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Uncertainty and sensitivity studies with the probabilistic accident consequence assessment code OSCAAR

確率論的事故影響評価コードOSCAARによる不確実さ感度研究

本間 俊充; 富田 賢一*; 波戸 真治*

Homma, Toshimitsu; Tomita, Kenichi*; Hato, Shinji*

本研究では、確率論的事故影響評価における気象条件等の自然のランダムネスに起因する統計的不確実さとモデルや入力パラメータに関する知識不足に起因する不確実さを取り上げ、OSCAARコードを敷地外住民個人の早期及び晩発性がん死亡リスクの不確実さ感度解析へ適用した。流跡線による拡散モデルに適合した新気象サンプリング手法を確立し、その統計的なばらつきについて検討した。OSCAARの65の入力パラメータを対象とした不確実さ伝播解析を実施し、サイト近傍の個人の早期及び晩発性がん死亡リスクの期待値の不確実さ幅を与えるとともに、感度解析に相関及び回帰に基づく指標を用い、不確実さに寄与する重要なパラメータを明らかにした。

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence.

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