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Title: Uncertainty Quantification - Lecture 2.


Abstract not provided.

Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the UQ Lecture to be posted online.
Country of Publication:
United States

Citation Formats

Debusschere, Bert, and Sargsyan, Khachik. Uncertainty Quantification - Lecture 2.. United States: N. p., 2015. Web.
Debusschere, Bert, & Sargsyan, Khachik. Uncertainty Quantification - Lecture 2.. United States.
Debusschere, Bert, and Sargsyan, Khachik. 2015. "Uncertainty Quantification - Lecture 2.". United States. doi:.
title = {Uncertainty Quantification - Lecture 2.},
author = {Debusschere, Bert and Sargsyan, Khachik},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2015,
month = 2

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  • Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRTmore » to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.« less
  • Abstract not provided.
  • This paper presents an overview of a methodology developed to quantify reactor safety computer code uncertainty. The methodology development program is supported by the Idaho National Engineering Laboratory (INEL), and Los Alamos National Laboratory (LANL) and is sponsored by the United States Nuclear Regulatory Commission (USNRC). The method addresses code minus experimental data differences from scaled facilities and provides a systematic extension of the scaled uncertainty statements to a full scale code application. Conclusions are made relative to the application of the method, interpretation of the results, and method limitations.
  • An EPRI project to quantify boresonic inspection uncertainty and to evaluate available boresonic inspection systems by comparing inspection results with natural defect characteristics has been completed. Two high-temperature, 1CrMoV steam turbine rotors retired from service because of unacceptable boresonic indications were selected for the project. Both rotors were thoroughly inspected utilizing non-focused, conventional boresonic systems plus one system utilizing focused, immersion boresonic technology. Additional inspections were conducted on a series of bore blocks with known artificial reflectors to help quantify the size of the indications detected in the rotors. Following boresonic characterization by all participating systems, a number of near-boremore » indications in the rotors were selected for destructive evaluation. The rotors were sectioned to extract twenty-one ultrasonic indications, and the coupons containing the indications were subjected to progressive sectioning and polishing for detailed metallographic characterization of the indications. Reflectors responsible for ultrasonic indications were evaluated under magnification to determine their axial, radial, and azimuthal dimensions. Metallurgical results from a small but representative sample of the indications analyzed are compared with boresonic data acquired from the selected indications. Results from the focused immersion system and the broad-beam contact systems correlated well with results obtained by destructive sectioning. A sizing factor of 2 is appropriate on the radial dimension of indications. No service-induced cracks were found. These indications were due to nonmetallic inclusion clusters and linear stringers which formed during the initial ingot manufacturing process.« less