Title: Experimental Covariance Determination for Critical Integral Experiments

Journal Article · · Nuclear Science and Engineering

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. In general, uncertainty quantification techniques ignore correlations between experiments and shared components. Experiments, such as the Thermal/Epithermal eXperiments (TEX) campaigns, consist of many shared components, such as the Jemima highly enriched uranium (HEU) fuel plates, which create a strong correlation in their uncertainties. While these correlations are known to exist, they are often not estimated because of the complexity of such calculations. Here this paper describes an intuitive method of determining the covariance for each of the experimental components, providing a correlation for each family of components across the multiple cases examined within a benchmark. A proof-of-principle study using the TEX-HEU experimental campaign was performed and verified that the covariance and correlation matrices can be calculated with information commonly found in the International Criticality Safety Benchmark Evaluation Project benchmarks. This study showed that the introduction of model and experimental covariances reduces the χ2 per degree of freedom from 2.203 to 1.179, indicating that the omission causes overly pessimistic bias quantifications. This technique can be seamlessly integrated to current benchmark evaluations as well as reevaluations of legacy benchmarks.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA), Nuclear Criticality Safety Program (NCSP)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
2331527
Report Number(s):
LLNL-JRNL-855080; 1083197
Journal Information:
Nuclear Science and Engineering, Journal Name: Nuclear Science and Engineering Vol. 2024; ISSN 0029-5639
Publisher:
Taylor & FrancisCopyright Statement
Country of Publication:
United States
Language:
English

References (5)

Development and application of marginal likelihood optimization for integral parameter adjustment journal September 2021
Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments journal October 2018
Sensitivity & Uncertainty Analysis, Volume 1 book January 2003
Whisper: Sensitivity/Uncertainty-Based Computational Methods and Software for Determining Baseline Upper Subcritical Limits journal September 2015
SCALE Code System report April 2020