Effect of In-situ heat treatment on flow stress behavior of 3D printed Ti-6Al-4V alloy under quasi-static and dynamic deformation: A comparative study through experimental and modelling through J-C Model and ANN approach

methods single scanning and in-situ heat treatment (double scanning), aimed at controlling the mechanical properties during fabrication via the selective laser melting (SLM) process. Using analytical techniques such as FESEM and EBSD images the phase present such as α, β, α′, and α + β and their evolution mechanisms were discussed critically in single scanned and in-situ heat treatment. The uniaxial tensile tests were carried out at different quasi-static (0.001 to 1 s ^− 1 ) and 0.001 to 1 s ^− 1 dynamic strain rate 10 to 500 s ^− 1 . Fractography was conducted on the deformed samples, Further, improved version of the Johnson-Cook model has been formulated by using the experimental parameters for the Ti6Al4V alloy, furthermore, an artificial neural network-based (ANN) predictive model was established to evaluate the flow stress response of the Ti-6Al-4V alloy across diverse loading conditions. The results demonstrated that the AI-based ANN model performs comparably to the modified Johnson-Cook model, with the predicted flow stress values showing strong agreement with those obtained using the Johnson-Cook (J-C) formulation.