Uncertainty Analysis in Nuclear Criticality Safety Computations

Uncertainty analysis is imperative for criticality risk assessments when using computational methods to predict the multiplication factor (k_eff) for fissionable material systems. For the validation of criticality safety computer codes, code accuracy and precision are determined by the computational bias and uncertainty in the bias to account for experimental, computational and model uncertainties. For the application of criticality safety computer codes in the criticality safety design of fissionable material systems, a minimum margin of subcriticality (MMS) must be included to provide additional assurance of subcriticality for any unquantified or unknown uncertainties [1]. Because of a substantial impact of the MMS on nuclear fuel cycle operations, recently increasing interests in reducing the MMS make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k_eff uncertainty analysis methods for Monte Carlo neutron transport based criticality safety computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage for the code validation against benchmark experiments and for the criticality safety design evaluation.