An evaluation of Quantification of Margins and Uncertainties for a neutron radiography application

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Date

2020-08-11

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Ung, Annie

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Abstract

Quantification of Margins and Uncertainties (QMU) is a framework that was first introduced to understand the knowns and unknowns of an application. It is used to analyze the reliability of a system by evaluating its confidence ratio. This involves identifying, characterizing, and analyzing any thresholds, margins, and uncertainties that may influence a system’s functionality. To understand the importance of it, the QMU framework is applied to a neutron transport problem, specifically neutron radiography. This thesis showcases extensive work that has been done on neutron radiography at the University of Texas at Austin’s Thermal Neutron Imaging Facility (TNIF). Many parameters of the image quality of the radiographs were measured using an American Society for Testing and Materials (ASTM) standard. This experimental set-up was then simulated using MCNP 6.2, a radiation transport tool that originated from Los Alamos National Laboratory. Aspects pertaining to the radiograph standard were investigated further for the application of the QMU framework by evaluating both the experimental and simulation results. From this analysis, the lowest confidence ratio was found to be 11.3 and the highest was 376.2. These values are greater than 1 therefore this system is recognized as reliable. Areas with lower confidence ratios are more likely to experience failure so these regions should be avoided when imaging if at all possible.

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