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dc.contributor.advisorOlivier L. de Weck.en_US
dc.contributor.authorSmaling, Rudolf Men_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.date.accessioned2008-03-26T20:30:54Z
dc.date.available2008-03-26T20:30:54Z
dc.date.copyright2005en_US
dc.date.issued2005en_US
dc.identifier.urihttp://dspace.mit.edu/handle/1721.1/28943en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/28943
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.en_US
dc.descriptionIncludes bibliographical references (leaves 183-191).en_US
dc.description.abstractA system architecture analysis and selection methodology is presented that builds on the Multidisciplinary Analysis and Optimization framework. It addresses a need and opportunity to extend the MAO techniques to include a means to analyze not only within the technical domain, but also include the ability to evaluate external influences that will act on the system once it is in operation. The nature and extent of these external influences is uncertain and increasingly uncertain for systems with long development timelines and methods for addressing such uncertainty are central to the thesis. The research presented in this document has culminated in a coherent system architecture analysis and selection process addressing this need that consists of several steps: 1. The introduction of the concept of Fuzzy Pareto Optimality. Under uncertainty, one must necessarily consider more than just Pareto Optimal solutions to avoid the unintentional exclusion of viable and possibly even desirable designs. 2. The introduction of a proximity based filtering technique that explicitly links the design and solution spaces. The intent here is preserve diverse designs, even if their resulting performance is similar. 3. Introduction of the concept of Technology Invasiveness through the use of a component Delta Design Structure Matrix (ADSM). The component DSM is used to evaluate the changes in the DSM due to the technology insertion. Based on the quantity and type of these changes a Technology Invasiveness metric is computed. 4. Through the use of utility curves, the technical domain analysis is linked to an analysis of external influence factors.en_US
dc.description.abstract(cont.) The shape of these curves depends wholly on the external influences that may act on the system once it is commercialized or otherwise put into use. The utility curves, in combination with the (technical) performance distributions, are then used to compute risk and opportunity for each system architecture. System Architecture selection follows from analysis in the technical domain linked to an analysis of external influences and their impact on system architecture potential for success. All of the concepts and the integrated process are developed and assessed in the context of a case which involves the study of a Hydrogen Enhanced Combustion Engine being studied for possible insertion into the vehicle fleet.en_US
dc.description.statementofresponsibilityby Rudolf M. Smaling.en_US
dc.format.extent214 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/28943en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.titleSystem architecture analysis and selection under uncertaintyen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc61232907en_US


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