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Statistically Representative Three-Dimensional Microstructures Based on Orthogonal Observation Sections

Published

Author(s)

D M. Saylor, J Fridy, B S. El-Dasher, K Y. Jung, Anthony D. Rollett

Abstract

Techniques are described that have been used to create a statistically representative three-dimensional model microstructure for input into computer simulations using the geometric and crystallographic observations from two orthogonal sections through an aluminum polycrystal. Orientation maps collected on the observation planes are used to characterize the sizes, shapes, and orientations of grains. Using a voxel-based tessellation technique, a microstructure is generated with grains whose size and shape are constructed to conform to those measured experimentally. Orientations are then overlaid on the grain structure such that distribution of grain orientations and the nearest neighbor relationships, specified by the distribution of relative misorientations across grain boundaries, match the experimentally measured distributions. The techniques are applicable to polycrystalline materials with sufficiently compact grain shapes and can also be used to controllably generate a wide variety of hypothetical microstructures for initial states in computer simulations.
Citation
Metallurgical and Materials Transactions B-Process Metallurgy and Materials Processing Science

Keywords

computer simulation, microstructural model, microstructure quantification, misorientation distribution, Monte carlo, orientation distribution, orientation mapping

Citation

Saylor, D. , Fridy, J. , El-Dasher, B. , Jung, K. and Rollett, A. (2017), Statistically Representative Three-Dimensional Microstructures Based on Orthogonal Observation Sections, Metallurgical and Materials Transactions B-Process Metallurgy and Materials Processing Science (Accessed December 14, 2024)

Issues

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Created February 19, 2017