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Zhenlei Li
Zhenlei Li

Public Documents 2
Nonlinear fatigue life prediction model based on isodamage curve considering two-bloc...
Jiangbo Fan
Yuheng Yun

Jiangbo Fan

and 5 more

September 22, 2023
A non-linear life prediction model considering the loading history is proposed based on isodamage curve. The stress-controlled low-high block loading at high temperature, with variously previous cycles, was performed on a nickel-based superalloy. The damage evolvement of the prior loading was revealed using scanning electron microscopy under the low-high block loading, especially the failure mechanism of coaxing effect. In addition, load history correlation factor was introduced to describe the influence of prior-cycle. Based on the Ni-based superalloy, the life prediction model of two-step loading, including the low-high block (LH) and high-low block loading (HL), was proposed, agreeing well with the experimental results for different metals. Comparing with other life prediction models, the proposed model demonstrated the higher prediction accuracy and wider applicability.
Combined tension and bending fatigue life assessment method of blade-like specimen co...
Zhenlei Li
Jiangbo Fan

Zhenlei Li

and 6 more

April 18, 2023
This paper proposes a novel combined cycle fatigue life prediction method of a blade-like specimen considering the effect of multiple damage modes and complex stress state. Combined tensile and bending fatigue (CTBF) experiments were performed on a blade-like specimen at 850°C, using a novel biaxial tension-vibration test system. To account for the effect of high stress ratio related creep on bending fatigue damage, a creep damage factor was proposed and explicitly introduced into Lemaitre-Chaboche model. In the framework of continuum damage mechanics (CDM), the CTBF life was assessed considering the geometry-stress gradient feature factor and multiple damage modes, including the damage of LCF, high stress ratio bending fatigue and oxidation. Finally, a novel CTBF life prediction model was proposed, agreeing well with the experimental results. Compared with the existing classical models, the proposed model provides the significantly higher prediction accuracy.

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