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

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• 作者：Hisashi Takamizawa ; ^{takamizawa.hisashi@jaea.go.jp" class="auth_mail" title="E-mail the corresponding author} ; Hiroto Itoh ^{ito.hiroto@jaea.go.jp" class="auth_mail" title="E-mail the corresponding author} ; Yutaka Nishiyama ^{nishiyama.yutaka93@jaea.go.jp" class="auth_mail" title="E-mail the corresponding author}
• 刊名：Journal of Nuclear Materials
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：479
• 期：Complete
• 页码：533-541
• 全文大小：3695 K

文摘

In order 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). The 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 steels, neutron flux, neutron fluence, and irradiation temperatures. It was found that the measured shifts of DBTT correlated well with the calculated ones. Data associated with the same materials were subdivided into the same clusters even if neutron fluences were increased.