A Multiple Regression Equation for Calculated k_eff Bias Errors by Criticality Code System

Some 500 cases of benchmark calculations on criticality problems for homogeneous experimental systems have been made with the KENO-IV Monte Carlo calculation code using the MGCL cross-section data library. The calculation results have been analyzed to classify the experimental systems so as to make the variance of calculated k_eff bias as small as possible in each classified system. The trends of bias are identified and illustrated to be optimumly expressed by a multiple variable regression equation in terms of several variables, which adequately correlate with the bias value of k_eff calculated for the experiments. The uncertainty accompanied by bias correction for calculated k_eff is clearly determined, and the margin set aside for the experimental error is assessed. Finally, the procedure to estimate nuclear criticality safety is proposed.