Modeling Yield Stress of Annealed Directed Energy Deposition of Ti-6Al-4V

Wednesday, May 9, 2018: 2:30 PM
Osceola 1-2 (Gaylord Palms Resort )
Dr. Peter Collins , Lehigh University, Bethlehem, PA
Dr. Gary Harlow , Lehigh University, Bethlehem, PA

Electron beam additive manufacturing (AM) of Ti-6Al-4V is a complicated process making modeling yield stress sY challenging. A primary difficulty is accurate measurement and control of process variables, which number in excess of twenty. The geometric structure of the build is problematical; it consists of multiple layers of various thicknesses of deposited Ti-6Al-4V. The number of layers varies in the plane of the build path and normal to it, depending on the geometry. Consequently, there is significant aleatoric variability in material composition and microstructure which causes substantial randomness in the sY. Also, there is epistemic uncertainty that cannot be ignored. Modeling sY of these builds must include both geometry and microstructure. A previously established physically based probability model for sY is further developed and used for the analysis of three different methods of post-deposition heat treatment: AM-a+β stress relief, AM-a+β HIP, and AM-β annealing. The critical random variables in the model are statistically characterized with appropriate cumulative distribution functions which are subsequently used for estimation and prediction of sY. Standard simulation techniques are used for the analyses. Afterwards, the simulated model results are calibrated with a subset of the sY data in order to minimize the effects of both types of uncertainty in the estimation and prediction. The chief purpose of this integrated modeling, microstructural analysis, and probability and statistics approach with calibration is to characterize sY, especially in the lower tail of its cumulative distribution function which is the essential region for high reliability estimation and prediction.

This material is based upon work supported by the Defense Advanced Research Projects Agency under Contract No. HR0011-12-C-0035. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Defense Advanced Research Projects Agency.