Inventory Uncertainty Quantification using TENDL Covariance Data in Fispact-II

The new inventory code FisPAcT-II provides predictions of inventory, radiological quantities and their uncertainties using nuclear data covariance information. Central to the method is a novel fast pathways search algorithm using directed graphs. The pathways output provides (1) an aid to identifying important reactions, (2) fast estimates of uncertainties, (3) reduced models that retain important nuclides and reactions for use in the code's Monte Carlo sensitivity analysis module. Described are the methods that are being implemented for improving uncertainty predictions, quantification and propagation using the covariance data that the recent nuclear data libraries contain. In the TENDL library, above the upper energy of the resolved resonance range, a Monte Carlo method in which the covariance data come from uncertainties of the nuclear model calculations is used. The nuclear data files are read directly by FisPAcr-II without any further intermediate processing. Variance and covariance data are processed and used by FisPAcr-II to compute uncertainties in collapsed cross sections, and these are in turn used to predict uncertainties in inventories and all derived radiological data.