Inverse Optimization and Design of Thermo-Mechanical Processing Paths for Improved Formability of Mg Alloys

Abstract

Commercial Mg alloys’ demand in aerospace and automotive applications have significantly increased due to its lightweight properties and higher mechanical strength than its aluminum counterparts. Processing Mg alloys into functional grades for industrial use, could reduce our carbon footprint by increasing the fuel efficiency of all modes of transportation. However, Mg alloys’ use in such applications is hindered by the lack of formability due to its lack of active slip systems at room temperature and increased twinning effects that promotes tension-compression yield asymmetry for the material. Therefore, forming Mg alloys into complex geometrical shapes such as a car bumpers, can lead to premature failures of the material at room temperature during forming. Multiple studies were conducted on Mg alloys to reduce the CRSS difference between basal and non-basal slip systems, but a different approach was considered in this study, instead of mitigating the difference in CRSS, steps were taken to engineer the anisotropy of the material using texture alterations to engineer the formability of these alloys. Equal Channel Angular Pressing (ECAP) has been used to alter the texture of Mg alloys to maximize formability. A relationship between texture anisotropy to ductility was considered that related Lankford coefficient measurements or R-value measurements to a single invariant parameter called the anisotropy effect on ductility (AED) parameter. Using AED, we can relate mechanical R-value measurements of ECAP materials to formability. To find the best route with highest formability a novel inverse optimization method was used to automatically derive ECAP routes from the plasticity properties of Mg alloys. The Visco-Plastic Self Consistent (VPSC) crystal plasticity model was used to simulate and predict mechanical properties and textures. New Optimization methods were used to calibrate the model with experimental results which revealed further improvements were required to model ECAP with good accuracy. With the addition of grain fragmentation and Hall-Petch effect to further improve the VPSC crystal plasticity model, texture, and mechanical property predictions after ECAP was conducted at a much higher accuracy than what was done before. This in turn improved the novel inverse optimization method in predicting new ECAP routes with superior formability.