Quantified PIRT and uncertainty quantification for computer code validation Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/2801pm91c

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • This study is intended to investigate and propose a systematic method for uncertainty quantification for the computer code validation application. Uncertainty quantification has gained more and more attentions in recent years. U.S. Nuclear Regulatory Commission (NRC) requires the use of realistic best estimate (BE) computer code to follow the rigorous Code Scaling, Application and Uncertainty (CSAU) methodology. In CSAU, the Phenomena Identification and Ranking Table (PIRT) was developed to identify important code uncertainty contributors. To support and examine the traditional PIRT with quantified judgments, this study proposes a novel approach, the Quantified PIRT (QPIRT), to identify important code models and parameters for uncertainty quantification. Dimensionless analysis to code field equations to generate dimensionless groups (Π groups) using code simulation results serves as the foundation for QPIRT. Uncertainty quantification using DAKOTA code is proposed in this study based on the sampling approach. Nonparametric statistical theory identifies the fixed number of code run to assure the 95 percent probability and 95 percent confidence in the code uncertainty intervals.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Keyword
Subject
Rights Statement
Peer Reviewed
Language
Replaces

Relationships

In Administrative Set:
Last modified: 10/27/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items