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Metals 2018, 8(9), 695; https://doi.org/10.3390/met8090695

Estimating the Effective Elastic Parameters of Nodular Cast Iron from Micro-Tomographic Imaging and Multiscale Finite Elements: Comparison between Numerical and Experimental Results

1
Engineering School, Fluminense Federal University, Rua Passo da Patria 156, Niterói 24210-240, Brazil
2
Institute of Computing, Fluminense Federal University, Rua Passo da Pátria 156, Niterói 24210-240, Brazil
3
Group of Experimental and Computational Mechanics, University of Brasília, Gama 72.405-610, Brazil
*
Authors to whom correspondence should be addressed.
Received: 1 August 2018 / Revised: 1 September 2018 / Accepted: 4 September 2018 / Published: 5 September 2018
(This article belongs to the Special Issue Cast Irons: Properties and Applications)
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Abstract

Herein, we describe in detail a methodology to estimate the effective elastic parameters of nodular cast iron, using micro-tomography in conjunction with multiscale finite elements. We discuss the adjustment of the image acquisition parameters, address the issue of the representative-volume choice, and present a brief discussion on image segmentation. In addition, the finite-element computational implementation developed to estimate the effective elastic parameters from segmented microstructural images is described, indicating the corresponding computational costs. We applied the proposed methodology to a nodular cast iron, and estimated the graphite elastic parameters through a comparison between the numerical and experimental results. View Full-Text
Keywords: nodular cast iron; effective Young’s modulus; computational homogenization; multiscale numerical methods; micro-CT; finite elements nodular cast iron; effective Young’s modulus; computational homogenization; multiscale numerical methods; micro-CT; finite elements
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Pereira, A.; Costa, M.; Anflor, C.; Pardal, J.; Leiderman, R. Estimating the Effective Elastic Parameters of Nodular Cast Iron from Micro-Tomographic Imaging and Multiscale Finite Elements: Comparison between Numerical and Experimental Results. Metals 2018, 8, 695.

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