Open AccessReduced-Order Microstructure-Sensitive Models for Damage Initiation in Two-Phase Composites
Author(s) -
David Montes de Oca Zapiain,
Evdokia Popova,
Fadi F. Abdeljawad,
James W. Foulk,
Surya R. Kalidindi,
Hojun Lim
Publication year - 2018
Publication title -
integrating materials and manufacturing innovation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.878
H-Index - 22
eISSN - 2193-9772
pISSN - 2193-9764
DOI - 10.1007/s40192-018-0112-0
Subject(s) - microstructure , materials science , salient , phase (matter) , computer science , characterization (materials science) , sorting , material properties , biological system , composite material , artificial intelligence , nanotechnology , physics , algorithm , quantum mechanics , biology
Local features of the internal structure or the microstructure dominate the overall performance of materials. An open problem in materials design with enhanced properties is to accurately identify and quantify salient features of the microstructure and understand its correlation with the material’s performance. This task is exacerbated when dealing with failure related properties that show strong correlations to higher-order details of the material microstructure. This paper presents a novel data-driven framework for quantitatively determining the highly complex correlations that exist between the higher-order details of the material microstructure and its failure-related properties, specifically its damage initiation properties. The enclosed work will address this challenge by significantly extending the Materials Knowledge Systems (MKS) framework and by leveraging concepts in extreme value distributions and machine learning. The developed framework was capable of successfully sorting nine different classes of synthetically generated two-phase microstructures for their sensitivity to damage initiation. The framework and approaches presented here open new research avenues for studying the microstructure-sensitive damage initiation properties associated with heterogeneous materials, and pave the way forward for practical multiscale materials design.