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Volume 41 Issue 6
Dec.  2020
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Kang Jing, Sun Kai, Mi Xiaoxi, Wu Lu, Mao Jianjun, Zhang Shuo, Lei Yang, Pan Rongjian, Tang Aitao. Research on Prediction Model of Irradiation Embrittlement of RPV Materials Based on Artificial Neural Network[J]. Nuclear Power Engineering, 2020, 41(6): 92-95.
Citation: Kang Jing, Sun Kai, Mi Xiaoxi, Wu Lu, Mao Jianjun, Zhang Shuo, Lei Yang, Pan Rongjian, Tang Aitao. Research on Prediction Model of Irradiation Embrittlement of RPV Materials Based on Artificial Neural Network[J]. Nuclear Power Engineering, 2020, 41(6): 92-95.

Research on Prediction Model of Irradiation Embrittlement of RPV Materials Based on Artificial Neural Network

  • Publish Date: 2020-12-15
  • Based on the analysis of a certain amount of on-site test samples, this paper constructs a high-precision artificial neural network model for the ductile-brittle transition temperature prediction of RPV materials. Then we use the model to explore the influence of neutron fluence and neutron fluence rate parameters on the ductile-brittle transition temperature of RPV materials. It is found that the ductile-brittle transition temperature increases linearly with the increasing of neutron fluence, and then rises slowly and finally saturates. The effect of neutron flux rate on the embrittlement of RPV materials is not obvious.

     

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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