Microstructurally-short crack growth driving force identification: combining DCT, PCT, crystal plasticity simulation and machine learning technique

Abstract : Identifying the Microstructurally-Short Crack (MSC) growth driving force of polycrystalline engineering alloys is a critical need in assessing performances of materials subject to fatigue load and to improve both material design and component life prediction. However, due to (i) the lack of “cycle-by-cycle” experimental data, (ii) the complexity of MSC growth phenomenon, and (iii) the incomplete physics of constitutive relationships, only simple driving force metrics, inadequate to predict MSC growth, have been postulated. Based on experimental results by Ludwig, Guilhem, et al., “cycle-by-cycle” data of a MSC propagating through a beta-metastable titanium alloy are available via phase and diffraction contrast tomography. To identify the crack driving force, we developed a framework utilizing the aforementioned experimental results and FFT-based crystal plasticity simulations (to compute micromechanical fields not available from the experiment). These results are combined and converted into probability distributions for use in a Bayesian Network.
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https://hal.archives-ouvertes.fr/hal-02116315
Contributor : Yoann Guilhem <>
Submitted on : Tuesday, April 30, 2019 - 7:26:57 PM
Last modification on : Thursday, June 6, 2019 - 5:24:02 PM

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  • HAL Id : hal-02116315, version 1

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Andrea Rovinelli, Michael D. Sangid, Ricardo A. Lebensohn, Wolfgang Ludwig, Yoann Guilhem, et al.. Microstructurally-short crack growth driving force identification: combining DCT, PCT, crystal plasticity simulation and machine learning technique. 3rd International Congress on 3D Materials Science (3DMS 2016), Jul 2017, St. Charles, United States. ⟨hal-02116315⟩

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