摘要
反应堆压力容器(RPV)作为压水堆中不可更换的关键部件之一,其安全和稳定是决定反应堆安全经济运行的重要因素。RPV钢的辐照脆化问题是制约RPV在堆内安全服役的关键。RPV钢的辐照脆化与其合金成分关系密切。本文利用神经网络方法研究了RPV钢中关键合金成分(Cu、Mn、Ni、Si、P)与辐照脆化之间的关系。研究结果表明,基于神经网络方法得到合金成分与辐照脆化的关系与传统认知基本一致,辐照脆化对Cu含量最敏感,Cu-Ni对辐照脆化存在协同作用,低Cu合金中Mn-Ni、Ni-Si对脆化存在协同作用。
As one of the key components that can not be replaced in PWR,the safety and stability of reactor pressure vessel(RPV)steel determine the safety and economy of the reactor.The irradiation embrittlement of RPV steel is the limiting factors for the operation of PWR.The irradiation embrittlement of RPV steel is closely related to its alloy composition.Based on the machine learning method,the relationship between key alloy components(Cu/Mn/Ni/Si/P)and irradiation embrittlement of RPV steel was constructed.The results show that the relationship between the alloy composition and irradiation embrittlement is basically consistent with the traditional cognition.The irradiation embrittlement is sensitive to Cu content,and Cu-Ni has synergistic effect on irradiation embrittlement.In low Cu alloys,Mn-Ni and Ni-Si have synergistic effects on embrittlement.
作者
贾丽霞
韩煦
白冰
王东杰
杨文
JIA Lixia;HAN Xu;BAI Bing;WANG Dongjie;YANG Wen(Division of Reactor Engineering Technology Research,China Institute of Atomic Energy,Beijing 102413,China)
出处
《原子能科学技术》
EI
CAS
CSCD
北大核心
2020年第11期2174-2181,共8页
Atomic Energy Science and Technology
基金
中国原子能科学研究院反应堆工程技术研究部创新基金项目。
关键词
反应堆压力容器钢
神经网络
辐照脆化
合金成分
reactor pressure vessel steel
neural network
irradiation embrittlement
alloy composition