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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.
Bart L. Sjenitzer, J. Eduard Hoogenboom
Nuclear Science and Engineering | Volume 175 | Number 1 | September 2013 | Pages 94-107
Technical Paper | doi.org/10.13182/NSE12-44
Articles are hosted by Taylor and Francis Online.
In nuclear reactor physics, deterministic and hybrid calculation methods dominate the field of transient analysis. This implies that important safety assessments are subject to many approximations, which are needed by these methods. This paper proposes the Dynamic Monte Carlo method (Dynamic MC), which solves the coupled Boltzmann and kinetic equations with exact geometry and continuous energy, using only Monte Carlo techniques.For Dynamic MC a number of new techniques are developed, e.g., precursor tracking, forced decay for precursors, and the branchless method. Also, the particle source of the simulation has to be determined differently from what is current standard Monte Carlo practice, and the simulation scheme is adapted.A few example cases are simulated, demonstrating the effectiveness of Dynamic MC. The sample cases vary from simple homogeneous systems to full fuel assemblies with an asymmetric flux profile during the transient. Since Dynamic MC is implemented in the general-purpose Monte Carlo code Tripoli, it can be applied to any geometry.