skip to main content

DOE PAGESDOE PAGES

Title: Benefits of utilizing CellProfiler as a characterization tool for U-10Mo nuclear fuel

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium-molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellular measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed bymore » automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries.« less
Authors:
 [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2]
  1. Colorado School of Mines, Golden, CO (United States)
  2. Idaho National Lab. (INL), Idaho Falls, ID (United States)
Publication Date:
OSTI Identifier:
1184724
Report Number(s):
INL/JOU--14-32389
Journal ID: ISSN 1044-5803
Grant/Contract Number:
AC07-05ID14517
Type:
Accepted Manuscript
Journal Name:
Materials Characterization
Additional Journal Information:
Journal Volume: 105; Journal ID: ISSN 1044-5803
Publisher:
Elsevier
Research Org:
Idaho National Laboratory (INL), Idaho Falls, ID (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS; 97 MATHEMATICS AND COMPUTING cell Profiler; focused ion beam