Bayesian Estimation of Cross-Section, Experimental Error, and Calculation Error: Comparison with Bias Factor Method

Assuming that the discrepancy between the experimental value and the calculation value comes from the cross section, experimental error, and calculation error, Bayesian estimation of the cross section and these errors were studied. Uncertainty of the discrepancy between the experimental value and the design value is discussed by comparing the present estimation and the bias factor method. Comparison of the formulas shows that the design value obtained by the bias factor method is consistent with that obtained by estimation of the cross section and calculation error of the target system. In addition, the uncertainty of the discrepancy between the experimental value and the design value can be reduced by considering a correlation of the experimental error between the mock-up experiment and the target system. A case study was performed using mixed oxide critical assembly benchmarks. The result shows that the experimental value of the target system can be accurately predicted by considering the cross section, experimental error, and calculation error.