Abstract
Nuclear data sensitivity analysis and uncertainty propagation have been extensively applied to nuclear data adjustment and uncertainty quantification in the field of nuclear engineering. Sensitivity and Uncertainty (S&U) analysis is developed in the KYADJ whole-core transport code in order to meet the requirement of advanced reactor design. KYADJ aims to use two-dimension Method of Characteristic (MOC) and one-dimension discrete ordinate (SN) coupled method to solve the neutron transport equation and achieve one-step direct transport calculation of the reactor core. Developing sensitivity and uncertainty analysis module in KYADJ can minimize deviations caused by modeling approximation and enhance calculation efficiency. This work describes the application of the classic perturbation theory to the KYADJ transport solver. In order to obtain uncertainty, a technique is proposed for processing a covariance data file in 45-group energy grid instead of 44-group SCALE 6.1 covariance data which is extensively used in various codes. Numerical results for Uncertainty Analysis in Modelling (UAM) benchmarks and the SF96 benchmark are presented. The results agree well with the reference and the capability of S&U analysis in KYADJ is verified.
Highlights
Nuclear data are the most important input parameters in the reactor core calculation
The sensitivity coefficients are verified by direct perturbation theory (DPT) and the uncertainty quantification is performed for both cases
It is noted that the sensitivity analysis function and the covariance matrix has been verified in comparison with the Reactor Monte Carlo Code (RMC) in previous study[9]
Summary
Nuclear data are the most important input parameters in the reactor core calculation. All nuclear data have uncertainty when they are measured by certain measuring methods and apparatus. The uncertainty information of nuclear data is stored in the evaluated nuclear data file, which can be extracted and compressed into a covariance matrix [1]. Knowledge of the uncertainty in nuclear data has an important impact on the reactor physical design. The certain confidence of the output parameter is comprehensively influenced by the uncertainty of the input parameter, the model error and the numerical error. The effects of the uncertainty of the nuclear data will domain with the improvement of computer accuracy and numerical methods
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