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Journal article

Computational predictions of hydrogen-assisted fatigue crack growth

Abstract:
A new model is presented to predict hydrogen-assisted fatigue. The model combines a phase field description of fracture and fatigue, stress-assisted hydrogen diffusion, and a toughness degradation formulation with cyclic and hydrogen contributions. Hydrogen-assisted fatigue crack growth predictions exhibit an excellent agreement with experiments over all the scenarios considered, spanning multiple load ratios, H pressures and loading frequencies. These are obtained without any calibration with hydrogen-assisted fatigue data, taking as input only mechanical and hydrogen transport material properties, the material’s fatigue characteristics (from a single test in air), and the sensitivity of fracture toughness to hydrogen content. Furthermore, the model is used to determine: (i) what are suitable test loading frequencies to obtain conservative data, and (ii) the underestimation made when not pre-charging samples. The model can handle both laboratory specimens and large-scale engineering components, enabling the Virtual Testing paradigm in infrastructure exposed to hydrogen environments and cyclic loading.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.ijhydene.2024.05.264

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


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Funder identifier:
https://ror.org/001aqnf71
Grant:
MR/V024124/1


Publisher:
Elsevier
Journal:
International Journal of Hydrogen Energy More from this journal
Volume:
72
Pages:
315-325
Publication date:
2024-05-29
Acceptance date:
2024-05-17
DOI:
EISSN:
1879-3487
ISSN:
0360-3199


Language:
English
Keywords:
Pubs id:
2004418
Local pid:
pubs:2004418
Deposit date:
2024-06-07

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