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dc.contributor.advisorGregory J. McRae.en_US
dc.contributor.authorCano Ruiz, José Alejandro, 1969-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Chemical Engineering.en_US
dc.date.accessioned2005-05-19T14:29:28Z
dc.date.available2005-05-19T14:29:28Z
dc.date.issued1999en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/16758
dc.descriptionThesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1999.en_US
dc.descriptionElectronic version available online.en_US
dc.description"September 2000."en_US
dc.descriptionIncludes bibliographical references.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.description.abstractThe environment has emerged as an important determinant of the performance of the modern chemical industry. Process engineering in the 21st century needs to evolve to include environmental issues as part of the design objectives, rather than as constraints on operations. A frequently cited objection to the use of quantitative indicators of environmental performance in product and process design is that the underlying data are too uncertain for the numbers to have any real meaning. This thesis demonstrates that explicit incorporation of uncertainties allows bounds to be established on the confidence of decisions made on the basis of uncertain indicators. The examples provided show that large uncertainties in indicators used to assess environmental performance do not necessarily imply uncertainty in decision-making. A series of computer-aided decision making tools have been developed to decrease the barriers to the use of environmental valuation functions in routine design activities. These tools include: uncertainty propagation of relative performance measures, a spreadsheet-based fate, transport and exposure model for chemicals, an information content chart for assessing the quality of uncertain indicators, a screening procedure to identify the most important structural and parametric uncertainties in multimedia exposure models,en_US
dc.description.abstracta process by product input-output life cycle assessment method to generate correlated distributions of unit environmental indicators, an extension of the deterministic equivalent modeling method for the generation of spreadsheet based polynomial chaos expansion metamodels of process flowsheet models, and a database for managing uncertain parameters used in environmental valuation models. Case studies are presented to help the reader in learning the use of the tools. The tools are also applied to an analysis of the U.S. toxics release inventory, in which confidence bounds are developed for the trends in impacts and the contributions of industrial sectors and specific chemical compounds to overall potential impact. Although the tools were developed bearing in mind the need for methods to evaluate the environmental performance of chemical process design alternatives, the ideas can be applied to any decision context in which there are significant uncertainties in the parameters of the objective function.en_US
dc.description.statementofresponsibilityby José Alejandro Cano Ruiz.en_US
dc.format.extent599 p.en_US
dc.format.extent16584894 bytes
dc.format.extent16584611 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
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/1721.1/7582
dc.subjectChemical Engineering.en_US
dc.titleDecision support tools for environmentally conscious chemical process designen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineering
dc.identifier.oclc48460440en_US


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