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Lunar architecture and technology analysis driven by lunar science scenarios
Author(s) -
Weisbin Charles R.,
Mrozinski Joseph,
Lincoln William,
Elfes Alberto,
Shelton Kacie,
Hua Hook,
Smith Jeffrey H.,
Adumitroaie Virgil,
Silberg Robert
Publication year - 2010
Publication title -
systems engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.474
H-Index - 50
eISSN - 1520-6858
pISSN - 1098-1241
DOI - 10.1002/sys.20144
Subject(s) - space exploration , computer science , architecture , systems engineering , scheduling (production processes) , operations research , fidelity , industrial engineering , simulation , aerospace engineering , engineering , operations management , art , visual arts , telecommunications
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