Grain Size Effect on the Fatigue Behavior of 304 Stainless Steel and Fatigue Strength Prediction

As a critical load-bearing component, the material fatigue performance of wind turbine flanges directly affects the service life of wind turbines. In this study, four specimens with different grain sizes of 304 stainless steel (SS 304), a key material for wind turbine flanges, were prepared through rolling treatment. Tensile and high-cycle fatigue (HCF) tests were conducted to investigate the effect of grain size on its fatigue performance. The results indicate that both fatigue strength and fatigue life improve with an increase in the rolling deformation. A fatigue strength prediction model based on the Basquin equation was developed, incorporating the grain size effect as an innovation. By integrating fatigue experimental data from various metallic materials, the effectiveness of the model was validated. The average prediction error for all materials is within 10%, demonstrating high universality. This study provides new insights into the microstructural control of fatigue performance of SS 304 and offers significant engineering value for the optimization design of wind turbine flange materials and enhancing the service life of equipment.

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Publication Details

Journal
NANO
Published
2025-08-14
DOI
https://doi.org/10.1142/s1793292025501024
Primary Topic
Fatigue and fracture mechanics
Type
article
Field-Weighted Citation Impact
0.00

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article

Grain Size Effect on the Fatigue Behavior of 304 Stainless Steel and Fatigue Strength Prediction

Yuanji Gao, Yan Shi, Hongyan Duan
NANO
Fatigue and fracture mechanics
article

Grain Size Effect on the Fatigue Behavior of 304 Stainless Steel and Fatigue Strength Prediction

Yuanji Gao, Yan Shi, Hongyan Duan
article en

Abstract

As a critical load-bearing component, the material fatigue performance of wind turbine flanges directly affects the service life of wind turbines. In this study, four specimens with different grain sizes of 304 stainless steel (SS 304), a key material for wind turbine flanges, were prepared through rolling treatment. Tensile and high-cycle fatigue (HCF) tests were conducted to investigate the effect of grain size on its fatigue performance. The results indicate that both fatigue strength and fatigue life improve with an increase in the rolling deformation. A fatigue strength prediction model based on the Basquin equation was developed, incorporating the grain size effect as an innovation. By integrating fatigue experimental data from various metallic materials, the effectiveness of the model was validated. The average prediction error for all materials is within 10%, demonstrating high universality. This study provides new insights into the microstructural control of fatigue performance of SS 304 and offers significant engineering value for the optimization design of wind turbine flange materials and enhancing the service life of equipment.

NANO
Lanzhou University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 75%
Fatigue and fracture mechanics
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