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Monte Carlo criticality calculation under extreme condition

極端な条件下でのモンテカルロ法臨界計算

植木 太郎  

Ueki, Taro

極端な条件下でのモンテカルロ法臨界計算について、世代間自己相関の観点から、評価量バイアスの存在可能性,判定方法、及び修正方法を示した。

Autocorrelation and bias characteristics in the Monte Carlo criticality calculation have been examined for a certain type of extreme problems. Possibility is shown that the bias of the effective multiplication factor can become larger than -0.1 in magnitude for population size as large as 10,000 starter particles per generation. This bias dramatically decreases if the number of starter particles per generation is large enough so that the noise propagation of a source distribution becomes linear. Furthermore, under this linearity, the bias correction is demonstrated to be an estimation problem of autocorrelation. Therefore, the linearity diagnosis of the noise propagation should be made available in the Monte Carlo criticality codes in public release in order to encompass analysis scenarios beyond normal circumstances.

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パーセンタイル:63.54

分野:Nuclear Science & Technology

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