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Stochastic modeling of the polygonal microstructures of alloys using representative microscopic images

Kunjam, P and Shashidhar, K and Rakesh, S and Mahapatra, DR (2021) Stochastic modeling of the polygonal microstructures of alloys using representative microscopic images. In: Materials Today Communications, 29 .

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Official URL: https://doi.org/10.1016/j.mtcomm.2021.102832


This paper proposes an algorithm to generate a statistically equivalent microstructure of alloys for polygonal mesh-based finite element modeling. Morphological and crystallographic characteristics obtained from scanning electron microscopy images of 2D surface slices are employed to generate the mesh. Titanium alloy microstructures are considered as an example to demonstrate the proposed method. The mean and standard deviation of the grain area distribution obtained from the images are employed as the statistical parameters. The algorithm uses the image data and applies perturbation using a distortion factor and Voronoi tessellation to generate the statistically equivalent polygonal microstructure that captures the randomness of grain shape and size iteratively. The grain area distribution of the simulated microstructure closely matches with the actual distribution. Lower-order elements (quadrilateral) on the domain boundary get introduced that may create artifacts when analyzed with the finite element method. A method to eliminate these artifacts is presented with an analysis of stress concentrations occurring due to grain orientation mismatch. Effective mechanical properties, deformation, and fracture behavior as a function of various microstructural parameters like grain area and crystallographic orientations can be analyzed using the polygonal finite element mesh. © 2021 Elsevier Ltd

Item Type: Journal Article
Publication: Materials Today Communications
Publisher: Elsevier Ltd
Additional Information: The copyright for this article belongs to Elsevier Ltd
Keywords: Finite element method; Fracture mechanics; Iterative methods; Mesh generation; Microstructure; Scanning electron microscopy; Stochastic models; Titanium alloys, Crystallographic characteristics; Crystallographic orientations; Grain area; Microscopic image; Morphological characteristic; Multiscale modeling; Polygonal meshes; Scanning electron microscopy image; Stochastic-modeling; Stochastics, Stochastic systems
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 01 Feb 2022 12:34
Last Modified: 01 Feb 2022 12:34
URI: http://eprints.iisc.ac.in/id/eprint/71192

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