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To investigate the influence of nuclear data uncertainties on reactor core calculations systematically, the sampling based uncertainty and sensitivity software package SUSA developed at GRS was extended for the use with nuclear covariance data. Varied nuclear data are generated randomly corresponding to the uncertainty information from the covariance matrices. After performing a large number of calculations with these data, the results are statistically evaluated; this can be done not only for integral, but also for local output quantities like the assembly power distribution. The method is applied to multi-group Monte Carlo calculations stationary states of the PWR MOX/UO2 core transient benchmark, and to corresponding nodal diffusion calculations. Unexpectedly large uncertainties result for the radial power distribution. The uncertainties in the nodal results agree very well with those in the Monte Carlo reference results; thus, it is possible to apply the random sampling method to determine the influence of nuclear data uncertainties on transient core calculations.

Abstract. In the present contribution, an overview of the sampling based XSUSA method for sensitivity and uncertainty analysis with respect to nuclear data is given. The focus is on recent developments and applications of XSUSA. These applications include calculations for critical assemblies, fuel assembly depletion calculations, and steadystate as well as transient reactor core calculations. The analyses are partially performed in the framework of international benchmark working groups (UACSA -Uncertainty Analyses for Criticality Safety Assessment, UAM -Uncertainty Analysis in Modelling). It is demonstrated that particularly for full-scale reactor calculations the influence of the nuclear data uncertainties on the results can be substantial. For instance, for the radial fission rate distributions of mixed UO 2 /MOX light water reactor cores, the 2σ uncertainties in the core centre and periphery can reach values exceeding 10%. For a fast transient, the resulting time behaviour of the reactor power was covered by a wide uncertainty band. Overall, the results confirm the necessity of adding systematic uncertainty analyses to best-estimate reactor calculations.

For the multiple sources of error introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily to quantify the effects of cross section uncertainties. Two methods for propagating cross section uncertainties through core simulators are the XSUSA statistical approach and the “two-step” method. The XSUSA approach, which is based on the SUSA code package, is fundamentally a stochastic sampling method. Alternatively, the two-step method utilizes generalized perturbation theory in the first step and stochastic sampling in the second step. The consistency of these two methods in quantifying uncertainties in the multiplication factor and in the core power distribution was examined in the framework of phase I-3 of the OECD Uncertainty Analysis in Modeling benchmark. With the Three Mile Island Unit 1 core as a base model for analysis, the XSUSA and two-step methods were applied with certain limitations, and the results were compared to those produced by other stochastic sampling-based codes. Based on the uncertainty analysis results, conclusions were drawn as to the method that is currently more viable for computing uncertainties in burnup and transient calculations.

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