Application of new information entropy to source convergence diagnostics in Monte Carlo criticality calculations

¹ NAIS Co. Inc., 416 Muramatsu, Tokai-mura, Naka-gun, Ibaraki 319-1112, Japan

^* E-mail: ynaito@nais.ne.jp

Abstract

In criticality safety evaluation, effective multiplication factor and its corresponding source distribution are often evaluated by the Monte Carlo method. For source convergence diagnostics a kind of information entropy (Shannon entropy) has, sometimes, been used. In the last conference (2009), we proposed new type information entropy in which the source distribution is expressed on an eigen-function space in order to evaluate the convergence not only of the effective multiplication factor but also of source distribution without increasing computing resources requirements. However, there arose questions concerning our entropy. Here, we answer some of the questions : (1) how to estimate expansion coefficients, (2) how to estimate the difference between the effective multiplication factor and the corresponding maximum eigenvalue, and (3) how to estimate the deviations of expansion coefficients due to the power iteration method using source distribution calculated by Monte Carlo methods. By applying our entropy to power iteration method, more effective source convergence diagnostics method combined with the “Sandwich Method” is attained.