Fragnito, Andrea (2023) Optimization of Heat Transfer with novel approaches. [Tesi di dottorato]

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Abstract

In the field of thermal engineering and science, heat transfer problems are essential for designing and operating various systems. As these problems become more complex, the use of numerical tools becomes increasingly crucial. Different heat transfer mechanisms, including conduction, convection, and radiation, require tailored approaches for analysis and optimization. The choice between gradient-based methods and non-gradient-based techniques like genetic algorithms depends on the system's size and complexity. Large-scale systems, such as industrial heat exchangers and power plant components, benefit from genetic algorithms, which focus on optimizing parameters directly impacting thermal performance. They are efficient, scalable, and prioritize energy efficiency. Genetic algorithms excel in addressing highly complex heat transfer problems by navigating intricate design spaces effectively. In contrast, small-scale systems like microfluidic devices or compact electronic components demand precision, making gradient-based techniques, especially topology optimization, more suitable. Topology optimization allows to fine-tune every aspect of the system to achieve maximum heat transfer efficiency, offering flexibility in design and innovative form factors. The choice of optimization technique should align with the specific goals and constraints of the heat transfer problem, considering scale, complexity, and design requirements. This thesis provides a comprehensive analysis of various optimization choices for heat transfer devices, offering examples and case studies to enrich the understanding of tools and techniques applicable to different systems and heat transfer mechanisms.

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