سال انتشار: ۱۳۹۱

محل انتشار: اولین همایش بین المللی و ششمین همایش مشترک انجمن مهندسی متالورژی ایران

تعداد صفحات: ۱۲

نویسنده(ها):

M. Marvi-Mashhadi – M.Sc. of Material Science & Engineering, Department of Material Science & Engineering, Ferdowsi
H. Vafaeenezhad –
S. Ghanei –
H. Beygi –

چکیده:

This study is intended to develop the potential of artificial neural networks (ANN) as an alternative modeling method for predicting the ultimate tensile stress (UTS) and morphology of dual-phase steels. The strategy of experiments consists of three inputs (intercritical annealing temperature, martensite volume fraction and manganese weight percent) and single-output (UTS and morphology) in different analysis steps. The comparison of neuralnetwork model and experimental data, which was obtained by standard tensile test, shows the ability of developed neural network used