Lunar architecture and technology analysis driven by lunar science scenarios

NASA's Vision for Space Exploration and the missions it comprises pose large‐scale systems‐engineering problems with concomitant large‐budget investment decisions involving multiple disciplines (e.g., science, engineering, information technology), multiple constraints (e.g., time, mass, energy...

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Bibliographic Details
Published in:Systems engineering 2010-09, Vol.13 (3), p.217-231
Main Authors: Weisbin, Charles R., Mrozinski, Joseph, Lincoln, William, Elfes, Alberto, Shelton, Kacie, Hua, Hook, Smith, Jeffrey H., Adumitroaie, Virgil, Silberg, Robert
Format: Article
Language:English
Subjects:
Applied sciences
Architecture
astronaut-robot teams
Astronauts
Combinatorial analysis
Computer programs
Computer science
control theory
systems
Decision theory. Utility theory
Decisions
Exact sciences and technology
Information systems. Data bases
Inventory control, production control. Distribution
Lists
lunar mission planning
Mathematical analysis
Memory organisation. Data processing
Missions
multiagent planning
multiagent scheduling
NASA Vision for Space Exploration
Operational research and scientific management
Operational research. Management science
optimal space mission planning
Portfolio theory
Productivity
Software
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Summary:NASA's Vision for Space Exploration and the missions it comprises pose large‐scale systems‐engineering problems with concomitant large‐budget investment decisions involving multiple disciplines (e.g., science, engineering, information technology), multiple constraints (e.g., time, mass, energy consumption), myriad uncertainties, and a hierarchical structure of problem decomposition with resolution of increasing fidelity. Navigation through this sea of complexity is greatly facilitated by an analytical system that includes optimization and analysis software tools. The interplay between program planning and decision‐support tools is seen here in a case study of a hypothetical mission on the Moon. The architecture of one such tool, HURON, is discussed and its application is illustrated in a comparison of the relative productivity of employing two pressurized or two unpressurized robotic rovers with two pairs of astronauts to conduct a specified group of activities. For the mission scenarios studied, a pair of pressurized rovers is shown to be significantly more productive than a pair of unpressurized rovers when calculating work accomplished divided by marginal operational costs. The HURON decision‐support system presented and successfully applied in this paper deals explicitly with combinatorial explosion of a huge design space in scheduling the activities of agents subject to constraints, deploys a productivity function as a measure of value, and automatically determines a ranked sensitivity list of important inputs. The approach is applicable to a wide class of large‐scale systems‐engineering applications. © 2009 Wiley Periodicals, Inc. Syst Eng
ISSN:1098-1241
1520-6858
DOI:10.1002/sys.20144