A fully-coupled hydrogen diffusion computational model for single crystal nickel-based superalloy
In the future of hydrogen economy, one of the major applications for superalloys used in gas turbines is to operate in hydrogen environments that are known to have detrimental effects, causing hydrogen embrittlement. Understanding the underlying mechanisms of crack initiation and growth due to hydrogen embrittlement is important for ensuring the structural integrity of metallic structures, especially used in gas turbines. In the present study, a finite-element approach was developed to simulate the full coupling of deformation and hydrogen diffusion in single-crystal Ni superalloy. To implement the constitutive equations for hydrogen diffusion, user-defined subroutines were developed in Abaqus: a URDFIL was used to compute the pressure gradient by accessing the stress field during the analysis and a UEXPAN to evaluate diffusion-assisted deformation. Then, a notch geometry was modelled employing a crystal plasticity formulation implemented via a UMAT to determine the mechanical deformation and hydrostatic stress state. The analogy between heat transfer and transient hydrogen diffusion is adopted due to the equivalency of variables associated with the two types of analysis. The fully-coupled analysis was validated against the Abaqus built-in sequentially-coupled analysis. The normalized hydrogen concentration as a function of distance from the crack tip and the stress gradient around the notch were evaluated. The obtained results showed that the implementation of user-defined subroutines within Abaqus to model fully-coupled hydrogen diffusion was successful. The method will be further developed to model hydrogen traps and the influence of microstructural traps on hydrogen-assisted fatigue.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023)Volume
1Pages
1143–1154Source
UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023)Publisher
SpringerVersion
- AM (Accepted Manuscript)
Rights holder
© The Author(s), under exclusive license to Springer Nature Switzerland AGPublisher statement
This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-49413-0_88. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-termsPublication date
2024-05-30Copyright date
2024ISBN
9783031494208; 9783031494215ISSN
2211-0984eISSN
2211-0992Publisher version
Book series
Mechanisms and Machine ScienceLanguage
- en