| dc.description.abstract | Uncertainty Quantification (UQ) and its subsequent propagation are powerful tools for estimating material property and performance distributions. As the paradigm of materials discovery within an Integrated Computational Materials Engineering framework continues to mature, so does the need for UQ to validate behavior predictions of new and existing materials. In this work, UQ is combined with physics informed models, high fidelity simulations, and statistical optimization techniques to characterize the high-strain-rate response of AF9628 and the dwell fatigue life of Ti-6Al-4V. Three specific instances involving the characterization of these materials using uncertainty quantification, and propagation, are presented.
First, a technique of information fusion called Reification, is used to combine constitutive models and experimental data to obtain a high-strain-rate performance boundary of AF9628. A range of model parameter values is also determined and is then propagated through a high fidelity simulation software to further estimate material property boundaries.
In the second study, the distribution of material density obtained via the high fidelity simulation is re-weighted, using a newly developed technique, Probability Law Optimized Weights (PLOW). The purpose of PLOW is to adjust a proposal distribution generated from a sub-set of inputs such that it more accurately reflects the target distribution generated from the full set of inputs. The method is particularly useful when computational limits prevent evaluation of the entire input set.
In the third study, 2-dimensional measurements of Microtextured Regions (MTRs) in Ti-6Al-4V are used to infer the size of the 3-dimensional MTRs from which they are sectioned. This distribution of estimated sizes is then propagated through a dwell fatigue model to study the influence of measurement type on the expected fatigue life for the near alpha titanium alloy. | |
