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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.
Jean-Marc Depinay, Michel Caillaud, Remi Sentis
Nuclear Science and Engineering | Volume 152 | Number 1 | January 2006 | Pages 48-55
Technical Paper | doi.org/10.13182/NSE06-A2562
Articles are hosted by Taylor and Francis Online.
Application of the Monte Carlo method to deep-penetration transport problems often requires a biasing technique based on the use of an importance function. Here, in the framework of a multigroup model, we use an importance function in the form Ig([arrow over]x, [arrow over]) = eKg[arrow over].[arrow over]x[varphi]g([arrow over]), where g is the energy group index that ranges from 1 to G and [arrow over] is a vector usually fixed empirically. We describe an algorithm to find a good set of coefficients Kg and a good set of functions [varphi]g. To do this, we solve a system derived from the homogenous adjoint equations. We give two numerical examples where we show how these importance functions can enhance the accuracy of the computation.