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Elementary school resources added to Navigating Nuclear
Elementary school lesson plans are the latest additions to the Navigating Nuclear: Energizing Our World website. The two lesson plans were created to help students in grades 3-5 understand the power of the atom and how to investigate different energy sources.
Navigating Nuclear is a K-12 nuclear science and energy curriculum created in partnership by the American Nuclear Society and Discovery Education, with lead funding from the Department of Energy's Office of Nuclear Energy.
Vladimir Sobes, Luiz Leal, Goran Arbanas, Benoit Forget
Nuclear Science and Engineering | Volume 183 | Number 3 | July 2016 | Pages 347-355
Technical Paper | dx.doi.org/10.13182/NSE15-50
Articles are hosted by Taylor and Francis Online.
This project seeks to allow coupling of differential and integral data evaluation in a continuous-energy framework and to use the generalized linear least-squares (GLLS) methodology in the TSURFER module of the SCALE code package to update the parameters of a resolved resonance region evaluation. Recognizing that the GLLS methodology in TSURFER is identical to the mathematical description of a Bayesian update in SAMMY, the SAMINT code was created to use the mathematical machinery of SAMMY to update resolved resonance parameters based on integral data. Traditionally, SAMMY used differential experimental data to adjust nuclear data parameters. Integral experimental data, such as in the International Criticality Safety Benchmark Experiments Project, remain a tool for validation of completed nuclear data evaluations. SAMINT extracts information from integral benchmarks to aid the nuclear data evaluation process. Later, integral data can be used to resolve any remaining ambiguity between differential data sets, highlight troublesome energy regions, determine key nuclear data parameters for integral benchmark calculations, and improve the nuclear data covariance matrix evaluation. SAMINT is not intended to bias nuclear data toward specific integral experiments but should be used to supplement the evaluation of differential experimental data. Using GLLS ensures proper weight is given to the differential data.