Integrated Framework for Propagation of Uncertainties in Nuclear Cross-Sections in CANDU Steady-State and Transient Reactor Physics Simulations
Abstract of the technical paper presented at:
37th Annual Conference of the Canadian Nuclear Society
Dumitru Serghiuta, John Tholammakkil, Canadian Nuclear Safety Commission, Ottawa, Canada
Hany Abdel-Khalik, Purdue University, West Lafayette, Indiana, U.S.
Alexandre Trottier, Canadian Nuclear Laboratory, Chalk River, Canada
The current CNSC REGDOC-2.4.1, Deterministic Safety Analysis, allows for use of more realistic methodologies, such as the best estimate (BE) reactor analysis simulations with consideration of uncertainties. Quantification and understanding of uncertainty sources is an essential requirement of BE analysis, as it provides a reliable metric by which the quality of the predictions can be assessed.
Although direct comparison against measurements provides the ultimate evidence that simulation predictions are reliable, the true value of any BE simulation lies in its ability to analyze reactor conditions for which measurements are unavailable. Therefore, there is a clear need to characterize (propagate and prioritize) all sources of uncertainties in order to reliably use the results of BE calculations in various aspects of reactor design, operation and safety.
To enhance the CNSC’s capability for independent verification of safety cases using more realistic methodologies, CNSC staff have initiated a study to investigate the feasibility of developing a first-of-a-kind integrated framework for uncertainty characterization (UCF) with primary application to CANDU neutronics calculations. The goal has been to provide a comprehensive and scientifically defensible methodology for characterizing uncertainties in all BE reactor analysis calculations, including both steady state and transient simulations, to be used in independent regulatory verification. The scope also included identification of needs and key challenges in developing and coding the UCF. The UCF concept has been developed to accomplish four primary functions: first, to identify all sources of uncertainties resulting from modelling assumptions, numerical approximations, nuclear data uncertainties, and technological parameters uncertainties; second, to propagate the identified uncertainties to the responses of interest such as the core eigenvalue, power distribution, bundle enthalpy rise, etc.; third, to map the propagated uncertainties to the wide range of operating conditions; and lastly, to generate a priority identification and ranking table (PIRT) which identifies and ranks the dominant sources of uncertainties according to importance.
The paper describes the proposed approach for the first step of implementation of UFC, which focuses on developing an integrated automated capability for uncertainty analysis for the core simulator NESTLE-C in both steady state and transient CANDU core calculations. The end result is a complete library of diffusion cross-sections and associated uncertainty distribution function and covariance matrix, and an integrated platform which includes execution scripts, sampler software, NESTLE-C, and processing software with an input flag that allows the user to estimate the joint probability distribution for all output results. The output results are also customized to include typical statistical quantities such as mean, variance, and covariance information for user-selected core attributes. The main computer codes employed in the generation of the diffusion cross-sections library are SERPENT, TRITON, T2N, and CRANE.
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