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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.
Meeting Spotlight
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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Fusion Science and Technology
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.
Keisuke Fujii, Motoshi Goto, Shigeru Morita, Masahiro Hasuo
Fusion Science and Technology | Volume 69 | Number 2 | April 2016 | Pages 514-525
Technical Paper | doi.org/10.13182/FST15-168
Articles are hosted by Taylor and Francis Online.
The Balmer-α line profile observed from high-temperature magnetized plasmas can be interpreted as the sum of narrow and broad components corresponding to the emission from atoms generated in edge and core regions, respectively. The inversion of this line profile reveals the atom density distribution in the plasma. The inversion method we reported in previous studies [Nucl. Fusion, 55, 063029 (2015) and Rev. Sci. Instrum., 85, 023502 (2014)] requires a regularization parameter that must be manually tuned to avoid overfitting. Therefore, it has been difficult to evaluate the uncertainty of the results. Here, we report an improved method based on Bayesian statistics in which the regularization parameter is interpreted as an adjustable parameter, which is then marginalized for the uncertainty evaluation. Two types of prior distributions were examined. The first is an empirical prior that assumes the smoothness of a solution, and the second is based on a diffusion model of hydrogen atoms. We found the use of the diffusion model as prior information to have an advantage with respect to the accuracy of the core region atom density.