Kacie Shelton

Comparison of Lunar Surface Mission Productivities as a Function of Mission Duration and Weighted Science Objectives

We formulate, model and analyze two proposed missions near the lunar south pole of different durations and scientific emphasis. Each mission is conducted by two teams of two astronauts riding in two pressurized rovers. Each team must remain within the same locality as the other team in case there is need for a rescue. Our analytical approach combines the best features of two analytic techniques, SciMax and HURON, to overcome difficulties of combinatorial explosiveness of the trade space, and to enable scheduling of “as much science as possible” rather than an inflexible set of experiments that may not make optimal use of available time. Weighting of individual science goals leads to different sets of scientific investigations and different amounts of time to be spent at the various sites. We demonstrate that increased rover driving speeds increases the amount of time available to spend at sites, and thus increases science productivity dramatically up to a point. Beyond that point, increasing driving speed improves productivity marginally due to the lack of availability of EVA time.

Technology assessment in support of the presidential vision for space exploration

This paper discusses the process and results of technology assessment in support of the United States vision for space exploration of the Moon, Mars and beyond. The paper begins by reviewing the presidential vision: a major endeavor in building systems of systems. It discusses why we wish to return to the Moon, and the exploration architecture for getting there safely, sustaining a presence, and safely returning. Next, a methodology for optimal technology investment is proposed with discussion of inputs including a capability hierarchy, mission importance weightings, available resource profiles as a function of time, likelihoods of development success, and an objective function. A temporal optimization formulation is offered, and the investment recommendations presented along with sensitivity analyses. Key questions addressed are sensitivity of budget allocations to cost uncertainties, reduction in available budget levels, and shifting funding within constraints imposed by mission timeline