Extreme high accuracy prediction and design of Fe-C-Cr-Mn-Si steel using machine learning

Extreme high accuracy prediction and design of Fe-C-Cr-Mn-Si steel using machine learning

Solid solution strengthening theory is essential for designing steel with high microhardness. Experimental determination is quite time consuming and costly. It is necessary to develop an alternate approach to rapidly and accurately predict new solid solution strengthening theory for steel. In this s...

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Bibliographic Details
Main Authors: Hao Wu, Jianyuan Zhang, Jintao Zhang, Chengjie Ge, Lu Ren, Xinkun Suo
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Materials & Design
Subjects:
Fe-C-Cr-Mn-Si steel
Machine learning
Conditional generative adversarial networks
Solid solution strengthening
Firefly optimization algorithm
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127524008487
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