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Massively parallel FFT-based simulation to analyze the behavior of architected SiC/SiC composite tubes from synchrotron X-ray tomography

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Résumé

Silicon carbide (SiC) is a material of interest for nuclear applications because of its stability at high temperature and under irradiation. In contrast with monolithic ceramics, architected SiC/SiC composites exhibit a quasi-ductile and reproducible behavior. Therefore, they are promising candidates for future fuel cladding tube applications. The apparent ductility of SiC/SiC composites comes from the progressive development of a network of micro-cracks. Damage mechanisms have been deeply studied from biaxial tests on tubes together with surface observations and Digital Image Correlation. To go further, in-situ tensile tests are performed on the X-ray tomography beamline Psiché (synchrotron SOLEIL) to characterize the 3D evolution of cracks (spatial distribution, orientation, …). In order to discuss these results, numerical simulations are performed from the 3D images. Thanks to its massively parallel implementation, the FFT-based code AMITEX_FFTP [2] allows the simulation of large experimental unit-cells with high resolutions (1977x1977x555 in this case) to be realized. The non-classical use of FFT-based algorithm to simulate the response of a tube is discussed and the different pre-treatments (segmentation, alignment) performed on the 3D images to feed the numerical simulation are described. Finally, stress distributions are analyzed with respect to the microstructure and compared to the crack distributions to discuss the influence of the microstructure on damage mechanisms.
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Dates et versions

hal-01629681 , version 1 (06-11-2017)

Identifiants

  • HAL Id : hal-01629681 , version 1

Citer

Yang Chen, Lionel Gélébart, Franck Ouaki, Julien Derouillat, Cédric Sauder, et al.. Massively parallel FFT-based simulation to analyze the behavior of architected SiC/SiC composite tubes from synchrotron X-ray tomography. 8th International Conference on Multiscale Materials Modeling, Oct 2016, Dijon, France. ⟨hal-01629681⟩
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