Nuclear Data Uncertainty Propagation: Total Monte Carlo vs. Covariances

Two distinct methods of propagation for basic nuclear data uncertainties to large scale systems will be presented and compared. The "Total Monte Carlo" method is using a statistical ensemble of nuclear data libraries randomly generated by means of a Monte Carlo approach with the TALYS system. These libraries are then directly used in a large number of reactor calculations (for instance with MCNP) after which the exact probability distribution for the reactor parameter is obtained. The second method makes use of available covariance files and can be done in a single reactor calculation (by using the perturbation method). In this exercise, both methods are using consistent sets of data files, which implies that covariance files used in the second method are directly obtained from the randomly generated nuclear data libraries from the first method. This is a unique and straightforward comparison allowing to directly apprehend advantages and drawbacks of each method. Comparisons for different reactions and criticality-safety benchmarks from 1 F to actinides will be presented. We can thus conclude whether current methods for using covariance data are good enough or not.