Methodology and issues of integral experiments selection for nuclear data validation

Ivanova Tatiana, Evgeny Ivanov, Ian Hill, A. Plompen, F.-J. Hambsch, P. Schillebeeckx, W. Mondelaers, J. Heyse, S. Kopecky, P. Siegler, S. Oberstedt
2017 EPJ Web of Conferences  
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
more » ... ent 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.
doi:10.1051/epjconf/201714606002 fatcat:w3n3szdfwfd4dhi55li6ocoeva