Journal ArticleDOI
Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures
Marat I. Latypov,Markus Kühbach,Irene J. Beyerlein,Jean Charles Stinville,Laszlo S. Toth,Tresa M. Pollock,Surya R. Kalidindi +6 more
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TLDR
In this paper, a quantification framework based on directionally resolved chord length distribution and principal component analysis is proposed to extract additional information from 2-D microstructural maps of polycrystalline materials.About:
This article is published in Materials Characterization.The article was published on 2018-11-01. It has received 39 citations till now. The article focuses on the topics: Recrystallization (geology).read more
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Chord-length distribution function for two-phase random media
Salvatore Torquato,B. Lu +1 more
TL;DR: In this article, the authors derived exact series representations of the chord-length distribution function for media comprised of spheres with a polydispersivity in size for arbitrary space dimension D. For the special case of spatially uncorrelated spheres (i.e., fully penetrable spheres), the first moment of p(z) was determined.
Journal ArticleDOI
Design and Tailoring of Alloys for Additive Manufacturing
TL;DR: In this article, a brief overview of the role of powders, as well as solidification and solid-state phase transformation phenomena typically encountered during fusion-based additive manufacturing is provided.
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Materials knowledge system for nonlinear composites
TL;DR: In this article, a new Materials Knowledge System framework for microstructure-sensitive predictions of effective stress-strain responses in composite materials is presented for composites with a wide range of combinations of strain hardening laws and topologies of the constituents.
Journal ArticleDOI
Graph Neural Networks for an Accurate and Interpretable Prediction of the Properties of Polycrystalline Materials
TL;DR: A graph neural network (GNN) model for obtaining an embedding of polycrystalline microstructure which incorporates not only the physical features of individual grains but also their interactions, which enables an accurate and interpretable prediction of the properties of poly Crystalline materials.
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Quantitative prediction of the aged state of Ni-base superalloys using PCA and tensor regression
TL;DR: Even though PCA provides an effective tool for visualization and classification of data, the model built based on the TR algorithm is shown to have stronger prediction capability.
References
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Journal ArticleDOI
LIII. On lines and planes of closest fit to systems of points in space
TL;DR: This paper is concerned with the construction of planes of closest fit to systems of points in space and the relationships between these planes and the planes themselves.
Book
The Superalloys: Fundamentals and Applications
TL;DR: In this paper, the physical metallurgy of nickel and its alloys is discussed and single crystal superalloys for blade applications for turbine disc applications are discussed. And the role of coatings is discussed.
Journal ArticleDOI
Algorithm for computer control of a digital plotter
TL;DR: An algorithm is given for computer control of a digital plotter that may be programmed without multiplication or division instructions and is efficient with respect to speed of execution and memory utilization.
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Grain size dependence of coercivity and permeability in nanocrystalline ferromagnets
TL;DR: In this article, a series of crystallized ribbons of composition Fe/sub 74.5-x/Cu/sub x/Nb/sub 3/Si/sub 13.5/B/sub 9/ (x=0, 1 at) have been annealed between about 500 degrees C and 900 degrees C.
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Texture Analysis with MTEX - Free and Open Source Software Toolbox
TL;DR: The MATLAB toolbox MTEX as discussed by the authors provides a unique way to represent, analyse and interpret crystallographic preferred orientation, i.e. texture based on integral (pole figure) or individual orientation (EBSD) measurements.