検索対象:     
報告書番号:
※ 半角英数字
 年 ~ 
 年

An Estimation method of flaw distributions reflecting inspection results through Bayesian update

ベイズ更新による検査結果を反映した欠陥分布の推定方法

Lu, K.; 宮本 裕平*; 真野 晃宏; 勝山 仁哉; Li, Y.

Lu, K.; Miyamoto, Yuhei*; Mano, Akihiro; Katsuyama, Jinya; Li, Y.

近年、原子炉圧力容器(RPV)のような安全上重要機器に対する構造健全性評価において、確率論的破壊力学(PFM)に基づく手法が各国で用いられている。PFM解析では、対象となる機器の想定される欠陥を考慮して、その破損確率や破損頻度を評価する。そのため、PFMに基づきRPVの健全性評価を行う場合、欠陥分布(欠陥深さ及び密度分布)を重要な影響因子として合理的に設定する必要がある。最近、べイズ更新に基づき検査結果を欠陥分布に反映する手法が示され、検査で亀裂が見つかった場合に適用できる尤度関数が提案された。一方、RPVに対する検査の結果として欠陥指示がない可能性があるが、その場合のべイズ更新に必要な尤度関数が提案されていない。そこで、本研究では、検査により欠陥指示があった場合となかった場合の両方に適用できる尤度関数を提案した。また、提案した尤度関数を用いて、べイズ更新により検査結果を反映した欠陥分布を更新した例を示した。以上より、本研究で提案した尤度関数が、欠陥指示がない場合にも適用できることを明らかにした。

Nowadays, probabilistic fracture mechanics (PFM) has been utilized in several countries as a rational method for structural integrity assessment of important structural components such as reactor pressure vessels (RPVs). In PFM analyses, potential flaws in target components are used to evaluate the failure probability or frequency. Therefore, flaw distributions (i.e., flaw depth and density distributions) in an RPV shall be rationally set as one of the most important influential factors, which are developed during the manufacturing process such as welding. Recently, a Bayesian updating methodology was applied to reflect the inspection results into flaw distributions, and the likelihood functions applicable to the case when flaws are detected in inspections were proposed. However, there may be no flaw indication as the inspection results of some RPVs. The flaw distributions in this situation are important while the corresponding likelihood functions have not been proposed. Therefore, this study proposed likelihood functions to be applicable for both case when flaws are detected and when there is no flaw indication as the inspection results. Based on the proposed likelihood functions, several application examples were given in which flaw distributions were estimated by reflecting the inspection results through Bayesian update. The results indicate that the proposed likelihood functions are useful for estimating the flaw distribution for the case when there is no flaw indication as the inspection results.

Access

:

- Accesses

InCites™

:

Altmetrics

:

[CLARIVATE ANALYTICS], [WEB OF SCIENCE], [HIGHLY CITED PAPER & CUP LOGO] and [HOT PAPER & FIRE LOGO] are trademarks of Clarivate Analytics, and/or its affiliated company or companies, and used herein by permission and/or license.