Flow stress model for hydrogen degraded Inconel 718

Ehrlin, Niklas; Fisk, Martin; Bjerkén, Christina

doi:10.1016/j.mechmat.2018.01.007

Cited by 5 publications

(1 citation statement)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model proposed by Lindgren et al [ 14 ] included dynamic strain aging in Equation (21) but has been excluded in the current work. It is also possible to include Hydrogen Enhanced Localized Plasticity (HELP) in a similar way as shown in [ 29 ].…”

Section: Materials Modelmentioning

confidence: 99%

Mechanism Based Flow Stress Model for Alloy 625 and Alloy 718

et al. 2020

Self Cite

View full text Add to dashboard Cite

To predict the final geometry in thermo-mechanical processes, the use of modeling tools is of great importance. One important part of the modeling process is to describe the response correctly. A previously published mechanism-based flow stress model has been further developed and adapted for the nickel-based superalloys, alloy 625, and alloy 718. The updates include the implementation of a solid solution strengthening model and a model for high temperature plasticity. This type of material model is appropriate in simulations of manufacturing processes where the material undergoes large variations in strain rates and temperatures. The model also inherently captures stress relaxation. The flow stress model has been calibrated using compression strain rate data ranging from 0.01 to 1 s−1 with a temperature span from room temperature up to near the melting temperature. Deformation mechanism maps are also constructed which shows when the different mechanisms are dominating. After the model has been calibrated, it is validated using stress relaxation tests. From the parameter optimization, it is seen that many of the parameters are very similar for alloy 625 and alloy 718, although it is two different materials. The modeled and measured stress relaxation are in good agreement.

show abstract

Section: Materials Modelmentioning

confidence: 99%