Direct comparison of microstructure-sensitive fatigue crack initiation via crystal plasticity simulations and in situ high-energy X-ray experiments

• Main Authors: Veerappan Prithivirajan, Priya Ravi, Diwakar Naragani, Michael D. Sangid
• Format: Article
• Language: English
• Published: Elsevier 2021-01-01
• Series: Materials & Design
• Subjects: Microstructure-based modeling; Selective laser melting; High cycle fatigue (HCF); Model validation; High-energy X-ray diffraction microscopy (HEDM)
• Online Access: http://www.sciencedirect.com/science/article/pii/S0264127520307516

The qualification of engineering materials requires extensive testing of the time-dependent performance of the material, namely the fatigue behavior. Model-based approaches for determining the fatigue behavior have presented a tangible step towards complementing and reducing the overall number of physical tests necessary to qualify a material for use in application. Yet, prior to the adoption of the model-based approaches, the model needs to be thoroughly validated, presenting challenges, including substantiating the model's ability to capture the correct physics for crack initiation, which is difficult provided the multiple length-scales of the problem. In this paper, a methodology and demonstration for validating the location of microstructure-sensitive fatigue crack initiation as predicted by crystal plasticity finite element (CPFE) simulations, using high-energy X-ray diffraction and tomography experiments are presented. Realistic 3D microstructural models are created for the material of interest, IN718 (produced via additive manufacturing), with different twin instantiations, based on the experimental data for use in the CPFE simulations. The location of failure predicted using the extreme values of failure metrics (plastic strain accumulation and plastic strain energy density) resulted in an unambiguous one-to-one correlation with the experimentally observed location of crack-initiation for the models with statistical twin instantiations.