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A comparative study of phenomenological, physically-based and artificial neural network models to predict the Hot flow behavior of API 5CT-L80 steel

Hassan Ahmadi, H. R. Rezaei Ashtiani, Mohammad Heidari

2020Materials Today Communications59 citationsDOI

Topics & Concepts

Materials scienceFlow stressPhenomenological modelArtificial neural networkPredictabilityDynamic recrystallizationStrain rateDeformation (meteorology)Flow (mathematics)MechanicsComposite materialHot workingMicrostructureStatisticsComputer scienceMathematicsArtificial intelligencePhysicsMetallurgy and Material FormingMicrostructure and Mechanical Properties of SteelsMetal Alloys Wear and Properties
A comparative study of phenomenological, physically-based and artificial neural network models to predict the Hot flow behavior of API 5CT-L80 steel | Litcius