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DOE OSTI · 1474254

Sample Generation for Nuclear Data

Swiler, Laura Painton·Adams, Brian M.·Wieselquist, William
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Abstract

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices. The treatment allows one to assume the cross sections are distributed with a multivariate normal distribution, lognormal distribution, or truncated normal distribution.

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73 NUCLEAR PHYSICS AND RADIATION PHYSICS

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BibTeXRIS

Swiler, Laura Painton, Adams, Brian M., Wieselquist, William. 2018-09-01. Sample Generation for Nuclear Data. https://doi.org/10.2172/1474254

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