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<p>In this paper, a probabilistic crystal plasticity modelling framework is proposed to consider the influence of material variability (including material properties and microstructure) on the fatigue life of notched components. First, a dual-scale crystal plasticity finite element (CPFE) model is incorporated to predict the cyclic plasticity and fatigue damage of notched components. Specifically, new fatigue indicator parameters considering the mean stress effect are developed for fatigue life prediction under different stress ratios. Subsequently, by quantifying the material variability based on the CPFE method, a framework for probabilistic fatigue life prediction is then established. The simulation results based on the V-notched specimen of Ni-based superalloy GH4169 can well describe the scatter of experimental fatigue life, which confirms the feasibility of the proposed method.</p>

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Probabilistic crystal plasticity modelling framework for notch fatigue assessment under material variability

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Xing Zhang,
  • Shun-Peng Zhu,
  • Jin-Chao He,
  • Rui Liu,
  • Wei Li,
  • Qiang Liu,
  • Shiyong Qin,
  • Qingyuan Wang

摘要

In this paper, a probabilistic crystal plasticity modelling framework is proposed to consider the influence of material variability (including material properties and microstructure) on the fatigue life of notched components. First, a dual-scale crystal plasticity finite element (CPFE) model is incorporated to predict the cyclic plasticity and fatigue damage of notched components. Specifically, new fatigue indicator parameters considering the mean stress effect are developed for fatigue life prediction under different stress ratios. Subsequently, by quantifying the material variability based on the CPFE method, a framework for probabilistic fatigue life prediction is then established. The simulation results based on the V-notched specimen of Ni-based superalloy GH4169 can well describe the scatter of experimental fatigue life, which confirms the feasibility of the proposed method.