Predicting of mechanical properties of Fe–Mn–(Al, Si) TRIP/TWIP steels using neural network modeling

In this work, an artificial neural network (ANN) model was established in order to predict the mechanical properties of transformation induced plasticity/twinning induced plasticity (TRIP/TWIP) steels. The model developed in this study was consider the contents of Mn (15–30 wt%), Si (2–4 wt%) and Al...

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Veröffentlicht in:	Computational materials science 2009-06, Vol.45 (4), p.959-965
Hauptverfasser:	Dini, G., Najafizadeh, A., Monir-Vaghefi, S.M., Ebnonnasir, A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural network (ANN) Condensed matter: structure, mechanical and thermal properties Deformation and plasticity (including yield, ductility, and superplasticity) Exact sciences and technology Mechanical and acoustical properties of condensed matter Mechanical properties Mechanical properties of solids Physics Steel TRIP/TWIP
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