Doctoral Dissertations

Author

Jia Guo

Abstract

"The objective of this research is to quantify the impact of both aleatory and epistemic uncertainties on performances of multidisciplinary systems. Aleatory uncertainty comes from the inherent uncertain nature and epistemic uncertainty comes from the lack of knowledge. Although intensive research has been conducted on aleatory uncertainty, few studies on epistemic uncertainty have been reported. In this work, the two types of uncertainty are analyzed. Aleatory uncertainty is modeled by probability distributions while epistemic uncertainty is modeled by intervals. Probabilistic analysis (PA) and interval analysis (IA) are integrated to capture the effect of the two types of uncertainty. The First Order Reliability Method is employed for PA while nonlinear optimization is used for IA. The unified uncertainty analysis, which consists of PA and IA, is employed to develop new sensitivity analysis methods for the mixture of the two types of uncertainty. The methods are able to quantify the contribution of each input variable with either epistemic uncertainty or aleatory uncertainty. The analysis results can then help better decision making on how to effectively mitigate the effect of uncertainty. The other major contribution of this research is the extension of the unified uncertainty analysis to the reliability analysis for multidisciplinary systems"--Abstract, page iv.

Advisor(s)

Du, Xiaoping

Department(s)

Mechanical and Aerospace Engineering

Degree Name

Ph. D. in Mechanical Engineering

Sponsor(s)

National Science Foundation (U.S.)
University of Missouri Research Board

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2008

Journal article titles appearing in thesis/dissertation

  • Sensitivity analysis with the mixture of epistemic and aleatory uncertainty
  • Reliability sensitivity analysis with random and interval variables
  • Reliability analysis for multidisciplinary systems with random and interval variables

Pagination

xii, 161 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2008 Jia Guo, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Epistemics
First-order logic
Random variables
Sensitivity theory (Mathematics)
Uncertainty -- Mathematics

Thesis Number

T 9456

Print OCLC #

355568005

Electronic OCLC #

355601523

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