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Statistical analysis using the Bayesian nonparametric method for irradiation embrittlement of reactor pressure vessels

ノンパラメトリックベイズ法を用いた原子炉圧力容器の照射脆化に関する統計解析

高見澤 悠 ; 伊藤 裕人; 西山 裕孝 

Takamizawa, Hisashi; Ito, Hiroto; Nishiyama, Yutaka

高中性子照射量領域における照射脆化に関して、ノンパラメトリックベイズ法を用いて日本国内の監視試験データや試験炉照射データに対して統計解析を実施した。ノンパラメトリックベイズ法は実測データを正規分布の和で表す解析手法であり、正規分布の数と平均値や分散は実測データの複雑さに応じて決定される。本研究では、照射脆化の主因として考えられている溶質原子クラスタを構成する元素(Cu, Ni, Mn, Si, P)や照射条件を入力パラメータとして、照射脆化との関係を評価した。解析の結果、中性子照射量が異なるデータであっても同じ材料のデータは同じ正規分布に分類されており、中性子照射量に依存した脆化メカニズムが顕在化していないことが示唆された。

To understand neutron irradiation embrittlement in high fluence regions, statistical analysis using the Bayesian nonparametric (BNP) method was performed for the Japanese surveillance and material test reactor irradiation database. The BNP method is essentially expressed as an infinite summation of normal distributions, with input data being subdivided into clusters with identical statistical parameters (such as mean and standard deviation) for each cluster to estimate shifts in ductile-to-brittle transition temperature (DBTT). Clusters typically depend on chemical compositions, irradiation conditions, and the irradiation embrittlement. Specific variables contributing to the irradiation embrittlement include the content of Cu, Ni, P, Si, and Mn in the pressure vessel, neutron flux, neutron fluence, and irradiation temperatures. It was found through numerous examinations that the measured shifts of DBTT correlated well with calculated ones. Data associated with the same materials were subdivided into the same clusters even if neutron fluences were significantly disparate among the results. This indicates that slowly developing or late-onset embrittlement mechanisms were not evident in the present study.

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パーセンタイル:49.65

分野:Materials Science, Multidisciplinary

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