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Open AccessFeature PaperArticle

Indirect Reconstruction of Pore Morphology for Parametric Computational Characterization of Unidirectional Porous Iron

Faculty of Mechanical Engineering, University of Maribor, 2000 Maribor, Slovenia
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Materials 2018, 11(2), 193; https://doi.org/10.3390/ma11020193
Received: 18 December 2017 / Revised: 23 January 2018 / Accepted: 24 January 2018 / Published: 26 January 2018
(This article belongs to the Section Porous Materials)
This paper addresses the problem of reconstructing realistic, irregular pore geometries of lotus-type porous iron for computer models that allow for simple porosity and pore size variation in computational characterization of their mechanical properties. The presented methodology uses image-recognition algorithms for the statistical analysis of pore morphology in real material specimens, from which a unique fingerprint of pore morphology at a certain porosity level is derived. The representative morphology parameter is introduced and used for the indirect reconstruction of realistic and statistically representative pore morphologies, which can be used for the generation of computational models with an arbitrary porosity. Such models were subjected to parametric computer simulations to characterize the dependence of engineering elastic modulus on the porosity of lotus-type porous iron. The computational results are in excellent agreement with experimental observations, which confirms the suitability of the presented methodology of indirect pore geometry reconstruction for computational simulations of similar porous materials. View Full-Text
Keywords: porous iron with unidirectional pores; compressive elastic properties; computational simulations; finite element analysis porous iron with unidirectional pores; compressive elastic properties; computational simulations; finite element analysis
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Kovačič, A.; Borovinšek, M.; Vesenjak, M.; Ren, Z. Indirect Reconstruction of Pore Morphology for Parametric Computational Characterization of Unidirectional Porous Iron. Materials 2018, 11, 193.

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