New method for analysis of X-ray computed tomography scans of TRISO fuel forms
Abstract
X-ray computed tomography (XCT) is a powerful characterization tool that has been used for examination of both tristructural-isotropic (TRISO) coated particles and fuel forms. Rapid, nondestructive imaging of complete specimens by XCT provides significant characterization advantages in both speed and comprehensiveness over traditional materialographic methods. This paper discusses a method that has been developed to analyze XCT images of pebble fuel forms containing ~18,000 TRISO particles each. The XCT images are three-dimensional with contrast based on relative x-ray transparency. In the case of TRISO fuel forms, XCT image intensity distinguishes between the high-density kernel, the medium-density SiC, and the low-density matrix and carbon layers. Image analysis software has been developed to process XCT data sets to extract spatial distribution information, including particle nearest-neighbor distances, local packing fraction, and fuel-free zone thickness in TRISO fuel forms. Finally, although this type of high-resolution XCT analysis is likely not feasible as a quality control measurement for commercial TRISO fuel, it is highly useful in generating feedback for the development of fuel form fabrication processes.
- Authors:
-
[1];
[1];
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); X Energy LLC, Greenbelt, MD (United States)
- X Energy LLC, Greenbelt, MD (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Nuclear Energy (NE)
- OSTI Identifier:
- 1649605
- Alternate Identifier(s):
- OSTI ID: 1646729
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nuclear Engineering and Design
- Additional Journal Information:
- Journal Volume: 357; Journal ID: ISSN 0029-5493
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS
Citation Formats
Helmreich, Grant, Hunn, John D., Brown, Daniel, and Blamer, Brandon. New method for analysis of X-ray computed tomography scans of TRISO fuel forms. United States: N. p., 2019.
Web. doi:10.1016/j.nucengdes.2019.110418.
Helmreich, Grant, Hunn, John D., Brown, Daniel, & Blamer, Brandon. New method for analysis of X-ray computed tomography scans of TRISO fuel forms. United States. https://doi.org/10.1016/j.nucengdes.2019.110418
Helmreich, Grant, Hunn, John D., Brown, Daniel, and Blamer, Brandon. Wed .
"New method for analysis of X-ray computed tomography scans of TRISO fuel forms". United States. https://doi.org/10.1016/j.nucengdes.2019.110418. https://www.osti.gov/servlets/purl/1649605.
@article{osti_1649605,
title = {New method for analysis of X-ray computed tomography scans of TRISO fuel forms},
author = {Helmreich, Grant and Hunn, John D. and Brown, Daniel and Blamer, Brandon},
abstractNote = {X-ray computed tomography (XCT) is a powerful characterization tool that has been used for examination of both tristructural-isotropic (TRISO) coated particles and fuel forms. Rapid, nondestructive imaging of complete specimens by XCT provides significant characterization advantages in both speed and comprehensiveness over traditional materialographic methods. This paper discusses a method that has been developed to analyze XCT images of pebble fuel forms containing ~18,000 TRISO particles each. The XCT images are three-dimensional with contrast based on relative x-ray transparency. In the case of TRISO fuel forms, XCT image intensity distinguishes between the high-density kernel, the medium-density SiC, and the low-density matrix and carbon layers. Image analysis software has been developed to process XCT data sets to extract spatial distribution information, including particle nearest-neighbor distances, local packing fraction, and fuel-free zone thickness in TRISO fuel forms. Finally, although this type of high-resolution XCT analysis is likely not feasible as a quality control measurement for commercial TRISO fuel, it is highly useful in generating feedback for the development of fuel form fabrication processes.},
doi = {10.1016/j.nucengdes.2019.110418},
journal = {Nuclear Engineering and Design},
number = ,
volume = 357,
place = {United States},
year = {2019},
month = {11}
}
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Works referenced in this record:
Qualification of HTR pebbles by X-ray tomography and thermal analysis
journal, October 2012
- Hania, P. R.; Janssen, B.; Fedorov, A. V.
- Nuclear Engineering and Design, Vol. 251
Fabrication and characterization of driver-fuel particles, designed-to-fail fuel particles, and fuel compacts for the US AGR-3/4 irradiation test
journal, May 2014
- Hunn, John D.; Lowden, Richard A.; Miller, James H.
- Nuclear Engineering and Design, Vol. 271
Nondestructive measurement of the weight of kernels in a simulated cylindrical fuel compact for HTGR using X-ray computed tomography
journal, September 2011
- Kim, Woong Ki; Lee, Young Woo; Cho, Moon Sung
- Nuclear Engineering and Design, Vol. 241, Issue 9
Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography
journal, June 2015
- Lowe, T.; Bradley, R. S.; Yue, S.
- Journal of Nuclear Materials, Vol. 461
Topographic distance and watershed lines
journal, July 1994
- Meyer, Fernand
- Signal Processing, Vol. 38, Issue 1
A Threshold Selection Method from Gray-Level Histograms
journal, January 1979
- Otsu, Nobuyuki
- IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, Issue 1
The DOE advanced gas reactor fuel development and qualification program
journal, September 2010
- Petti, David; Maki, John; Hunn, John
- JOM, Vol. 62, Issue 9
3D Nondestructive Visualization and Evaluation of TRISO Particles Distribution in HTGR Fuel Pebbles Using Cone-Beam Computed Tomography
journal, January 2017
- Yu, Gongyi; Du, Yi; Xiang, Xincheng
- Science and Technology of Nuclear Installations, Vol. 2017