Strain induced transformation of retained austenite in TRIP aided steels: A neural network model

Abstract

A neural network model has been developed to predict the strain induced transformation behaviour of retained austenite in transformation induced plasticity aided steels, as a function of the driving force for martensitic transformation, initial retained austenite content, matrix microstructure and forming conditions. The model was found to make realistic predictions that generally agree with established metallurgical principles and other published data.

Keywords

TRIP NEURAL NETWORKS RETAINED AUSTENITE MARTENSITIC TRANSFORMATION DRIVING FORCE

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