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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.
Floyd Gelhaus, John Hallam, Tor Sauar
Nuclear Science and Engineering | Volume 64 | Number 2 | October 1977 | Pages 684-693
Technical Paper | doi.org/10.13182/NSE77-A27400
Articles are hosted by Taylor and Francis Online.
The level of reliability of fuel rods operating in commercial nuclear power plants has been less than desired for a number of reasons. Several of these causes have been successfully minimized, but pellet-clad interaction failures persist. Since power and power change are dominant parameters in this failure mode, restrictions on operational maneuvers have been recommended by all U.S. fuel suppliers. Slower-than-design-allowable maneuvers decrease the plant capacity factor, which can cost a utility up to $7 million per year per plant. To assist utility engineering and operations personnel in their day-to-day decisions in this regard, the Electric Power Research Institute (EPRI) is initiating a project, designated RP895, to develop a fully computerized Power Shape Monitoring System (PSMS) for core-wide fuel rod reliability prediction. This paper describes the PSMS system and details some of the hardware/software requirements as they are now perceived. Salient results from a just-completed complementary EPRI-funded study, RP509, are described; this effort employed hand data acquisition and many man-machine interfaces that will be fully integrated and automated in the PSMS. The capabilities of the PSMS will derive from the use of modern minicomputer hardware and software and from accurate computational modules that enable near-real-time predictive capability.