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Division Spotlight
Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
Meeting Spotlight
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
College students help develop waste-measuring device at Hanford
A partnership between Washington River Protection Solutions (WRPS) and Washington State University has resulted in the development of a device to measure radioactive and chemical tank waste at the Hanford Site. WRPS is the contractor at Hanford for the Department of Energy’s Office of Environmental Management.
Bingbing Ji, Zhiping Chen, Jia Liu, Liangzhi Cao, Zhuojie Sui, Hongchun Wu
Nuclear Science and Engineering | Volume 195 | Number 12 | December 2021 | Pages 1247-1264
Technical Paper | doi.org/10.1080/00295639.2021.1923338
Articles are hosted by Taylor and Francis Online.
Because of the complexity of the nuclear reactor system, traditional statistical sampling methods, such as random sampling and Latin hypercube sampling, often lead to unstable uncertainty quantification results of the reactor physics analysis. In order to make the analysis results robust, traditional sampling methods require a large number of samples, which brings a huge computation cost. For this reason, this paper proposes a new sampling scheme based on the moment matching method to generate efficient samples for the uncertainty quantification of reactor physics calculations. A linear programming model is established to minimize the deviations of the first- and second-order moments. The generated samples can better reflect the statistical characteristics of the real distribution than classical sampling methods. A series of numerical experiments is carried out to demonstrate the superiority of the proposed moment matching sampling method, which can quickly provide more reliable uncertainty quantification results with a small sample size.