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The Young Members Group works to encourage and enable all young professional members to be actively involved in the efforts and endeavors of the Society at all levels (Professional Divisions, ANS Governance, Local Sections, etc.) as they transition from the role of a student to the role of a professional. It sponsors non-technical workshops and meetings that provide professional development and networking opportunities for young professionals, collaborates with other Divisions and Groups in developing technical and non-technical content for topical and national meetings, encourages its members to participate in the activities of the Groups and Divisions that are closely related to their professional interests as well as in their local sections, introduces young members to the rules and governance structure of the Society, and nominates young professionals for awards and leadership opportunities available to members.
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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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Latest News
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Bertrand Iooss, Amandine Marrel
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1588-1606
Technical Paper | doi.org/10.1080/00295450.2019.1573617
Articles are hosted by Taylor and Francis Online.
In the framework of the estimation of safety margins in nuclear accident analysis, a quantitative assessment of the uncertainties tainting the results of computer simulations is essential. Accurate uncertainty propagation (estimation of high probabilities or quantiles) and quantitative sensitivity analysis may call for several thousand code simulations. Complex computer codes, as the ones used in thermal-hydraulic accident scenario simulations, are often too CPU-time expensive to be directly used to perform these studies. A solution consists in replacing the computer model by a CPU-inexpensive mathematical function, called a metamodel, built from a reduced number of code simulations. However, in case of high-dimensional experiments (with typically several tens of inputs), the metamodel building process remains difficult. To face this limitation, we propose a methodology which combines several advanced statistical tools: initial space-filling design, screening to identify the noninfluential inputs, and Gaussian process (Gp) metamodel building with the group of influential inputs as explanatory variables. The residual effect of the group of noninfluential inputs is captured by another Gp metamodel. Then, the resulting joint Gp metamodel is used to accurately estimate Sobol’ sensitivity indices and high quantiles (here 95% quantile). The efficiency of the methodology to deal with a large number of inputs and reduce the calculation budget is illustrated on a thermal-hydraulic calculation case simulating with the CATHARE2 code a loss-of-coolant accident scenario in a pressurized water reactor. A predictive Gp metamodel is built with only a few hundred code simulations which allows the calculation of the Sobol’ sensitivity indices. This Gp also provides a more accurate estimation of the 95% quantile and associated confidence interval than the empirical approach, at equal calculation budget. Moreover, on this test case, the joint Gp approach outperforms the simple Gp.