Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features
The microstructural evolution prediction and operating condition evaluation of nickel-based single crystal (SX) superalloys during creep are of great significance for damage assessment in service. In this paper, quantitative models of crept microstructural evolution of a nickel-based SX superalloy c...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | Journal of Materials Research and Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785422008729 |
| _version_ | 1811281342861672448 |
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| author | Jinghui Xu Longfei Li Xingang Liu Hui Li Qiang Feng |
| author_facet | Jinghui Xu Longfei Li Xingang Liu Hui Li Qiang Feng |
| author_sort | Jinghui Xu |
| collection | DOAJ |
| description | The microstructural evolution prediction and operating condition evaluation of nickel-based single crystal (SX) superalloys during creep are of great significance for damage assessment in service. In this paper, quantitative models of crept microstructural evolution of a nickel-based SX superalloy containing Re and Ru were constructed by using the machine learning method with physical and statistical features of microstructure. Firstly, a sequence of high temperature creep tests was conducted on high-throughput specimens with multiple conditions. The physical microstructural features, i.e., volume fraction (Vf), rafting degree (Ω), and rafts thickness (D) of γ′ precipitates of 8 different specimens were quantitated continuously. Secondly, the statistic features were introduced as supplementary to improve the specificity of microstructural features, using the two statistical methods of two-point correlation and principal component analysis (PCA). Then, two machine learning models were constructed through a neural network algorithm, to predict the microstructure under a certain creep condition and evaluate the creep condition with a certain microstructural feature. The validation creep test showed that these two models have good performance. The quantitative models constructed in this study have great significance in the alloy optimization and damage assessment of nickel-based SX superalloys, which can be extended to other SX superalloys. |
| first_indexed | 2024-04-13T01:31:57Z |
| format | Article |
| id | doaj.art-4be16c7540754603bfb1035d1e68cb7f |
| institution | Directory Open Access Journal |
| issn | 2238-7854 |
| language | English |
| last_indexed | 2024-04-13T01:31:57Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Materials Research and Technology |
| spelling | doaj.art-4be16c7540754603bfb1035d1e68cb7f2022-12-22T03:08:29ZengElsevierJournal of Materials Research and Technology2238-78542022-07-011923012313Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical featuresJinghui Xu0Longfei Li1Xingang Liu2Hui Li3Qiang Feng4Beijing Advanced Innovation Center for Materials Genome Engineering, State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing 100083, ChinaBeijing Advanced Innovation Center for Materials Genome Engineering, State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing 100083, China; Corresponding author.Superalloys Division, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, ChinaSuperalloys Division, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, ChinaBeijing Advanced Innovation Center for Materials Genome Engineering, State Key Laboratory for Advanced Metals and Materials, University of Science and Technology Beijing, Beijing 100083, ChinaThe microstructural evolution prediction and operating condition evaluation of nickel-based single crystal (SX) superalloys during creep are of great significance for damage assessment in service. In this paper, quantitative models of crept microstructural evolution of a nickel-based SX superalloy containing Re and Ru were constructed by using the machine learning method with physical and statistical features of microstructure. Firstly, a sequence of high temperature creep tests was conducted on high-throughput specimens with multiple conditions. The physical microstructural features, i.e., volume fraction (Vf), rafting degree (Ω), and rafts thickness (D) of γ′ precipitates of 8 different specimens were quantitated continuously. Secondly, the statistic features were introduced as supplementary to improve the specificity of microstructural features, using the two statistical methods of two-point correlation and principal component analysis (PCA). Then, two machine learning models were constructed through a neural network algorithm, to predict the microstructure under a certain creep condition and evaluate the creep condition with a certain microstructural feature. The validation creep test showed that these two models have good performance. The quantitative models constructed in this study have great significance in the alloy optimization and damage assessment of nickel-based SX superalloys, which can be extended to other SX superalloys.http://www.sciencedirect.com/science/article/pii/S2238785422008729Nickel-based SX superalloyHigh-throughput creep testsStatistical microstructural featuresMicrostructure-property correlationArtificial neural networks |
| spellingShingle | Jinghui Xu Longfei Li Xingang Liu Hui Li Qiang Feng Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features Journal of Materials Research and Technology Nickel-based SX superalloy High-throughput creep tests Statistical microstructural features Microstructure-property correlation Artificial neural networks |
| title | Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features |
| title_full | Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features |
| title_fullStr | Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features |
| title_full_unstemmed | Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features |
| title_short | Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features |
| title_sort | quantitative models of high temperature creep microstructure property correlation of a nickel based single crystal superalloy with physical and statistical features |
| topic | Nickel-based SX superalloy High-throughput creep tests Statistical microstructural features Microstructure-property correlation Artificial neural networks |
| url | http://www.sciencedirect.com/science/article/pii/S2238785422008729 |
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