| The following dissertation investigates the development of a methodology suitable for the evaluation of advanced propulsion concepts. At early stages of development, both the future performance of these concepts and their requirements are highly uncertain, making it difficult to forecast their future value. Developing advanced propulsion concepts requires a huge investment of resources. The methodology was developed to enhance the decision-makers understanding of the concepts, so that they could mitigate the risks associated with developing such concepts.; A systematic methodology to identify potential advanced propulsion concepts and assess their robustness is necessary to reduce the risk of developing advanced propulsion concepts. Existing advanced design methodologies have evaluated the robustness of technologies or concepts to variations in requirements, but they are not suitable to evaluate a large number of dissimilar concepts. Variations in requirements have been shown to impact the development of advanced propulsion concepts, and any method designed to evaluate these concepts must incorporate the possible variations of the requirements into the assessment. In order to do so, a methodology was formulated to be capable of accounting for two aspects of the problem. First, it had to systemically identify a probabilistic distribution for the future requirements. Such a distribution would allow decision-makers to quantify the uncertainty introduced by variations in requirements. Second, the methodology must be able to assess the robustness of the propulsion concepts as a function of that distribution.; This dissertation describes in depth these enabling elements and proceeds to synthesize them into a new method, the Evolving Requirements Technology Assessment (ERTA). As a proof of concept, the ERTA method was used to evaluate and compare advanced propulsion systems that will be capable of powering a hurricane tracking, High Altitude, Long Endurance (HALE) unmanned aerial vehicle (UAV). The use of the ERTA methodology to assess HALE UAV propulsion concepts demonstrated that potential variations in requirements do significantly impact the assessment and selection of propulsion concepts. The proof of concept also demonstrated that traditional forecasting techniques, such as the cross impact analysis, could be used to forecast the requirements for advanced propulsion concepts probabilistically. "Fitness", a measure of relative goodness, was used to evaluate the concepts. Finally, stochastic optimizations were used to evaluate the propulsion concepts across the range of requirement sets that were considered. |