A Mathematical Formulation to Estimate the Effect of Grain Refiners on the Ultimate Tensile Strength of Al-Zn-Mg-Cu Alloys
作者： Halil Kurt , Murat Oduncuoglu , Mehmet Kurt
DOI: 10.3390/MET5020836
关键词:
摘要: In this study, the feed-forward (FF) neural networks (NNs) with back-propagation (BP) learning algorithm is used to estimate ultimate tensile strength of unrefined Al-Zn-Mg-Cu alloys and refined by Al-5Ti-1B Al-5Zr master alloys. The obtained mathematical formula presented in great detail. designed NN model shows good agreement test results can be predict Additionally, effects scandium (Sc) carbon (C) rates are investigated using proposed equation. It was observed that properties improved addition 0.5 Sc 0.01 C wt.%.
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