Probabilistic Prediction of Location-Specific Microstructure in Turbine Disks

While there are established methods available in determining the fatigue life of critical rotating components, there is still room for improvement for better understanding and prediction of life limiting factors. Improved risk assessment of jet engine disk components would require probabilistic modeling capability of the evolution of microstructural features, residual stresses and material anomalies as the disk components undergo thermo-mechanical processing. Currently, the integrated process modeling system DEFORM can only predict the evolution of microstructure deterministically during thermo-mechanical processing. Scientific Forming Technologies Corporation is teaming with Carnegie Mellon University in this project. The objective of this project is to develop a probabilistic modeling framework that enables probabilistic prediction of microstructure evolution and bulk residual stresses due to thermo-mechanical processing. The probabilistic modeling framework in DEFORM will enable the user to systematically analyze the variabilities and uncertainties associated with the processing conditions, boundary conditions, material properties and incoming starting grain size distribution of the billet material, thus providing a probabilistic location specific microstructure response which can be used as an input to the probabilistic lifing model. At the end of phase I, we intend to demonstrate a proof of concept models for probabilistic grain size evolution and residual stresses as a result of thermo-mechanical processing. Our team will work closely with a major jet engine OEM, GE Aviation to develop an implementation and a validation plan. It is envisioned that the implementation and validation of probabilistic modeling of microstructure evolution will be undertaken in the phase II of this project.