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2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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Front-end nuclear fuel supply cooperation: Turning allied interdependence into strategic advantage
The global nuclear revival, which is fueled by unprecedented demand for firm, affordable, dispatchable power for artificial intelligence and data center build-out, energy security imperatives, and climate commitments, has exposed a structural reality of the Western fuel cycle: No single allied nation currently possesses the full suite of front-end capabilities. From mining through conversion, enrichment, fabrication, and the emerging deconversion and metallization steps required for reactor fuels, capability is distributed across Canada, France, Japan, the United Kingdom, and the United States (collectively, the “Sapporo Five”), as well as a small group of close partners.
Warren F. Witzig, Ross T. Thomas
Nuclear Science and Engineering | Volume 69 | Number 2 | February 1979 | Pages 251-263
Technical Paper | doi.org/10.13182/NSE79-A20615
Articles are hosted by Taylor and Francis Online.
Multidimensional linear regression analysis is employed as a modeling technique for the prediction of boiling water reactor (BWR) shutdown margin reactivity. A comparison is made between the best models developed using regression analysis and the General Electric (GE) three-dimensional BWR core simulator code. The GE code is based on one-group diffusion theory, and its accuracy is verified by comparison with experimental data. One use of this code is the calculation of shutdown margin throughout a fuel cycle, but it requires a large computing facility not located at a reactor site. The regression models give an approximation of a core's shutdown margin based on current core physics parameters. The method can be utilized at a BWR plant site to provide information demonstrating compliance with license and technical specification requirements. The results obtained by regression predictions for the two cores studied compare favorably with current industry methods. After establishing a regression model, predictions can be made at a reactor site using a pocket calculator.