Application of Covariance Data to Criticality Safety Data Validation
The use of cross-section covariance data has long been a key part of traditional sensitivity and uncertainty analyses (S/U). This paper presents the application of S/U methodologies to the data validation tasks of a criticality safety computational study. The S/U methods presented are designed to provide a formal means of establishing the area (or range) of applicability for criticality safety data validation studies. The goal of this work is to develop parameters that can be used to formally determine the ''similarity'' of a benchmark experiment (or a set of benchmark experiments individually) and the application area that is to be validated. These parameters are termed D parameters, which represent the differences by energy group of S/U-generated sensitivity profiles, and ck parameters, which are the correlation coefficients, each of which gives information relative to the similarity between pairs of selected systems. The application of a Generalized Linear Least-Squares Methodology ( GLLSM) tool to criticality safety validation tasks is also described in this paper. These methods and guidelines are also applied to a sample validation for uranium systems with enrichments greater than 5 wt %.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (US)
- DOE Contract Number:
- AC05-96OR22464
- OSTI ID:
- 14614
- Report Number(s):
- ORNL/CP-104995; TRN: AH200129%%339
- Resource Relation:
- Conference: Conference title not supplied, Conference location not supplied, Conference dates not supplied; Other Information: PBD: 13 Nov 1999
- Country of Publication:
- United States
- Language:
- English
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