Thermally Driven Multi-Objective Packing Optimization Using a Dynamic Acceleration Field Methodology

Abstract

Multidisciplinary systems design is a complex and time-intensive process. Designers must often simultaneously consider a wide variety of different requirements, specifications, and constraints that must constantly be re-evaluated throughout the design process. As such, there is a demand in industry for efficient and cost-effective software solutions that will aid design teams throughout the multidisciplinary design process. The scope of this work covers a subset of multidisciplinary design problems: the packing optimization of a set of components considering heat transfer and thermal effects. The novel multi-physics multi-objective packing optimization algorithm presented in this work packs three-dimensional components into a user-defined design space while considering conduction, convection, and functionality constraints throughout the design process. Component temperature calculations are performed via the incorporation of commercial thermal finite element analysis (FEA) and computational fluid dynamics (CFD) software packages. The solver can consider a combination of one or more objectives, including the maximization of packing density, minimization of temperature variance, minimization of maximum component temperature, minimization of the offset from a desired center of mass, and the minimization of rotational inertia. Components are packed via the application of a set of dynamic acceleration fields designed to achieve these objectives, which drive component motion towards optimal positions and orientations. This thesis presents the theory, methodology, and mathematics behind the novel multi-objective packing optimization algorithm. The results of academic case studies, algorithm validation, and a real-world application are also included to demonstrate the effectiveness of the presented algorithm.