کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1576542 1514778 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Microstructural prediction through artificial neural network (ANN) for development of transformation induced plasticity (TRIP) aided steel
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد دانش مواد (عمومی)
پیش نمایش صفحه اول مقاله
Microstructural prediction through artificial neural network (ANN) for development of transformation induced plasticity (TRIP) aided steel
چکیده انگلیسی

The prediction of the amount of retained austenite as a function of chemical composition and heat treatment is important for achieving the desired properties in TRIP (Transformation Induced Plasticity) aided steel. In the present work, three experimental steels (CMnSiAlP, CMnSiAlNb and CMnSiNb) made in vacuum induction furnace were suitably heat treated in hot dip processing simulator (HDPS) to produce multiphase TRIP microstructure. The process parameters were determined with the aid of multilayered perception (MLP) based artificial neural network (ANN) models in combination with the results of the study of the transformation behaviour. Amount of retained austenite in microstructure measured by optical microscopy and X-ray diffraction technique had shown a good agreement with that predicted through the afore mentioned model. All three alloys were found to have an excellent strength–ductility balance and significantly good strain hardening exponent (n) value. Among the three grades, CMnSiAlNb grade was observed to have a better combination of properties in terms of high strength and ductility.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Materials Science and Engineering: A - Volume 565, 10 March 2013, Pages 148–157
نویسندگان
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