|About this Abstract
||2016 TMS Annual Meeting & Exhibition
||Computational Methods for Uncertainty Quantification, Model Validation, and Stochastic Predictions
||Microstructure-Uncertainty Propagation in Sheet Metal Forming FE-Simulations
||Stephen Niezgoda, Ayman A Salem, Joshua B Shaffer, Daniel P Satko
|On-Site Speaker (Planned)
Uncertainty in component performance arises due to material variability at multiple scales (e.g. variability between suppliers, batches, lots, and spatial locations within the same workpiece). Although military and international standards have reduced the variability in average macroscale properties, it is difficult to control the spatial fluctuations in local structure which result in spatially varying properties same preform. Reliable material processing simulation requires accurate characterization of the relationship between this variability of local structure and overall component response. Here we demonstrate a non-intrusive stochastic crystal plasticity finite element framework which predicts the variability in finished part performance metrics and taking the spatial statistics of the microstructure as input. Springback prediction during sheet metal forming is described as an initial case study. The mathematical formulation of the stochastic finite element framework and the constitutive theory will be discussed, as well as the experimental procedure for measuring the spatial variability in microstructure statistics.
||Planned: A print-only volume