An uncertainty reduction method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize that there exist some correlations among the prediction errors of core safety parameters, e.g., a correlation between the control rod worth and the assembly relative power at corresponding position. Correlations of errors among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients of core parameters. The estimated correlations of errors among core safety parameters are verified through the direct Monte Carlo sampling method. Once the correlation of errors among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained.

In this paper, we present a new Boolean resubstitution technique with permissible functions and ordered binary decision diagrams, abbreviated as OBDD [8]. Boolean resubstitution is one technique for multi-level logic optimization. Permissible functions are special don't care sets. We represent the data structure of permissible functions and logic functions at each node in Boolean networks in terms of OBDD. Therefore, logic functions can be flexibly manipulated and rapidly executed. We have previously reported a multi-level logic optimization technique called transduction methods [l] using OBDD in ICCAD'89[7]. We have improved the OBDD operation techniques, so that now OBDD operations can be executed faster than we reported before. We also applied Boolean resubstitution to our multi-level logic synthesis. We present results of experiments employing the improved OBDD operation techniques and applying Boolean resubstitution to our multi-level logic synthesis.