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David W. Miller. Sondecker, George Ralph, IV Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics 2011-11-18T20:58:33Z 2011-11-18T20:58:33Z 2011 2011 http://hdl.handle.net/1721.1/67192 758670955 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 115-116). The objective of stochastic process design is to strategically identify, measure, and reduce sources of uncertainty to guide the development of complex systems. Fundamental to this design approach is the idea that system development is driven by measurable characteristics called quantities of interest. These quantities of interest collectively describe the state of system development and evolve as the system matures. This thesis provides context for the contributions of quantities of interest to a stochastic process view of complex system development using three space hardware development projects. The CASTOR satellite provides the opportunity for retrospective identification of quantities of interest and their evolution through time. As a complement to CASTOR, the preliminary design of the REXIS x-ray spectrometer provides the foundation for applying stochastic process approaches during the early phases of system development. Lastly, a spacecraft panel structural dynamics experiment is presented that illustrates analysis techniques commonly employed in stochastic process analysis. by George Ralph Sondecker, IV. S.M. 154 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Aeronautics and Astronautics. Identification and evolution of quantities of interest for a stochastic process view of complex space system development Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="04e0ea4e-4cf3-4e84-87fa-aeb63d3004e5"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Identification and evolution of quantities of interest for a stochastic process view of complex space system development</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2011</PublicationDate> <Authors> <Author> <DisplayName>Sondecker, George Ralph, IV</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Aeronautics and Astronautics.</Keyword> <Abstract>The objective of stochastic process design is to strategically identify, measure, and reduce sources of uncertainty to guide the development of complex systems. Fundamental to this design approach is the idea that system development is driven by measurable characteristics called quantities of interest. These quantities of interest collectively describe the state of system development and evolve as the system matures. This thesis provides context for the contributions of quantities of interest to a stochastic process view of complex system development using three space hardware development projects. The CASTOR satellite provides the opportunity for retrospective identification of quantities of interest and their evolution through time. As a complement to CASTOR, the preliminary design of the REXIS x-ray spectrometer provides the foundation for applying stochastic process approaches during the early phases of system development. Lastly, a spacecraft panel structural dynamics experiment is presented that illustrates analysis techniques commonly employed in stochastic process analysis.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>