DOAJ Open Access 2020

Design of comprehensive mechanical properties by machine learning and high-throughput optimization algorithm in RAFM steels

Chenchong Wang Chunguang Shen Xiaojie Huo Chi Zhang Wei Xu

Abstrak

In order to make reasonable design for the improvement of comprehensive mechanical properties of RAFM steels, the design system with both machine learning and high-throughput optimization algorithm was established. As the basis of the design system, a dataset of RAFM steels was compiled from previous literatures. Then, feature engineering guided random forests regressors were trained by the dataset and NSGA II algorithm were used for the selection of the optimal solutions from the large-scale solution set with nine composition features and two treatment processing features. The selected optimal solutions by this design system showed prospective mechanical properties, which was also consistent with the physical metallurgy theory. This efficiency design mode could give the enlightenment for the design of other metal structural materials with the requirement of multi-properties. Keywords: Machine learning, High-throughput optimization, Mechanical property, RAFM steel

Topik & Kata Kunci

Nuclear engineering. Atomic power

Penulis (5)

Chenchong Wang

Chunguang Shen

Xiaojie Huo

Chi Zhang

Wei Xu

Format Sitasi

APA MLA BibTeX

Wang, C., Shen, C., Huo, X., Zhang, C., Xu, W. (2020). Design of comprehensive mechanical properties by machine learning and high-throughput optimization algorithm in RAFM steels. https://doi.org/10.1016/j.net.2019.10.014

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Informasi Jurnal

Tahun Terbit: 2020
Sumber Database: DOAJ
DOI: 10.1016/j.net.2019.10.014
Akses: Open Access ✓