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The mission of the Nuclear Nonproliferation Policy Division (NNPD) is to promote the peaceful use of nuclear technology while simultaneously preventing the diversion and misuse of nuclear material and technology through appropriate safeguards and security, and promotion of nuclear nonproliferation policies. To achieve this mission, the objectives of the NNPD are to: Promote policy that discourages the proliferation of nuclear technology and material to inappropriate entities. Provide information to ANS members, the technical community at large, opinion leaders, and decision makers to improve their understanding of nuclear nonproliferation issues. Become a recognized technical resource on nuclear nonproliferation, safeguards, and security issues. Serve as the integration and coordination body for nuclear nonproliferation activities for the ANS. Work cooperatively with other ANS divisions to achieve these objective nonproliferation policies.
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UWC 2020: A call for transformational change
Bowing to current COVID-19 realities but buoyed by the success of June’s virtual Annual Meeting, ANS event planners returned to the virtual realm for this year’s Utility Working Conference. Originally scheduled for August 9–12 at Marco Island, Fla., the condensed event was held Wednesday, August 11, wherever registrants’ computer devices happened to be located.
In addition to 26 educational sessions and workshops, UWC 2020 featured an opening plenary session titled “Achieving Transformational Change: A leadership discussion,” moderated by Bob Coward, MPR Associates principal officer and ANS past president (2017–2018). Plenary panelists included representatives from three utilities—Arizona Public Service (APS), Exelon, and Xcel Energy—plus the Institute of Nuclear Power Operations (INPO) and the Nuclear Regulatory Commission.
Nathan W. Porter, Maria N. Avramova, Vincent A. Mousseau
Nuclear Science and Engineering | Volume 190 | Number 3 | June 2018 | Pages 271-286
Technical Paper | dx.doi.org/10.1080/00295639.2018.1435135
Articles are hosted by Taylor and Francis Online.
This work describes the results of a quantitative uncertainty analysis of the thermal-hydraulic subchannel code for nuclear engineering applications, Coolant Boiling in Rod Arrays-Three Field (COBRA-TF). CTF is used, which is a version of COBRA-TF developed in cooperation between the Consortium for Advanced Simulation of Light Water Reactors and North Carolina State University. Four steady-state cases from Phase II Exercise 3 of the Organisation for Economic Co-operation and Development/Nuclear Energy Agency Light Water Reactor Uncertainty Analysis in Modeling (UAM) Benchmark are analyzed using the statistical analysis tool, Design Analysis Kit for Optimization and Terascale Applications (Dakota). The input parameters include boundary condition, geometry, and modeling uncertainties, which are selected using a sensitivity study and then defined based on expert judgment. A forward uncertainty quantification method with Latin hypercube sampling (LHS) is used, where the sample size is based on available computational resources.
The means and standard deviations of thermal-hydraulic quantities of interest are reported, as well as the Spearman rank correlation coefficients between the inputs and outputs. The means and standard deviations are accompanied by their respective standard errors, and the correlation coefficients are tested for statistical significance. The quantities of interest include void fractions, temperatures, and pressure drops. The predicted uncertainty in all parameters remains relatively low for all quantities of interest. The dominant sources of uncertainty are identified. For cases based on experiments, two different validation metrics are used to quantify the difference between measured and predicted void fractions.
The results compare well with past studies, but with a number of improvements: the use of an updated CTF input deck using the current UAM specification and the most recent version of CTF, the use of an LHS method, an analysis of standard errors for the statistical results, and a quantitative comparison to experimental data.
Though the statistical uncertainty analysis framework presented herein is applied to thermal-hydraulic analyses, it is generally applicable to any simulation tool. Given a specified amount of computational resources, it can be used to quantify statistical significance through the use of fundamental statistical analyses. This is in contrast with the prevailing methods in nuclear engineering, which provide a sample size necessary to achieve a specified level of statistical certainty.