Microstructure evaluation and modelling the tensile strength and yield strength of titanium alloys
by P.S. Noori Banu; S. Devaki Rani
International Journal of Microstructure and Materials Properties (IJMMP), Vol. 14, No. 1, 2019

Abstract: The rationale of the current study was to develop artificial neural network (ANN) models of titanium alloys for predicting tensile strength and yield strength using the alloy composition and processing parameters as the inputs and validate the models through experimental evaluation and correlate with microstructure characteristics. The robustness of the model was tested through experimental evaluation of tensile strength in Ti-6Al-4V, Ti-5.8Al-4Sn-3.5 Zr-0.7Nb-0.5Mo-0.3 Si, Ti-3Al-8V-4Zr-6Cr-4Mo, and Ti-10V-2Fe-3Al alloys. Microstructure characteristics i.e., volume fraction of alpha, alpha grain area and Feret ratio of Ti, Ti-6Al-4V, Ti-6Al-5V, Ti-6Al-6V-2Sn, Ti-8Mn, and Ti-13V-11Cr-3Al correlated inversely with predicted tensile strength and yield strength. This three-tier validation ensures efficient performance of the developed ANN models.

Online publication date: Mon, 04-Mar-2019

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