RBF-assisted surrogate modeling and machine learning for mechanical property prediction in friction stir additive manufacturing: Application to dissimilar AA6061/AA7075 aluminum alloys.

发表于 2026-9-8 12:26:09

期刊：Scientific Reports

文献作者：Krishnan Venkatachalam; Senthil Kumaran Selvaraj; Giriraj Mannayee; Kalyanaraman Pattabiraman; Sundaramali G

出版日期：--

DOI号：10.1038/s41598-026-42608-7

下载链接：https://www.nature.com/articles/s41598-026-42608-7.pdf

文献链接：https://doi.org/10.1038/s41598-026-42608-7

当前文献来源于 Springer Science and Business Media LLC。

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[Nature] RBF-assisted surrogate modeling and machine learning for mechanical property prediction in friction stir additive manufacturing: Application to dissimilar AA6061/AA7075 aluminum alloys.

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[Nature] RBF-assisted surrogate modeling and machine learning for mechanical property prediction in friction stir additive manufacturing: Application to dissimilar AA6061/AA7075 aluminum alloys. 一键复制

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