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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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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
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Taro Ueki
Nuclear Science and Engineering | Volume 180 | Number 1 | May 2015 | Pages 58-68
Technical Paper | doi.org/10.13182/NSE14-54
Articles are hosted by Taylor and Francis Online.
The overlapping batch means method (OBM) has been investigated for robust statistical error estimation of local power tallies in Monte Carlo (MC) reactor core calculation. Originally, a nonoverlapping version was introduced in MC criticality calculation by Gelbard and Prael. However, the issue of batch size optimization was thought of as a lack of robustness. In this work, OBM with asymptotic bias correction was implemented with the batch size of the square root of the number of generations and compared with the orthonormally weighted standardized time series method (OWSTS). Numerical tests were conducted for various positions of the core of a pressurized water reactor. Results obtained indicate that neither OBM nor OWSTS consistently outperforms the other in terms of an overall performance measure incorporating bias and stability. Therefore, OBM with asymptotic bias correction can be an option to statistical error estimation in production MC criticality codes since OWSTS lacks an automated process to determine the number of weighting functions and can output the estimate only at the final generation. It is also shown that OBM with asymptotic bias correction performs equally regardless of the batch size.