Stochastic 3D microstructure modeling of twinned polycrystals for investigating the mechanical behavior of š¯›¾-TiAl intermetallics

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Date

2024-03-10

Authors

Rieder, Philipp
Neumann, Matthias
Monteiro Fernandes, Lucas
Mulard, Aude
Willot, FranƧois
Schmidt, Volker

Journal Title

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Volume Title

Publication Type

Wissenschaftlicher Artikel

Published in

Computational Materials Science, 2024

Abstract

A stochastic 3D microstructure model for polycrystals is introduced which incorporates two types of twin grains, namely neighboring and inclusion twins. They mimic the presence of crystal twins in -TiAl polycrystalline microstructures as observed by 3D imaging techniques. The polycrystal grain morphology is modeled by means of Voronoi and ā€“more generallyā€“ Laguerre tessellations. The crystallographic orientation of each grain is either sampled uniformly on the space of orientations or chosen to be in a twinning relation with another grain. The model is used to quantitatively study relationships between morphology and mechanical properties of polycrystalline materials. For this purpose, full-field Fourier-based computations are performed to investigate the combined effect of grain morphology and twinning on the overall elastic response. For -TiAl polycrystallines, the presence of twins is associated with a softer response compared to polycrystalline aggregates without twins. However, when comparing the influence on the elastic response, a statistically different polycrystalline morphology has a much smaller effect than the presence of twin grains. Notably, the bulk modulus is almost insensitive to the grain morphology and exhibits much less sensitivity to the presence of twins compared to the shear modulus. The numerical results are consistent with a two-scale homogenization estimate that utilizes laminate materials to model the interactions of twins.

Description

Faculties

FakultƤt fĆ¼r Mathematik und Wirtschaftswissenschaften

Institutions

Institut fĆ¼r Stochastik

Citation

DFG Project uulm

EU Project THU

Other projects THU

SMILE / SMILE: Datenbasierte stochastische 3D Strukturmodellierung fĆ¼r das automatische Lernen mechanischer Eigenschaften / BMBF / 01IS21091

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CC BY 4.0 International

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DOI external

DOI external

10.1016/j.commatsci.2024.112922

Institutions

Periodical

Degree Program

DFG Project THU

item.page.thu.projectEU

item.page.thu.projectOther

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Keywords

Stochastic 3D modeling, Polycrystalline material, Tessellation, Twinning, Crystallographic twin, Electron back-scattered diffraction, Fast Fourier transform, Elastic response, Full-field computation, Homogenization, DDC 500 / Natural sciences & mathematics