|About this Abstract
||2023 TMS Annual Meeting & Exhibition
||Quantifying Microstructure Heterogeneity for Qualification of Additively Manufactured Materials
||Control of Residual Stress and Distortion in Metal Additive Manufacturing via Inverse Mapping of Textures
||Ruoqi Gao, Hamid Garmestani, Steven Y. Liang
|On-Site Speaker (Planned)
The objective of this work is to develop a computational-mechanics texture-driven platform for predicting and controlling residual stress and part distortion in metal additive manufacturing (AM) via inverse mapping of microstructure in the fusion process parameter space. While previous studies on distortion issue have neglected the consideration of microstructure attributes, this work takes into account the effect of texture development and its gradient on residual stress by considering the anisotropic attributes of mechanical properties via crystal plasticity modeling. This work simulated the thermal deposition and temperature profiles of Ti-6Al-4V in a full-field closed-form solution for significant computational speed compared to numerically-iterative techniques. It will be followed by the prediction of texture development, texture-induced anisotropic mechanical properties, and residual stress considering materials property anisotropy. This work can further link the AM process parameters to microstructure and then to the final residual stress development and part distortion in explicit expression forms.
||Additive Manufacturing, Modeling and Simulation,