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Division Spotlight
Operations & Power
Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
Standards Program
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
Proving DRACO will deliver
The United States is now closer than it has been in over five decades to launching the first nuclear thermal rocket into space, thanks to DRACO—the Demonstration Rocket for Agile Cislunar Orbit.
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.