Rule-based graph theory to enable exploration of the space system architecture design space

NASA's current plans for human spaceflight include an evolutionary series of missions based on a steady increase in capability to explore cis-lunar space, the Moon, near-Earth asteroids, and eventually Mars. Although the system architecture definition has the greatest impact on the eventual performance and cost of an exploration program, selecting an optimal architecture is a difficult task due to the lack of methods to adequately explore the architecture design space and the resource-intensive nature of architecture analysis. This research presents a modeling framework to mathematically represent and analyze the space system architecture design space using graph theory. The framework enables rapid exploration of the design space without the need to limit trade options or the need for user interaction during the exploration process. The architecture design space for three missions in a notional evolutionary exploration program, which includes staging locations, vehicle implementation, and system functionality, for each mission destination is explored. Using relative net present value of various system architecture options, the design space exploration reveals that the launch vehicle selection is the primary driver in reducing cost, and other options, such as propellant type, staging location, and aggregation strategy, provide less impact.Ph