Georgia Tech's Participation in the Mosaic of Microstructures MURI
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Rapid execution of PBM has strong implications on materials design and multi scale modeling. Effective Models via the Materials Knowledge System The MKS extends Nonlinear Systems Theory to provide a fast, accurate, and parallizable representation of otherwise costly physics based models (PBM). Influence Coefficients are calibrated from PBM and they capture the influence of the local configurations of the μS upon the salient response field. Response Field Strain, Stress, Evolution Microstructure (μS) Discrete, Continuum Accurate Prediction of High Contrast Composite Elastic Strain Fields Prediction of Spinodal Decomposition Evolution F a s t , S c a l a b l e L i n k a g e s Computational Times FEM – 45 Minutes - Supercomputer MKS – 15 seconds - PC
description
An illustration of the Materials Knowledge Systems generated by calibrating Volterra kernels to materials science simulation. The slide provides the comprehensive application of microstructure informatics and its impact on materials design.
Transcript of Georgia Tech's Participation in the Mosaic of Microstructures MURI
Rapid execution of PBM has strong implications on materials design and multi scale modeling.
Effective Models via the Materials Knowledge SystemThe MKS extends Nonlinear Systems Theory to provide a fast, accurate, and parallizable representation of otherwise costly physics based models (PBM).
Influence Coefficients are calibrated from PBM and they capture the influence of the local configurations of the μS upon the salient response field.
Response FieldStrain, Stress, Evolution
Microstructure (μS)Discrete, Continuum
Accurate Prediction of High Contrast Composite Elastic Strain Fields
Prediction of Spinodal DecompositionEvolution Fast, Scalable Linkages
Computational TimesFEM – 45 Minutes - SupercomputerMKS – 15 seconds - PC
Structure-Processing MKSProcessing History
Structure-PropertyHomogenization
Structure-Property MKS Localization
This MURI will advance the μS informatics framework to increasingly complex material systems such as multi-ferroics and polycrystalline metal alloys.
Novel μS Informatics Systems for Inverse Materials DesignμS informatics is a data-driven framework that facilitates efficient objective μS classification
and allows robust mining of the underlying structure-property-processing linkages.
Sunderaraghavan ComerBouman
VoorheesChoudary
