Nuclear Data Evaluation and Uncertainty Quantification
Total Monte Carlo (TMC) is a method to propagate nuclear data uncertainties to different applications, such as fission reactors, fusion reactors and shielding applications.
The basic idea is to use a state-of-the-art nuclear model code like TALYS and randomize the input parameters within a reasonable range. This range may be defined as fixed. Alternatively a feedback-loop may be used, which compares the resulting calculated cross sections with the existing data-set in the EXFOR database of nuclear reaction data, in order to decide whether the current parameter set leads to acceptable results.
In this way several hundred possible cross-section datasets are generated. TENDL is the TALYS Evaluated Nuclear Data Library.
These datasets are, after proper formatting, fed into a simulation code for the system (e.g. a reactor). In this way the macroscopic parameters and their corresponding uncertainties are calculated in direct dependence of basic nuclear physics input parameters. Since this is done “event-by-event” (parameter-set by parameter-set) the results are traceable back to the input data opening up for sensitivity analysis, studies of correlations, etc.
The TMC uncertainty propagation and TENDL production. In the TMC processes the final result is a spread in a macroscopic parameter. This spread is the systematic uncertainty in the calculation due to ND in the investigated parameter.