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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.
Glenn E. Sjoden
Nuclear Science and Engineering | Volume 155 | Number 2 | February 2007 | Pages 179-189
Technical Paper | Mathematics and Computation, Supercomputing, Reactor Physics and Nuclear and Biological Applications | doi.org/10.13182/NSE07-A2655
Articles are hosted by Taylor and Francis Online.
A new exponential spatial differencing scheme based on zeroth spatial transport moments, the exponential directional iterative (EDI) Sn scheme for three-dimensional (3-D) Cartesian geometry, is presented. The EDI scheme is a logical extension of the positive, efficient exponential directional weighted (EDW) method used in the PENTRAN parallel Sn solver in an adaptive differencing strategy. The EDI scheme uses EDW-rendered exponential coefficients as initial values to begin a fixed-point iteration to refine exponential coefficients. Iterative refinement of these coefficients typically converged in fewer than four fixed-point iterations per ordinate, and yielded more accurate angular fluxes compared to other schemes tested. Overall, the EDI scheme is an order of magnitude more accurate than EDW, and two orders of magnitude more accurate than the legacy diamond zero (DZ) scheme for a given mesh. EDI is therefore a good candidate for a fourth-level scheme in the PENTRAN adaptive sequence. The 3-D Cartesian computational cost of EDI was ~20% more than EDW, and only ~40% more than DZ. Thus, EDI renders increased accuracy using zeroth spatial transport moments in a straightforward manner for any 3-D Cartesian code. More evaluation is ongoing to determine suitability in an upgraded adaptive differencing sequence algorithm in PENTRAN.