Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel
- Nuclear Science and Engineering Program, Colorado School of Mines, 1500 Illinois St, Golden, CO 80401 (United States)
- Nuclear Fuels and Materials Division, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-6188 (United States)
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 by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries. - Graphical abstract: Display Omitted - Highlights: • A technique is developed to score U–10Mo FIB-SEM image quality using CellProfiler. • The pass/fail metric is based on image illumination, focus, and area scratched. • Automated image analysis is performed in pipeline fashion to characterize images. • Fission gas void, interaction layer, and grain boundary coverage data is extracted. • Preliminary characterization results demonstrate consistency of the algorithm.
- OSTI ID:
- 22476112
- Journal Information:
- Materials Characterization, Vol. 105; Other Information: Copyright (c) 2015 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 1044-5803
- Country of Publication:
- United States
- Language:
- English
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