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    Rights statement: This is the author’s version of a work that was accepted for publication in Computer Methods in Applied Mechanics and Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Methods in Applied Mechanics and Engineering, 393, 2022 DOI: 10.1016/j.cma.2022.114811

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Adaptive stochastic morphology simulation and mesh generation of high-quality 3D particulate composite microstructures with complex surface texture

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Adaptive stochastic morphology simulation and mesh generation of high-quality 3D particulate composite microstructures with complex surface texture. / Huang, J.; Deng, F.; Liu, L. et al.
In: Computer Methods in Applied Mechanics and Engineering, Vol. 393, 114811, 01.04.2022.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Huang J, Deng F, Liu L, Ye J. Adaptive stochastic morphology simulation and mesh generation of high-quality 3D particulate composite microstructures with complex surface texture. Computer Methods in Applied Mechanics and Engineering. 2022 Apr 1;393:114811. Epub 2022 Mar 22. doi: 10.1016/j.cma.2022.114811

Author

Huang, J. ; Deng, F. ; Liu, L. et al. / Adaptive stochastic morphology simulation and mesh generation of high-quality 3D particulate composite microstructures with complex surface texture. In: Computer Methods in Applied Mechanics and Engineering. 2022 ; Vol. 393.

Bibtex

@article{c8738fcd2dba46a1889287cb416f63f2,
title = "Adaptive stochastic morphology simulation and mesh generation of high-quality 3D particulate composite microstructures with complex surface texture",
abstract = "Particulate composite materials have a broad range of potential applications in engineering and other disciplines. Accurate modeling of their microstructures and fast generation of the finite element meshes play a vital role in investigating many micromechanical phenomena and improving understanding of the underlying failure mechanisms. Due to the exceedingly intricate multiscale internal structures that they possess, the modeling and meshing of their microstructures still remain difficult in general. In this work, we present a computational framework and methodology for the representation, simulation, and mesh generation of 3D stochastic microstructures of particulate composites. Towards this goal, we propose a multi-level multiscale scheme that allows for capturing the multiscale structures of particulate composite materials at both the coarse and fine scales. A briging scale approach based on heat kernel smoothing is also presented to seamlessly link the coarse and fine scales. In addition to the microstructural modeling of particulate composite materials, we also develop an adaptive curvature-based surface and volume mesh generation algorithm for particulate composite microstructures with complex surface texture. Following the implementation of the morphology and mesh generation algorithm, a series of numerical examples are presented to demonstrate the capability and potential of the proposed method. ",
keywords = "Heat kernel smoothing, Microstructure, Particulate composite materials, Surface texture, Failure (mechanical), Glass ceramics, Morphology, Numerical methods, Stochastic systems, Textures, Complex surface, Composite microstructures, Fine-scale, Heat kernel, Kernel smoothing, Mesh generation algorithm, Particulate composite material, Particulate composites, Surface textures, Mesh generation",
author = "J. Huang and F. Deng and L. Liu and J. Ye",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Computer Methods in Applied Mechanics and Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Methods in Applied Mechanics and Engineering, 393, 2022 DOI: 10.1016/j.cma.2022.114811",
year = "2022",
month = apr,
day = "1",
doi = "10.1016/j.cma.2022.114811",
language = "English",
volume = "393",
journal = "Computer Methods in Applied Mechanics and Engineering",
issn = "0045-7825",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Adaptive stochastic morphology simulation and mesh generation of high-quality 3D particulate composite microstructures with complex surface texture

AU - Huang, J.

AU - Deng, F.

AU - Liu, L.

AU - Ye, J.

N1 - This is the author’s version of a work that was accepted for publication in Computer Methods in Applied Mechanics and Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Methods in Applied Mechanics and Engineering, 393, 2022 DOI: 10.1016/j.cma.2022.114811

PY - 2022/4/1

Y1 - 2022/4/1

N2 - Particulate composite materials have a broad range of potential applications in engineering and other disciplines. Accurate modeling of their microstructures and fast generation of the finite element meshes play a vital role in investigating many micromechanical phenomena and improving understanding of the underlying failure mechanisms. Due to the exceedingly intricate multiscale internal structures that they possess, the modeling and meshing of their microstructures still remain difficult in general. In this work, we present a computational framework and methodology for the representation, simulation, and mesh generation of 3D stochastic microstructures of particulate composites. Towards this goal, we propose a multi-level multiscale scheme that allows for capturing the multiscale structures of particulate composite materials at both the coarse and fine scales. A briging scale approach based on heat kernel smoothing is also presented to seamlessly link the coarse and fine scales. In addition to the microstructural modeling of particulate composite materials, we also develop an adaptive curvature-based surface and volume mesh generation algorithm for particulate composite microstructures with complex surface texture. Following the implementation of the morphology and mesh generation algorithm, a series of numerical examples are presented to demonstrate the capability and potential of the proposed method.

AB - Particulate composite materials have a broad range of potential applications in engineering and other disciplines. Accurate modeling of their microstructures and fast generation of the finite element meshes play a vital role in investigating many micromechanical phenomena and improving understanding of the underlying failure mechanisms. Due to the exceedingly intricate multiscale internal structures that they possess, the modeling and meshing of their microstructures still remain difficult in general. In this work, we present a computational framework and methodology for the representation, simulation, and mesh generation of 3D stochastic microstructures of particulate composites. Towards this goal, we propose a multi-level multiscale scheme that allows for capturing the multiscale structures of particulate composite materials at both the coarse and fine scales. A briging scale approach based on heat kernel smoothing is also presented to seamlessly link the coarse and fine scales. In addition to the microstructural modeling of particulate composite materials, we also develop an adaptive curvature-based surface and volume mesh generation algorithm for particulate composite microstructures with complex surface texture. Following the implementation of the morphology and mesh generation algorithm, a series of numerical examples are presented to demonstrate the capability and potential of the proposed method.

KW - Heat kernel smoothing

KW - Microstructure

KW - Particulate composite materials

KW - Surface texture

KW - Failure (mechanical)

KW - Glass ceramics

KW - Morphology

KW - Numerical methods

KW - Stochastic systems

KW - Textures

KW - Complex surface

KW - Composite microstructures

KW - Fine-scale

KW - Heat kernel

KW - Kernel smoothing

KW - Mesh generation algorithm

KW - Particulate composite material

KW - Particulate composites

KW - Surface textures

KW - Mesh generation

U2 - 10.1016/j.cma.2022.114811

DO - 10.1016/j.cma.2022.114811

M3 - Journal article

VL - 393

JO - Computer Methods in Applied Mechanics and Engineering

JF - Computer Methods in Applied Mechanics and Engineering

SN - 0045-7825

M1 - 114811

ER -