|About this Abstract
||2016 TMS Annual Meeting & Exhibition
||Computational Methods for Uncertainty Quantification, Model Validation, and Stochastic Predictions
||Understanding the Effect of Experimental Uncertainty on the Multistage Fatigue Model
||Justin Hughes, William Williams, Mark F. Horstemeyer
|On-Site Speaker (Planned)
Understanding how the accuracy and precision of materials modeling is affected by calibration to uncertain data is necessary for the production of robust and reliable designs. By utilizing computational resources, monte carlo brute force methods can be employed to help understand how the variability of experiments affects modeling results. A monte carlo random sampling method is applied to the physically-based, microstructure sensitive MultiStage Fatigue (MSF) model and output distributions are quantified. Model sensitivities and uncertainties are investigated for experimentally derived parameters.
||Planned: A print-only volume