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The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
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.
Jan Dufek, Waclaw Gudowski
Nuclear Science and Engineering | Volume 152 | Number 3 | March 2006 | Pages 274-283
Technical Paper | doi.org/10.13182/NSE06-2
Articles are hosted by Taylor and Francis Online.
A new adaptive stochastic approximation method for an efficient Monte Carlo calculation of steady-state conditions in thermal reactor cores is described. The core conditions that we consider are spatial distributions of power, neutron flux, coolant density, and strongly absorbing fission products like 135Xe. These distributions relate to each other; thus, the steady-state conditions are described by a system of nonlinear equations. When a Monte Carlo method is used to evaluate the power or neutron flux, then the task turns to a nonlinear stochastic root-finding problem that is usually solved in the iterative manner by stochastic optimization methods. One of those methods is stochastic approximation where efficiency depends on a sequence of stepsize and sample size parameters. The stepsize generation is often based on the well-known Robbins-Monro algorithm; however, the efficient generation of the sample size (number of neutrons simulated at each iteration step) was not published yet. The proposed method controls both the stepsize and the sample size in an efficient way; according to the results, the method reaches the highest possible convergence rate.