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Experimentally Validated and Empirically Compared Machine Learning Approach for Predicting Yield Strength of Additively Manufactured Multi-Principal Element Alloys from Co–Cr–Fe–Mn–Ni System

Abhinav Chandraker, Sampad Barik, Nichenametla Jai Sai, Ankur Chauhan

2024Metallurgical and Materials Transactions A14 citationsDOI

Topics & Concepts

Yield (engineering)Materials scienceInverseMicrostructureAlloyPrincipal component analysisEmpirical modelling3D printingComputer scienceProcess engineeringArtificial intelligenceMetallurgyMathematicsSimulationGeometryEngineeringAdditive Manufacturing Materials and ProcessesHigh Entropy Alloys StudiesTitanium Alloys Microstructure and Properties
Experimentally Validated and Empirically Compared Machine Learning Approach for Predicting Yield Strength of Additively Manufactured Multi-Principal Element Alloys from Co–Cr–Fe–Mn–Ni System | Litcius