Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6%Al-4%V titanium alloy

Mosleh, A.O and Mikhaylovskaya, A.V and Kotov, A.D and Kwame, J.S. (2019) Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6%Al-4%V titanium alloy. Journal of Manufacturing Processes, 45. pp. 262-272. ISSN 1526-6125

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    Abstract

    The study presents an integrated approach for superplastic forming of Ti-6%Al-4%V titanium alloy. The flow behavior of the studied alloy was investigated using uniaxial constant strain rate tensile tests in a temperature range of 800–900 °C and a strain rate range of 3 × 10−4–3 × 10-3s-1. The obtained flow behavior was modeled using the simple Johnson-Cook (S J-C), modified Johnson-Cook (M J-C) and artificial neural network (ANN) models. An assessment study between the constructed models was performed in order to evaluate the predictability of each model. Standard statistical comparative quantities such as correlation coefficient (R), mean absolute relative error (AARE) and the root mean square error (RMSE) were used to ascertain the model viability. The S J-C model proved ineffectual in predicting the flow behavior of Ti-6%Al-4%V alloy. The M J-C and ANN models are able to successfully describe the flow behavior of the alloy. The validity of the model used for the simulation was ascertained by testing the predicted data with the constructed models at a temperature of 875 °C and a strain rate of 2 × 10-3s-1 using DEFORM 3D finite element simulation (FES). The obtained results from the FES were verified with the experimental results after superplastic forming process. The FES results show the possibility of using uniaxial tensile test data to simulate superplastic forming process of the Ti-6%Al-4%V titanium sheets.

    Creators(s): Mosleh, A.O, Mikhaylovskaya, A.V, Kotov, A.D and Kwame, J.S. ORCID logoORCID: https://orcid.org/0000-0002-9583-0124;
    Item type:Article
    ID code:69009
    Keywords:titanium alloys, constitutive modeling, Johnson-Cook (J-C) models, artificial neural network, superplastic forming, finite elements analysis, Engineering design, Materials Science(all)
    Subjects:Technology > Engineering (General). Civil engineering (General) > Engineering design
    Department:Faculty of Engineering > Design, Manufacture and Engineering Management
    Depositing user: Pure Administrator
    Date deposited:24 Jul 2019 12:23
    Last modified:05 Sep 2020 04:23
    URI:https://strathprints.strath.ac.uk/id/eprint/69009
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