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Meeting 2025 TMS Annual Meeting & Exhibition
Symposium AI/Data Informatics: Computational Model Development, Verification, Validation, and Uncertainty Quantification
Presentation Title Uncertainty Quantification In Crystal Plasticity Simulations Using Multimodal High-Energy Synchrotron X-Ray Experiments
Author(s) Diwakar Naragani, Paul Shade, Armand Beaudoin, Donald Boyce
On-Site Speaker (Planned) Diwakar Naragani
Abstract Scope We present an integrated experiment-modeling framework to calibrate, validate, and develop crystal plasticity equations. In-situ X-ray diffraction microscopy characterizes intergranular lattice orientations and elastic strain tensors at designated states during R=-1 cyclic loading of a Ni-based superalloy. Complementary fields of grain-level stresses are generated via a crystal plasticity formulation with an Armstrong-Frederick-type hardening evolution law. A genetic algorithm generates several candidate parameter sets that serve as priors to a Bayesian workflow. The synthesis of simulated and measured stresses provides a basis for quantifying uncertainty in the model parameters. Parameter uncertainty is shown to reduce drastically when grain-level stresses are used to calibrate instead of a macroscopic stress-strain curve. Sensitivity analysis helps identify the relative importance of parameters and ill-conditioned equations in the CP implementation. A more applicable hardening law is developed by employing measured and simulated critical resolved shear stresses for each grain.
Proceedings Inclusion? Planned:
Keywords Modeling and Simulation, Characterization, Machine Learning

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