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Human Factors, Instrumentation & Controls
Improving task performance, system reliability, system and personnel safety, efficiency, and effectiveness are the division's main objectives. Its major areas of interest include task design, procedures, training, instrument and control layout and placement, stress control, anthropometrics, psychological input, and motivation.
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International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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Latest News
The 2025 ANS election results are in!
Spring marks the passing of the torch for American Nuclear Society leadership. During this election cycle, ANS members voted for the newest vice president/president-elect, treasurer, and six board of director positions (four U.S., one non-U.S., one student). New professional division leadership was also decided on in this election, which opened February 25 and closed April 15. About 21 percent of eligible members of the Society voted—a similar turnout to last year.
J. M. Canik, X.-Z. Tang
Fusion Science and Technology | Volume 71 | Number 1 | January 2017 | Pages 103-109
Technical Paper | doi.org/10.13182/FST16-124
Articles are hosted by Taylor and Francis Online.
While the sensitivity of the scrape-off layer and divertor plasma to the highly uncertain cross-field transport assumptions is widely recognized, the plasma is also sensitive to the details of the plasma-material interface (PMI) models used as part of comprehensive predictive simulations. Here, these PMI sensitivities are studied by varying the relevant submodels within the SOLPS plasma transport code. Two aspects are explored: the sheath model used as a boundary condition in SOLPS, and fast particle reflection rates for ions impinging on a material surface. Both of these have been the study of recent high-fidelity simulation efforts aimed at improving the understanding and prediction of these phenomena. It is found that in both cases quantitative changes to the plasma solution result from modification of the PMI model, with a larger impact in the case of the reflection coefficient variation. This indicates the necessities to better quantify the uncertainties within the PMI models themselves and to perform thorough sensitivity analysis to propagate these throughout the boundary model; this is especially important for validation against experiment, where the error in the simulation is a critical and less-studied piece of the code-experiment comparison.