Abstract
Nuclear data validation involves a large suite of Integral Experiments (IEs) for criticality, reactor physics and dosimetry applications. [1] Often benchmarks are taken from international Handbooks. [2, 3] Depending on the application, IEs have different degrees of usefulness in validation, and usually the use of a single benchmark is not advised; indeed, it may lead to erroneous interpretation and results. [1] This work aims at quantifying the importance of benchmarks used in application dependent cross section validation. The approach is based on well-known General Linear Least Squared Method (GLLSM) extended to establish biases and uncertainties for given cross sections (within a given energy interval). The statistical treatment results in a vector of weighting factors for the integral benchmarks. These factors characterize the value added by a benchmark for nuclear data validation for the given application. The methodology is illustrated by one example, selecting benchmarks for 239 Pu cross section validation. The studies were performed in the framework of Subgroup 39 (Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files) established at the Working Party on International Nuclear Data Evaluation Cooperation (WPEC) of the Nuclear Science Committee under the Nuclear Energy Agency (NEA/OECD).
Highlights
Nuclear data (ND) validation is part of the global validation of analytical tools and is intended to support nuclear industry applications, and so, the results should provide essential information for decision making in support of nuclear safety, design and operation
The studies were performed in the framework of Subgroup 39 (Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files) established at the Working Party on International Nuclear Data Evaluation Cooperation (WPEC) of the Nuclear Science Committee under the Nuclear Energy Agency (NEA/OECD)
In this article we present examples of one criticality safety case [4] and of an extended pseudo- application – the resonance integral of 239Pu fission – in order to demonstrate application to practical cases as well as directly to nuclear data
Summary
Nuclear data (ND) validation is part of the global validation of analytical tools and is intended to support nuclear industry applications, and so, the results should provide essential information for decision making in support of nuclear safety, design and operation. Nuclear data validation is a complex process owing to the need to take into account several correlated physical phenomena – nuclear fission, radiation capture, neutrons scattering and slowing-down, all elastic and inelastic neutron-nuclei interactions etc. Each of these phenomena are present, to various degrees, in the available IEs. For a robust validation case, it is required that a statistically significant number of IEs be used in validation [1]. In addition it is demonstrated that the Validation and Uncertainty Quantification (V&UQ) process gives enough information to establish a ranking table of IEs, characterizing their importance in in a given application domain.
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