|About this Abstract
||MS&T22: Materials Science & Technology
||Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
||Analyzing Uncertainty in Modeled Additive Process-Microstructure-Property Relationships Using the ExaAM Framework
||Matthew Rolchigo, John Coleman, Robert Carson, Gerry Knapp, Alex Plotkowski, Scott Wells, Samuel Reeve, Lyle Levine, Jim Belak, John Turner
|On-Site Speaker (Planned)
Modeling of additive process-microstructure-property relationships necessitates understanding and quantifying the sources of uncertainty in each model, as well as the result of input parameter uncertainty propagation on model results. Using pre-Exascale hardware and codes developed and modified as part of the ExaAM project, we use Tasmanian sparse grids to generate a range of values for several uncertain input parameters for AdditiveFOAM modeling of heat transport and ExaCA modeling of as-solidified grain structure, generating a large ensemble consisting of hundreds of simulated microstructures. Microstructures will be compared to an additive benchmark dataset for Inconel 625, and sensitivity of several aspects of the grain structures will be quantified as functions of model and input parameter uncertainties. ExaConstit will then be used to model the variation in constitutive properties using representative regions of the resulting microstructures, further linking the sensitivity of properties to processing and microstructure. Supported by ECP (17-SC-20-SC).