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dc.contributor.advisorGeorge E. Apostolakis.en_US
dc.contributor.authorElliott, Michael A. (Michael Alfred)en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Nuclear Science and Engineering.en_US
dc.date.accessioned2011-05-09T15:20:28Z
dc.date.available2011-05-09T15:20:28Z
dc.date.copyright2010en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/62690
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2010.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 104-107).en_US
dc.description.abstractRisk-informed decision-making (RIDM) is a formal process that assists stakeholders make decisions in the face of uncertainty. At MIT, a tool known as the Analytic Deliberative Decision Making Process (ADP) has been under development for a number of years to provide an efficient framework for implementing RIDM. ADP was initially developed as a tool to be used by a small group of stakeholders but now it has become desirable to extend ADP to an engineering scale that can be used by many individual across large organizations. This dissertation identifies and addresses four challenges in extended the ADP to an engineering scale. Rigorous preference elicitation using pairwise comparisons is addressed. A new method for judging numerical scales used in these comparisons is presented along with a new type of scale. This theory is tested by an experiment involving 64 individuals and it is found that the optimal scale is a matter of individual choice. The elicitation of expert opinion is studied and a process that adapts to the complexity of the decision at hand is proposed. This method is tested with a case study involving the choice of a heat removal technology for a new type of fission reactor. Issues related to the unique informational needs of large organizations are investigated and new tools to handle these needs are developed. Finally, difficulties with computationally intensive modeling and simulation are identified and a new method of uncertainty propagation using orthogonal polynomials is explored. Using a code designed to investigate the LOCA behavior of a fission reactor, it is demonstrated that this new propagation methods offers superior convergence over existing techniques.en_US
dc.description.statementofresponsibilityby Michael A. Elliott.en_US
dc.format.extent126 p.en_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/1721.1/7582en_US
dc.subjectNuclear Science and Engineering.en_US
dc.titleContributions to risk-informed decision makingen_US
dc.title.alternativeContributions to RIDMen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering
dc.identifier.oclc714407608en_US


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