基于机器学习的RAFM钢中子辐照脆化预测模型研究

doi:10.11896/cldb.22010142

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Abstract Building the neutron irradiation embrittlement prediction model of reduced activation ferritic/martensitic (RAFM) steels is of great significance for the safe operation of the fusion reactor and the optimal design of new RAFM steels. In the present work, based on the collected neutron irradiation dataset of RAFM steels, the key features affecting the ductile-brittle transition temperature (DBTT) of RAFM steels under neutron irradiation are identified by correlation screening and recursive elimination methods. Using the selected key features, the prediction model for DBTT of neutron-irradiated RAFM steels with good prediction ability is constructed. In order to further predict the ductile-brittle transition temperature shift (ΔDBTT) under neutron irradiation, the prediction model for DBTT of un-irradiated RAFM steels is constructed. The prediction model for ΔDBTT of neutron-irradiated RAFM steels is constructed by combining the prediction models before and after irradiation. By comparing the ΔDBTT predicted by the model with the data collected from the related experimental literatures, the results indicate that this prediction model has high precision and reliability.

Key words： machine learning RAFM steel irradiation embrittlement DBTT

Published: 10 January 2023 Online: 2023-01-31

CLC number:

TG113.25

Fund:National Key Research and Development Program of China (2018YFE0307104), the National Natural Science Foundation of China (11632001), the International Cooperation Projects Supported by Foundation of President of the Hefei Institutes of Physical Science, Chinese Academy of Sciences (2021YZGH05), and Special Exchange Program of Chinese Academy of Sciences A (E2AAAI13).

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	LI Xiaochen
	DING Wenyi
	ZHU Xiaohan
	ZHENG Mingjie

Cite this article:

LI Xiaochen,DING Wenyi,ZHU Xiaohan, et al. Research on Prediction Model of Neutron Irradiation Embrittlement of RAFM Steels Based on Machine Learning[J]. Materials Reports, 2023, 37(1): 22010142-7.

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http://www.mater-rep.com/EN/10.11896/cldb.22010142 OR http://www.mater-rep.com/EN/Y2023/V37/I1/22010142

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