Enhanced processing map of Ti–6Al–2Sn–2Zr–2Mo–2Cr–0.15Si aided by extreme gradient boosting

Enhanced processing map of Ti–6Al–2Sn–2Zr–2Mo–2Cr–0.15Si aided by extreme gradient boosting

A processing map is required for Ti alloys to find processing parameters securing a high formability. This study adopted the extreme gradient boosting (XGB) approach of machine learning to predict a flow curve and plot a processing map with less experiments for the first time. The optimum XGB model...

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Bibliographic Details
Main Authors: Min Hwa Bae, Minseob Kim, Jinyeong Yu, Min Sik Lee, Sang Won Lee, Taekyung Lee
Format: Article
Language:English
Published: Elsevier 2022-10-01
Series:Heliyon
Subjects:
Metals forming and shaping
Metals and alloys
Deformation and fracture
Processing map
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844022022794

Internet

http://www.sciencedirect.com/science/article/pii/S2405844022022794

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