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3D modelling of ceramic composites and simulation of their electrical, thermal and elastic properties AITranslate

Fraunhofer Institute for Silicate Research ISC;Fraunhofer Institute for Silicate Research ISC
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Publisher: Elsevier
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Abstract AITranslate

Highlights • Finite element simulation of modelled microstructures’ macroscopic properties. • Computational approach for the accurate 3D modelling of ceramic microstructures. • The effect of the grain boundaries was included in the model. • Impedance spectra, thermal conductivity, and elastic constants were simulated. • Macroscopic properties of porous zirconia–alumina ceramics were simulated. This work presents a computational approach for the accurate three-dimensional modelling of ceramic microstructures and the finite element simulation of their macroscopic properties. Especially, the effect of the grain boundaries was included in the model, as well as the capability to represent multiple phase materials. The model was adapted to corresponding real microstructures with the help of quantitative image analysis of 2D cross sections. Initially, flexible voxel based representative volume elements were used. To be suitable for finite element simulations, an adapted surface tesselation was created from the voxel model, where all the relevant structural parameters were kept constant while the model size was decimated to about 10% of the initial size. In this representation, grain boundaries were introduced by computing a thin offset mesh for each interface. The grain boundary turned out to be essential when impedance spectra were to be simulated, as the electrical conductivity and the dielectric properties both contribute to the complex response to the harmonic electric excitation. Following this approach, the macroscopic properties of porous zirconia–alumina ceramics could be simulated with an accuracy of >90%, as investigated at several ratios of mixture, ranging from pure alumina to pure zirconia.

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DOI:https://doi.org/10.1016/j.commatsci.2013.08.013

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Citation Information:

Highlights • Finite element simulation of modelled microstructures’ macroscopic properties. • Computational approach for the accurate 3D modelling of ceramic microstructures. • The effect of the grain boundaries was included in the model. • Impedance spectra, thermal conductivity, and elastic constants were simulated. • Macroscopic properties of porous zirconia–alumina ceramics were simulated. This work presents a computational approach for the accurate three-dimensional modelling of ceramic microstructures and the finite element simulation of their macroscopic properties. Especially, the effect of the grain boundaries was included in the model, as well as the capability to represent multiple phase materials. The model was adapted to corresponding real microstructures with the help of quantitative image analysis of 2D cross sections. Initially, flexible voxel based representative volume elements were used. To be suitable for finite element simulations, an adapted surface tesselation was created from the voxel model, where all the relevant structural parameters were kept constant while the model size was decimated to about 10% of the initial size. In this representation, grain boundaries were introduced by computing a thin offset mesh for each interface. The grain boundary turned out to be essential when impedance spectra were to be simulated, as the electrical conductivity and the dielectric properties both contribute to the complex response to the harmonic electric excitation. Following this approach, the macroscopic properties of porous zirconia–alumina ceramics could be simulated with an accuracy of >90%, as investigated at several ratios of mixture, ranging from pure alumina to pure zirconia.

quote

GB/T 7714-2015 [1] T.M. Müller, F. Raether. Computational Materials Science, 2014(81). DOI:10.1016/j.commatsci.2013.08.013.
MLA [1] T.M. Müller, and F. Raether. Computational Materials Science, no. 81, 2014, https://doi.org/10.1016/j.commatsci.2013.08.013.
APA [1] T.M. Müller, & F. Raether. (2014). Computational Materials Science(81). https://doi.org/10.1016/j.commatsci.2013.08.013
IEEE [1] T.M. Müller and F. Raether, Computational Materials Science, no. 81, 2014, doi: 10.1016/j.commatsci.2013.08.013.