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Losch K, Schuff S, Balle F, et al. A stochastic microstructure model for particle reinforced aluminium matrix composites. J Microsc. 2018;273(2):115-126doi: 10.1111/jmi.12766.
Losch, K., Schuff, S., Balle, F., Beck, T., & Redenbach, C. (2019). A stochastic microstructure model for particle reinforced aluminium matrix composites. Journal of microscopy, 273(2), 115-126. https://doi.org/10.1111/jmi.12766
Losch, K, et al. "A stochastic microstructure model for particle reinforced aluminium matrix composites." Journal of microscopy vol. 273,2 (2019): 115-126. doi: https://doi.org/10.1111/jmi.12766
Losch K, Schuff S, Balle F, Beck T, Redenbach C. A stochastic microstructure model for particle reinforced aluminium matrix composites. J Microsc. 2019 Feb;273(2):115-126. doi: 10.1111/jmi.12766. Epub 2018 Nov 16. PMID: 30444272.
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J Microsc. 2019 Feb;273(2):115-126. doi: 10.1111/jmi.12766. Epub 2018 Nov 16.

A stochastic microstructure model for particle reinforced aluminium matrix composites.

Journal of microscopy

K Losch, S Schuff, F Balle, T Beck, C Redenbach

Affiliations

  1. Department of Mathematics, Technische Universität Kaiserslautern, Kaiserslautern, Germany.
  2. Institute of Materials Science and Engineering, Technische Universität Kaiserslautern, Kaiserslautern, Germany.
  3. Institut für Nachhaltige Technische Systeme (INATECH), Albert-Ludwigs-Universität Freiburg, Freiburg, Germany.

PMID: 30444272 DOI: 10.1111/jmi.12766

Abstract

Metal matrix composites are complex materials consisting of various phases which can display largely different mechanical properties. The deformation behaviour of these composites cannot be sufficiently modelled by averages or simple particle shapes due to the local stresses that occur on the particle edges. Therefore, a sophisticated model of the microstructure is needed. We introduce a method for stochastic modelling of a silicon carbide (SiC) particle reinforced aluminium matrix composite. The SiC particles are modelled by Laguerre polyhedra generated by densely packed spheres. The shape factors of the polyhedra have been fitted to the particle shapes observed in three-dimensional images. Particle elongation in extrusion direction and the observed log-normal volume distribution of the particles are included in the model by suitable scaling. An outlook is presented on how to model the grains of the polycrystalline aluminium matrix and intermetallic precipitates, which result from the strengthening mechanism of the matrix. LAY DESCRIPTION: Metal matrix composites are complex materials consisting of different phases which can display largely different mechanical properties. The deformation behaviour of these composites cannot be sufficiently modelled by averages or simple particle shapes due to the local stresses that occur on the particle edges. Therefore, a sophisticated model of the microstructure is needed. We introduce a method of stochastic modelling of a silicon carbide (SiC) particle reinforced aluminium matrix composite. The SiC particles are modelled by Laguerre polyhedra generated by densely packed spheres. The shape factors of the polyhedra have been fitted to the SiC shapes observed in three-dimensional images. Additionally, the polyhedra are scaled anisotropically to account for orientation anisotropy and to obtain a log-normal volume distribution. An outlook is presented on how to model the aluminium phase's grains and intermetallic precipitates, which result from the strengthening mechanism of the aluminium matrix alloy.

© 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

Keywords: Aluminium matrix composite; metal matrix composite; microstructural model; silicon carbide particles; volume images

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