|About this Abstract
||2018 TMS Annual Meeting & Exhibition
||Computational Method and Experimental Approaches for Model Development and Validation, Uncertainty Quantification, and Stochastic Predictions
||Property Localization: Quantifying the Uncertainty of Inferred Constitutive Models for Grain Boundaries
||Christian Kurniawan, Oliver K Johnson
|On-Site Speaker (Planned)
The space of all possible grain boundary characters is large and complex, making the development of constitutive models by testing individual bicrystals impractical both experimentally and computationally. In this talk we describe Property Localization, a high-throughput method for inferring grain boundary constitutive models from measurements (and/or simulations) made on polycrystals. The probabilistic framework on which Property Localization is built naturally facilitates uncertainty quantification for the resulting constitutive models.
||Planned: Supplemental Proceedings volume