A Resource Allocation Method for Achieving Optimal Reliability in a Lunar Architecture

In January 2005, President Bush announced the Vision for Space Exploration. This vision involved a progressive expansion of human capabilities beyond Low Earth Orbit beginning with a return to the moon starting no later than 2020. Current design processes utilized to meet this vision employ performance based trade studies to determine the lowest cost, highest reliability solution. In these design processes, designers trade independent performance variables and then calculate the design discriminators, reliability and costs, of the different architectures. The methodology implemented in this paper focuses on a concurrent evaluation of the performance, cost, and reliabilities of lunar architectures. This process directly addresses the top level requirements early in the design process and allows the decision maker to evaluate the highest reliability, lowest cost lunar architectures without being distracted by the performance details of the architecture. To achieve this methodology of bringing optimal cost and reliability solutions to the decision maker, parametric performance, cost, and reliability models are created to model each vehicle element. These models were combined using multidisciplinary optimization techniques and response surface equations to create parametric vehicle models which quickly evaluate the performance, reliability, and cost of the vehicles. These parametric models, known as ROSETTA models, combined with a life cycle cost calculator provide the tools necessary to create a lunar architecture simulation. The integration of the tools into an integrated framework that can quickly and accurately evaluate the lunar architectures is presented. This lunar architecture selection tool is verified and validated against the Apollo lunar architectures. The results of this lunar architecture selection tool are then combined into a Pareto frontier to guide the decision maker to producing the highest reliability architecture for a given life cycle cost. The advantages of this method over traditional design processes are numerous. With this presented methodology, the decision maker can transparently choose a lunar architecture solution based upon the high level design discriminators. This method can achieve significant reductions in life cycle costs keeping the same architecture reliability as a traditional design process point solution. This methodology also allows the decision maker to choose a solution which achieves a significant reduction in failure rate while maintaining the same life cycle costs as the point solution of a traditional design process.