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dc.contributor.authorShahtaheri, Yasamanen_US
dc.date.accessioned2020-02-12T07:00:30Z
dc.date.available2020-02-12T07:00:30Z
dc.date.issued2018-08-20
dc.identifier.othervt_gsexam:16625en_US
dc.identifier.urihttp://hdl.handle.net/10919/96804
dc.description.abstractInfrastructures are the most fundamental facilities and systems serving the society. Due to the existence of infrastructures in economic, social, and environmental contexts, all lifecycle phases of such fundamental facilities should maximize utility for the designers, occupants, and the society. With respect to the nature of the decision problem, two main types of uncertainties may exist: 1) the aleatory uncertainty associated with the nature of the built environment (i.e., the economic, social, and environmental impacts of infrastructures must be described as probabilistic); and 2) the epistemic uncertainty associated with the lack of knowledge of decision maker utilities. Although a number of decision analysis models exist that consider the uncertainty associated with the nature of the built environment, they do not provide a systematic framework for including aleatory and epistemic uncertainties, and decision maker utilities in the decision analysis process. In order to address the identified knowledge gap, a three-phase modular decision analysis methodology is proposed. Module one uses a formal preference assessment methodology (i.e., utility function/indifference curve) for assessing decision maker utility functions with respect to a range of alternative design configurations. Module two utilizes the First Order Reliability Method (FORM) in a systems reliability approach for assessing the reliability of alternative infrastructure design configurations with respect to the probabilistic decision criteria and decision maker defined utility functions (indifference curves), and provides a meaningful feedback loop for improving the reliability of the alternative design configurations. Module three provides a systematic framework to incorporate both aleatory and epistemic uncertainties in the decision analysis methodology (i.e., uncertain utility functions and group decision making). The multi-criteria, probabilistic decision analysis framework is tested on a nine-story office building in a seismic zone with the probabilistic decision criteria of: building damage and business interruption costs, casualty costs, and CO2 emission costs. Twelve alternative design configurations and four decision maker utility functions under aleatory and epistemic uncertainties are utilized. The results of the decision analysis methodology revealed that the high-performing design configurations with an initial cost of up to $3.2M (in a cost range between $1.7M and $3.2M), a building damage and business interruption cost as low as $303K (in a cost range between $303K and $6.2M), a casualty cost as low as $43K (in a cost range between $43K and $1.2M), and a CO2 emission as low as $146K (in a cost range between $133K to $150K) can be identified by having a higher probability (i.e., up to 80%) of meeting the decision makers' preferences. The modular, holistic, decision analysis framework allows decision makers to make more informed performance-based design decisions—and allows designers to better incorporate the preferences of the decision makers—during the early design process.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectInfrastructureen_US
dc.subjectPerformance-Baseden_US
dc.subjectDesign Strategiesen_US
dc.subjectDecision Analysisen_US
dc.subjectMulti-Criteriaen_US
dc.subjectMulti-Objectiveen_US
dc.subjectOptimizationen_US
dc.subjectAleatory Uncertaintyen_US
dc.subjectEpistemic Uncertaintyen_US
dc.subjectSystem Reliabilityen_US
dc.subjectUtility Functionen_US
dc.subjectFirst Order Reliability Methoden_US
dc.titleA Probabilistic Decision Support System for a Performance-Based Design of Infrastructuresen_US
dc.typeDissertationen_US
dc.contributor.departmentCivil and Environmental Engineeringen_US
dc.description.degreePHDen_US
thesis.degree.namePHDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineCivil Engineeringen_US
dc.contributor.committeechairde la Garza, Jesus M.en_US
dc.contributor.committeechairFlint, Madeleine Marieen_US
dc.contributor.committeememberRodriguez-Marek, Adrianen_US
dc.contributor.committeememberWernz, Christianen_US


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