This chapter considers the design of thermal systems, focusing on simulation, feasible design, and optimization. Though most thermal systems have been modeled and simulated extensively, the results obtained have, in many cases, not been used to design and optimize the process. This chapter reviews the basic concepts of design of thermal systems, based on simulation as well as experimentation, and discusses strategies that may be employed to design and optimize the system. Many complexities, such as strong property variations, complicated domains, conjugate mechanisms, chemical reactions, and intricate boundary conditions, are often encountered in practical thermal processes and systems. The basic approaches that may be used to accurately simulate these systems are outlined. The link between the process and the resulting output is critical, particularly in areas like manufacturing. Thus it is important to couple the modeling and experimental data with the performance and design of the system. Optimization in terms of the operating conditions, as well as of the system hardware, is needed to minimize costs and enhance product quality and system performance. Different optimization strategies that are currently available and that may be used for thermal systems are outlined. Several practical processes from a wide range of applications, such as manufacturing, thermal management of electronic systems, energy, environment, and security, are considered in greater detail to illustrate these approaches, as well as to present typical simulation and design results. Validation of the mathematical and numerical model is particularly important and is discussed in terms of existing results, as well as new experimental data. Similarly, feasibility of the process, choice of operating conditions from inverse solutions, knowledge-based design, combined experimental and numerical inputs for design, sensitivity, uncertainty, and other important aspects are presented. Most thermal systems have more than one objective of interest, leading to multi-objective optimization, which is briefly presented. The current state of the art and future needs in design of thermal systems are discussed.
All Science Journal Classification (ASJC) codes