter 4 Heat transfer in forced and natural convection 81
- Chapter 5 Numerical study of coupled partial differential equations in heat transfer problems with imprecisely defined parameters 91
- Chapter 6 Numerical approach to study the effect of uncertain spectrum of field variables in a porous cavity 107
- Chapter 7 Investigation of the thermal fluid system using direct numerical simulation 123
- Chapter 8 Dynamics of shock-accelerated V-shaped gas interface 139
- Chapter 9 Nonlinear and linear analyses of partially ionized plasma 155
- Chapter 10 Thermo-fluid behavior of electroosmotic flow in a hydrophobic microchannel under Joule heating and external fields 185
- Chapter 11 The study of oscillating water column energy device in a two-layer fluid system of finite impermeable depth 219
- Chapter 12 Data-driven prediction of thermal conductivity ratio in nanoparticle-enhanced 60:40 EG/water nanofluids 239
- Chapter 13 Industrial applications of flow dynamics and heat transfer 261
- Chapter 14 Optimization techniques in flow dynamics and heat transfer 301
- Chapter 15 Advanced optimization methods in flow dynamics 335
- Index 353
- De Gruyter Series in Advanced Mechanical Engineering
