Numerical analysis of the indentation size effect using a strain gradient crystal plasticity model AITranslate
Abstract AITranslate
Highlights • We study indentation size effect via strain-gradient dependent crystal plasticity. • Numerical results are compared with analytical models and experiment measurements. • The transition between elastically- and plastically-dominated contact is captured. • A maximum in hardness as depth increases in tests with rounded tips is reproduced. This work presents a finite element analysis of the indentation size effect (ISE) experimentally observed in tests performed at submicron scale. A 3D model of a conical rigid surface indenting on a Nb single crystal at different depths has been developed. The bcc Nb material has been characterized within a finite-strain framework through a crystal plasticity model incorporating strain-gradient hardening. The hardness evolution for different material orientations and for different initial dislocation densities has been studied. The numerical results are compared with predictions of existing analytical models and with experimental results.
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DOI:https://doi.org/10.1016/j.commatsci.2013.10.004
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Highlights • We study indentation size effect via strain-gradient dependent crystal plasticity. • Numerical results are compared with analytical models and experiment measurements. • The transition between elastically- and plastically-dominated contact is captured. • A maximum in hardness as depth increases in tests with rounded tips is reproduced. This work presents a finite element analysis of the indentation size effect (ISE) experimentally observed in tests performed at submicron scale. A 3D model of a conical rigid surface indenting on a Nb single crystal at different depths has been developed. The bcc Nb material has been characterized within a finite-strain framework through a crystal plasticity model incorporating strain-gradient hardening. The hardness evolution for different material orientations and for different initial dislocation densities has been studied. The numerical results are compared with predictions of existing analytical models and with experimental results.
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| GB/T 7714-2015 | [1] D. González, J. Alkorta, J.M. MartínezEsnaola, et al. Computational Materials Science, 2014(82). DOI:10.1016/j.commatsci.2013.10.004. |
| MLA | [1] D. González, et al., Computational Materials Science, no. 82, 2014, https://doi.org/10.1016/j.commatsci.2013.10.004. |
| APA | [1] D. González, J. Alkorta, J.M. MartínezEsnaola, & J. Gil Sevillano. (2014). Computational Materials Science(82). https://doi.org/10.1016/j.commatsci.2013.10.004 |
| IEEE | [1] D. González, J. Alkorta, J.M. MartínezEsnaola, and J. Gil Sevillano, Computational Materials Science, no. 82, 2014, doi: 10.1016/j.commatsci.2013.10.004. |
