Flow stress model for IN718 accounting for evolution of strengthening precipitates during thermal treatment AITranslate
Abstract AITranslate
Highlights • A physically based material model is coupled with a model for growth and coarsening. • The model for precipitate evolution accounts for nucleation, growth and coarsening. • Compression tests for solution annealed, half-aged and fully-aged material. • The material model shows good agreement with experimental measurements. • The model can be used in thermo-mechanical simulation of the ageing process in IN718. A flow stress model describing precipitate hardening in the nickel based alloy Inconel® 718 following thermal treatment is presented. The interactions between precipitates and dislocations are included in a dislocation density based material model. Compression tests have been performed using solution annealed, fully-aged and half-aged material. Models were calibrated using data for solution annealed and fully-aged material, and validated using data from half-aged material. Agreement between experimental data and model predictions is good.
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DOI:https://doi.org/10.1016/j.commatsci.2013.10.007
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Highlights • A physically based material model is coupled with a model for growth and coarsening. • The model for precipitate evolution accounts for nucleation, growth and coarsening. • Compression tests for solution annealed, half-aged and fully-aged material. • The material model shows good agreement with experimental measurements. • The model can be used in thermo-mechanical simulation of the ageing process in IN718. A flow stress model describing precipitate hardening in the nickel based alloy Inconel® 718 following thermal treatment is presented. The interactions between precipitates and dislocations are included in a dislocation density based material model. Compression tests have been performed using solution annealed, fully-aged and half-aged material. Models were calibrated using data for solution annealed and fully-aged material, and validated using data from half-aged material. Agreement between experimental data and model predictions is good.
quote
| GB/T 7714-2015 | [1] M. Fisk, J.C. Ion, L.E. Lindgren. Computational Materials Science, 2014(82). DOI:10.1016/j.commatsci.2013.10.007. |
| MLA | [1] M. Fisk, et al., Computational Materials Science, no. 82, 2014, https://doi.org/10.1016/j.commatsci.2013.10.007. |
| APA | [1] M. Fisk, J.C. Ion, & L.E. Lindgren. (2014). Computational Materials Science(82). https://doi.org/10.1016/j.commatsci.2013.10.007 |
| IEEE | [1] M. Fisk, J.C. Ion, and L.E. Lindgren, Computational Materials Science, no. 82, 2014, doi: 10.1016/j.commatsci.2013.10.007. |
