CALCULATION UNCERTAINTIES IN SPENT FUEL INVENTORY DETERMINATION

In the depletion calculation of the nuclear fuel, the uncertainty is of utmost importance, as it affects the uncertainty of the subsequent calculation, when the calculated composition is used. The calculations are even more important when they are safety related, e. g., when determining the reactivity or emissions of radioactivity to the environment. This work covers the depletion model of Gd-2M+ fuel which was developed in ORIGEN-ARP/TRITON calculation sequences, both being parts of a SCALE 6.2.1 package. The uncertainties of the respective calculation model were determined by comparison with experimental data for both calculation sequences. The effects of operational and manufacturing uncertainties on concentration of the most important nuclides using TRITON depletion model of Gd-2M+ fuel were determined. The effect of respective uncertainties manifested in changes of composition on the multiplication factor using Monte-Carlo sequence KENO-VI were also specified.

Diagnosing the Relative Impact of “Sneaks,” “Phantoms,” and Volatility in Sequences of Lagged Ensemble Probability Forecasts with a Simple Dynamic Decision Model

Monte Carlo simulation of sequences of lagged ensemble probability forecasts is undertaken using Markov transition law estimated from a reforecast ensemble. A simple three-state, three-action dynamic decision model is then applied to the Monte Carlo sequence realizations using a basket of cost functions, and the resulting expense incurred by the decision model is conditioned upon the structure of the sequence realizations. Findings show that the greatest average expense is incurred by “sneak” and “volatile” sequence structures, which are structures characterized by large and rapid increases in event probability at short lag times. These findings are simple quantitative illustration of the adage that large run-to-run variability of forecasts can be troublesome to a decision maker. The experiments also demonstrate how even small improvements in the amount of advance warning of an event can translate into a substantial reduction in decision expense. In general, the conditioned decision expense is found to be sensitive to sequence structure for a given cost function, to the parameters of a given cost function, and to the choice of cost function itself.