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Title: Using Whisper-1.1 to Guide Improvements to Nuclear Data Evaluations

Conference ·
OSTI ID:1400116

Along with the latest release of the general purpose Monte Carlo radiation transport code, MCNP6.2, came the first officially released version of Whisper, version 1.1, a statistical analysis code used for nuclear criticality safety (NCS) validation. The Whisper software package is primarily used to calculate the upper subcritical limit (USL) of a particular application case along with components of the margin of subcriticality (MOS). In the calculation of the MOS due to nuclear data uncertainties, Whisper uses the generalized linear-least-squares (GLLS) approach to obtain adjusted nuclear data uncertainties which are then propagated to estimate the nuclear data uncertainties in the keff of the application. Due to the fact that Whisper contains the simulated and measured keff values for over 1100 benchmarks, nuclear data sensitivity profiles for each benchmark along with the nuclear data covariance matrices, all of which are used in the GLLS method, it is possible to easily utilize these data available to help guide improvements to nuclear data evaluations. In the present work, the Whisper data and the GLLS method are used together to suggest an adjusted nuclear data cross section evaluation specifically for 233U such that the agreement between the calculated and experimental keff measurements of the relevant benchmarks are improved. With this adjusted nuclear data available, feedback to the theoretical and experimental nuclear data community is provided.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA), Nuclear Criticality Safety Program (NCSP)
DOE Contract Number:
AC52-06NA25396
OSTI ID:
1400116
Report Number(s):
LA-UR-17-24648
Resource Relation:
Conference: 2017 ANS NCSD Topical Meeting, Carlsbad, NM (United States), 10-15 Sep 2017
Country of Publication:
United States
Language:
English