CIAU Method for Uncertainty Evaluation for System Thermal-Hydraulic Code Calculations

Best-Estimate calculation results from complex thermal-hydraulic system codes (like Relap5, Cathare, Athlet, Trace, etc..) are affected by unavoidable approximations that are un-predictable without the use of computational tools that account for the various sources of uncertainty. Therefore the use of best-estimate codes within the reactor technology, either for design or safety purposes, implies understanding and accepting the limitations and the deficiencies of those codes. Uncertainties may have different origins ranging from the approximation of the models, to the approximation of the numerical solution, and to the lack of precision of the values adopted for boundary and initial conditions. The amount of uncertainty that affects a calculation may strongly depend upon the codes and the modeling techniques (i.e. the code’s users). A consistent and robust uncertainty methodology must be developed taking into consideration all the above aspects. The CIAU (Code with the capability of Internal Assessment of Uncertainty) and the UMAE (Uncertainty Methodology based on Accuracy Evaluation) methods have been developed by University of Pisa (UNIPI) in the framework of a long lasting research activities started since 80’s and involving several researchers. CIAU is extensively discussed in the available technical literature, Refs. [1, 2, 3, 4, 5, 6, 7], and tens of additional relevant papers, that provide comprehensive details about the method, can be found in the bibliography lists of the above references. Therefore, the present paper supplies only ‘spot-information’ about CIAU and focuses mostly on the applications to some cases of industrial interest. In particular the application of CIAU to the OECD BEMUSE (Best Estimate Methods Uncertainty and Sensitivity Evaluation, [8, 9]) project is discussed and a critical comparison respect with other uncertainty methods (in relation to items like: sources of uncertainties, selection of the input parameters and quantification of their uncertainty ranges, ranking process, etc.) is presented.