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The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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Strontium: Supply-and-demand success for the DOE’s Isotope Program
The Department of Energy’s Isotope Program (DOE IP) announced last week that it would end its “active standby” capability for strontium-82 production about two decades after beginning production of the isotope for cardiac diagnostic imaging. The DOE IP is celebrating commercialization of the Sr-82 supply chain as “a success story for both industry and the DOE IP.” Now that the Sr-82 market is commercially viable, the DOE IP and its National Isotope Development Center can “reassign those dedicated radioisotope production capacities to other mission needs”—including Sr-89.
Geun-Sun Auh
Nuclear Science and Engineering | Volume 118 | Number 3 | November 1994 | Pages 186-193
Technical Paper | doi.org/10.13182/NSE94-A19384
Articles are hosted by Taylor and Francis Online.
Among the three digital dynamic compensation methods that are developed for or applied to the rhodium self-powered neutron detector—the dominant pole Tustin method of the core operating limit supervisory system, the direct inversion method, and the Kalman filter method—the best method is selected. The direct inversion method is slightly improved from the previous version, and the Kalman filter method is proposed. The simulation results show that the direct inversion method is better than the dominant pole Tustin method, but the best compensation results can be obtained from the Kalman filter method. The direct inversion method gives better results than the dominant pole Tustin method because it does not contain the assumption of a single pole and zero. The Kalman filter method is the best among the three methods because it uses the information of previous time steps throughout its estimation process.