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DOE, General Matter team up for new fuel mission at Hanford
The Department of Energy's Office of Environmental Management (EM) on Tuesday announced a partnership with California-based nuclear fuel company General Matter for the potential use of the long-idle Fuels and Materials Examination Facility (FMEF) at the Hanford Site in Washington state.
According to the announcement, the DOE and General Matter have signed a lease to explore the FMEF's potential to be used for advanced nuclear fuel cycle technologies and materials, in part to help satisfy the predicted future requirements of artificial intelligence.
David B. Reister
Nuclear Science and Engineering | Volume 51 | Number 3 | July 1973 | Pages 316-323
Technical Paper | doi.org/10.13182/NSE73-A26608
Articles are hosted by Taylor and Francis Online.
A method for determining narrow upper and lower bounds for the fundamental eigenvalue of a nuclear reactor in either multigroup diffusion theory or transport theory has been developed. This method is based on the Barta-Polya theorem. The Barta-Polya theorem has been extended to yield bounds for multigroup diffusion theory eigenvalue problems. The trial function is a linear sum of known modes and unknown amplitude parameters. Determination of the optimum values of the parameters is a max-min problem of the type that occurs in optimum control and economics. To facilitate numerical computation, a coarse mesh is introduced. A computational method has been developed which quickly yields narrow eigenvalue bounds. Classical methods cannot determine optimum bounds since the function which is to be optimized is not differentiable at the max-min point. The bounds are determined using an iterative method. On each iteration the function is linearized about the mesh points, and linear programming is used to find the optimum solution to the approximate problem. Bounds have been found for a two-region, one-group diffusion theory problem and for a one-group transport theory problem. The bounds are superior to previous results and approach the exact solution as the number of terms in the trial function increases.