University of Leicester
Browse
- No file added yet -

Modeling of cavity nucleation, early‐stage growth, and sintering in polycrystal under creep–fatigue interaction

Download (4.15 MB)
journal contribution
posted on 2022-03-02, 11:20 authored by Jingdong Hu, Changjun Liu, Fuzhen Xuan, Bo Chen
A mechanistic-based cavitation model that considers nucleation, early-stage growth, and sintering under creep–fatigue interaction is proposed to predict the number density of cavities ρ. Both the nucleation and early-stage growth rates, controlled by grain boundary (GB) sliding under tension, are formulized as a function of local normal stress σn. Cavity sintering that occurs during the compression is governed by the unconstrained GB diffusion depending on the σn. Modeling results provide important insights into experimental load-waveform design. First, test with initial compression promotes higher ρ compared to the initial tension, if the unbalanced hold time in favor of tension is satisfied. Second, the ρ value does not have a monotonic dependence on either the compressive hold time or stress, because of their competing effect on nucleation and sintering. Third, the optimum value of stress variation rate exists in terms of obtaining the highest ρ value due to sintering effect.

Funding

China Scholarship Council (CSC), Grant/Award Number: 201906740075; EPSRCEarly Career Fellowship Scheme, Grant/Award Number: EP/R043973/1; EastChina University of Science andTechnology

History

Citation

Fatigue Fract Eng Mater Struct.2022;1–22

Author affiliation

School of Engineering

Version

  • VoR (Version of Record)

Published in

Fatigue & Fracture of Engineering Materials & Structures

Volume

45

Issue

3

Publisher

Wiley

issn

8756-758X

eissn

1460-2695

Acceptance date

2021-12-22

Copyright date

2022

Available date

2022-03-02

Language

en

Usage metrics

    University of Leicester Publications

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC