A decomposition methodology based on the concept of "thermoeconomic isolation" applied to the synthesis/design and operational optimization of an advanced tactical fighter aircraft is the focus of this research. Conceptual, time, and physical decomposition were used to solve the system-level as well as unit-level optimization problems. The total system was decomposed into five sub-systems as follows: propulsion sub-system (PS), environmental control sub-system (ECS), fuel loop sub-system (FLS), vapor compressor and PAO loops sub-system (VC/PAOS), and airframe sub-system (AFS) of which the AFS is a non-energy based sub-system. Configurational optimization was applied. Thus, a number of different configurations for each sub-system were considered. The most promising set of candidate configurations, based on both an energy integration analysis and aerodynamic performance, were developed and detailed thermodynamic, geometric, physical, and aerodynamic models at both design and off-design were formulated and implemented. A decomposition strategy called Iterative Local-Global Optimization (ILGO) developed by Muñoz and von Spakovsky was then applied to the synthesis/design and operational optimization of the advanced tactical fighter aircraft. This decomposition strategy is the first to successfully closely approach the theoretical condition of "thermoeconomic isolation" when applied to highly complex, highly dynamic non-linear systems. This contrasts with past attempts to approach this condition, all of which were applied to very simple systems under very special and restricted conditions such as those requiring linearity in the models and strictly local decision variables. This is a major advance in decomposition and has now been successfully applied to a number of highly complex and dynamic transportation and stationary systems. This thesis work presents the detailed results from one such application, which additionally considers a non-energy based sub-system (AFS). / Master of Science

Enhanced Finned-Tube Condenser Design and Optimization Susan W. Stewart 173 pages Directed by Dr. Sam V. Shelton Finned-tube heat exchangers are widely used in space conditioning systems, as well as any other application requiring heat exchange between liquids and gases. Their most widespread use is in residential air conditioning systems. Residential systems dictate peak demand on the U.S. national grid, which occurs on the hot summer afternoons, and thereby sets the expensive infrastructure requirement of the nations power plant and electrical distribution system. In addition to peak demand, residential air conditioners are major energy users that dominate residential electrical costs and environmental impact. The only significant opportunity for electrical power use reduction of residential air conditioners is in technology improvement of the finned-tube heat exchangers, i.e., condenser and evaporator coils. With the oncoming redesign of these systems in the next five years to comply with the regulatory elimination of R-22 used in residential air conditioners today, improvement in the design technology of these systems is timely. An air conditioner condenser finned-tube coil design optimization methodology is derived and shown to lead to improved residential air conditioner efficiency at fixed equipment cost. This nonlinear optimization of the 14 required design parameters is impractical by systematic experimental testing and iteration of tens of thousands condenser coils in an air conditioning system. The developed methodology and results can be used in the redesign of residential systems for the new mandated environmentally friendly refrigerants and to meet increasing regulatory minimum system efficiencies. Additionally, plain fins and augmented fins, (louvered), are compared using the developed model and optimization scheme to show the effect of the augmentation on system performance. Furthermore, an isolated condenser model was developed using condenser entropy generation minimization as the figure of merit to minimize the model complexity and computation time. Isolated model optimizations are compared with the system model optimum designs.