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Education, Training & Workforce Development
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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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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
NRC approves subsequent license renewal for Oconee
All three units at the Duke Energy’s Oconee nuclear power plant in South Carolina are now licensed to operate for an additional 20 years.
Troy L. Becker, Allan B. Wollaber, Edward W. Larsen
Nuclear Science and Engineering | Volume 155 | Number 2 | February 2007 | Pages 155-167
Technical Paper | Mathematics and Computation, Supercomputing, Reactor Physics and Nuclear and Biological Applications | doi.org/10.13182/NSE07-A2653
Articles are hosted by Taylor and Francis Online.
A new hybrid Monte Carlo-Deterministic technique is presented for simulating global particle transport problems, in which flux estimates are desired at all physical locations in the system. This technique has two steps: First, an inexpensive deterministic global estimate of the forward flux is obtained; then Monte Carlo is used to estimate the multiplicative correction to the deterministic flux estimate. We call the multiplicative correction to the deterministic flux the correcton flux, and the Monte Carlo particles that estimate this flux correctons. For deep-penetration problems, the correcton flux has significantly less spatial variation than the physical flux. Therefore, the Monte Carlo process automatically distributes correctons much more uniformly across the system than it distributes Monte Carlo particles for the original angular flux. In the "deep" parts of the problem, at locations far from the source, this results in a greatly reduced variance and a greatly increased figure of merit.