Using the finite cell method to predict crack initiation in ductile materials AITranslate
Abstract AITranslate
Highlights • Finite cell method is developed for predicting the crack initiation location. • Numerical 2D and 3D examples are solved to demonstrate the efficiency of the FCM. • Ductile Lemaitre damage model is implemented in a high order finite element code known as AdhoC. In this paper, the Finite Cell Method (FCM) is used to predict the crack evolution in ductile materials under small strains and nonlinear isotropic hardening conditions. The FCM is the result of combining the p-version finite element and fictitious domain methods, and has been shown to be effective in solving problems with complicated geometries for which the meshing procedure can be quite expensive. The crack evolution is introduced to the constitutive equations by using the simplified Lemaitre ductile damage model. The performance of the method is verified by means of two numerical examples in both 2D and 3D problems.
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DOI:https://doi.org/10.1016/j.commatsci.2013.10.012
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Highlights • Finite cell method is developed for predicting the crack initiation location. • Numerical 2D and 3D examples are solved to demonstrate the efficiency of the FCM. • Ductile Lemaitre damage model is implemented in a high order finite element code known as AdhoC. In this paper, the Finite Cell Method (FCM) is used to predict the crack evolution in ductile materials under small strains and nonlinear isotropic hardening conditions. The FCM is the result of combining the p-version finite element and fictitious domain methods, and has been shown to be effective in solving problems with complicated geometries for which the meshing procedure can be quite expensive. The crack evolution is introduced to the constitutive equations by using the simplified Lemaitre ductile damage model. The performance of the method is verified by means of two numerical examples in both 2D and 3D problems.
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| GB/T 7714-2015 | [1] M. Ranjbar, M. Mashayekhi, J. Parvizian, et al. Computational Materials Science, 2014(82). DOI:10.1016/j.commatsci.2013.10.012. |
| MLA | [1] M. Ranjbar, et al., Computational Materials Science, no. 82, 2014, https://doi.org/10.1016/j.commatsci.2013.10.012. |
| APA | [1] M. Ranjbar, M. Mashayekhi, J. Parvizian, A. Düster, & E. Rank. (2014). Computational Materials Science(82). https://doi.org/10.1016/j.commatsci.2013.10.012 |
| IEEE | [1] M. Ranjbar, M. Mashayekhi, J. Parvizian, A. Düster, and E. Rank, Computational Materials Science, no. 82, 2014, doi: 10.1016/j.commatsci.2013.10.012. |
