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Division Spotlight
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.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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Fusion Science and Technology
Latest News
Argonne research aims to improve nuclear fuel recycling and metal recovery
Servis
Scientists at Argonne National Laboratory are investigating a used nuclear fuel recycling technology that could lead to a scaled-down and more efficient approach to metal recovery, according to a recent news article from the lab. The research, led by Argonne radiochemist Anna Servis with funding from the Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E), could have an impact beyond the nuclear fuel cycle and improve other high-value metal processing, such as rare earth recovery, according to Argonne.
The research: Servis’s work is being carried out under ARPA-E’s CURIE (Converting UNF Radioisotopes Into Energy) program. The specific project—Radioisotope Capture Intensification Using Rotating Packed Bed Contactors—started in 2023 and is scheduled to end in January 2026.
Michael L. Lanahan, Said I. Abdel-Khalik, Minami Yoda
Fusion Science and Technology | Volume 79 | Number 8 | November 2023 | Pages 1071-1081
Research Article | doi.org/10.1080/15361055.2023.2177065
Articles are hosted by Taylor and Francis Online.
Given the lack of fusion-relevant component test facilities, current estimates of the thermo-fluid performance of plasma-facing components are based for the most part on numerical simulations. A major source of uncertainty in these simulations is the semiempirical turbulence (closure) models for the Reynolds stresses appearing in the governing Reynolds-averaged Navier-Stokes equations, which involve a set of constants that depend upon the flow.
The objective of this study is to evaluate Bayesian parameter estimation of turbulence closure constants in ANSYS Fluent to model heat transfer in impinging jets. The Bayesian statistical calibration produces a probability distribution for these constants from experimental data; the maximum a posteriori estimates are then taken to be the calibrated constants, or parameters. The turbulence model constants are calibrated using an experimental study of a submerged jet of air impinging on a flat heated surface at Reynolds numbers Re = O(104) and impingement distance in jet diameters H/d = 2. Numerical predictions using the calibrated model parameters are then compared with those generated using the default constants. Predictions obtained with model parameters calibrated on datasets of two different sizes are compared to evaluate the effect of the number of calibration samples. Finally, the extrapolative ability of the calibrated model is examined by predictions at a Re beyond the calibration values.