Optimization of wear parameters for ECAP-processed ZK30 alloy using response surface and machine learning approaches: a comparative study

Abstract The present research applies different statistical analysis and machine learning (ML) approaches to predict and optimize the processing parameters on the wear behavior of ZK30 alloy processed through equal channel angular pressing (ECAP) technique. Firstly, The ECAPed ZK30 billets have been...

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出版年:	Scientific Reports
主要な著者:	Mahmoud Shaban, Fahad Nasser Alsunaydih, Hanan Kouta, Samar El-Sanabary, Abdulrahman Alrumayh, Abdulrahman I. Alateyah, Majed O. Alawad, Waleed H. El-Garaihy, Yasmine El-Taybany
フォーマット:	論文
言語:	英語
出版事項:	Nature Portfolio 2024-04-01
主題:	Equal channel angular pressing ZK30 alloy Wear performance Response surface methodology Machine learning
オンライン･アクセス:	https://doi.org/10.1038/s41598-024-59880-0