自主反应堆压力容器辐照损伤预测模型构建分析

郭彦辉; 孙造占; 孙海涛; 徐超亮; 刘向兵; 陶钧

doi:10.13832/j.jnpe.2022.S1.0055

自主反应堆压力容器辐照损伤预测模型构建分析

doi: 10.13832/j.jnpe.2022.S1.0055

1.
生态环境部核与辐射安全中心，北京，100082
2.
苏州热工研究院有限公司，江苏苏州，215004
3.
中核核电运行管理有限公司，浙江嘉兴，314300

基金项目: 国家重点研发计划“核安全与先进核能技术”重点专项（2019YFB1900900）

详细信息

作者简介:
郭彦辉（1982—），男，博士，现主要从事核安全审评和研究，E-mail: Guoyh2005@163.com

通讯作者:
孙海涛， E-mail: sunnsc@163.com

中图分类号: TL351.6
计量
- 文章访问数: 33
- HTML全文浏览量: 21
- PDF下载量: 13
- 被引次数: 0
出版历程
- 收稿日期: 2022-01-18
- 修回日期: 2022-04-21
- 刊出日期: 2022-06-15

Construction and Analysis of Irradiation Damage Prediction Model for Autonomous Reactor Pressure Vessel

1.
Nuclear and Radiation Safety Center, Beijing, 100082, China
2.
Suzhou Nuclear Power Research Institute, Suzhou, Jiangsu, 215004, China
3.
China Nuclear Power Operation Management Co., Ltd., Jiaxing, Zhejiang, 314300, China

摘要

摘要: 反应堆压力容器（RPV）辐照脆化问题是制约RPV安全服役的关键，构建辐照损伤预测模型是预测辐照脆化损伤的有效方法。本文通过研究辐照损伤参数化预测模型、结构化预测模型和人工神经网络预测模型等典型辐照损伤模型的构建机理和构建方法，对比了不同预测模型的优缺点。结果表明：基于辐照机理的预测模型构建技术较能反映辐照脆化的物理作用机理，基于此提出了RPV自主预测模型的构建技术路线。
- 反应堆压力容器（RPV） /
- 辐照脆化 /
- 辐照损伤预测模型
Abstract: The problem of irradiation embrittlement of reactor pressure vessel (RPV) is the key to restrict the safe service of RPV, and the building of irradiation damage prediction model is an effective method to predict irradiation embrittlement damage. In this paper, the building mechanisms and methods of typical irradiation damage models such as parameterized prediction model, structured prediction model and artificial neural network prediction model are studied, and the advantages and disadvantages of different prediction models are compared. The results show that the building technology of prediction model based on irradiation mechanism can better reflect the physical mechanism of irradiation embrittlement. Based on this, the construction technology route of RPV independent prediction model is proposed.
- Reactor pressure vessel (RPV) /
- Irradiation embrittlement /
- Irradiation damage prediction model

HTML全文

图 1 Mathew RPV人工神经网络辐照损伤预测模型示意图　　　　　　

w_ji—隐藏层的权重矩阵；b⁽¹⁾—第一层的偏置向量；b⁽²⁾—第二层的偏置向量；ω_Cu— 铜元素的质量分数，ω_Ni—镍元素的质量分数，ω_Mn—锰元素的质量分数，ω_Si—硅元素的质量分数；ω_P—磷元素的质量分数

Figure 1. Schematic Diagram of Mathew RPV Artificial Neural Network Irradiation Damage Prediction Model

下载: 全尺寸图片幻灯片

参考文献(9)

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