Publications

Sample Generation for Nuclear Data

Swiler, Laura P.; Adams, Brian M.; Wieselquist, William W.

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simiution) 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.