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February 2, 2026steel research international0 citations

Experimental Study on Fatigue Crack Growth of Precorroded High‐Strength Steels

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ZFZhao FangFYFan YangYCYuyang Chen

Key Points

  • The study aims to understand how precorrosion affects the fatigue crack growth behavior of high-strength steels.
  • Conducted salt spray corrosion tests on compact tension specimens made of Q460C, Q550D, and Q690D.
  • Measured corrosion rates using mass loss and surface roughness techniques.
  • Compared material constants using Paris law and strain energy density factor with existing literature.
  • Developed a linear prediction model for material constants based on exposure time.
  • Corrosion pit depth and surface roughness increased with longer exposure times.
  • Material constants showed a decreasing trend for m and n, while log C increased and log A decreased with exposure time.
  • Data distributions for m and log C at various exposure times were normal, indicating a linear relationship with exposure time.
  • The proposed prediction model reliably forecasts fatigue resistance concerning m and log C but is not accurate for n and log A.

Abstract

To investigate the fatigue crack growth behavior of precorroded high‐strength steels, a salt spray corrosion test using compact tension specimens made of Q460C, Q550D, and Q690D is conducted, and the corrosion rate is studied by mass losses and surface roughness. The effect of precorrosion on fatigue crack growth behavior is discussed based on a fatigue crack growth test by comparing fitted material constants in the Paris law and the strain energy density factor equation with those in related literature and design codes. A prediction model to predict material constants with longer exposure time is proposed. The results show that corrosion pit depth and surface roughness generally increase with the increase in exposure time; The parameters, m and n , show a generally gradual decreasing trend while log C and log A increase and decrease, respectively, with increase in exposure time; The test data of m and log C at each exposure time demonstrate a normal distribution, and the means of the data show a linear correlation with exposure time. The proposed linear prediction model is proved feasible in predicting fatigue resistance, including m and log C in Paris law with longer exposure time, but it does not fit in predictions based on n and log A .

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Cite This Study

Fang et al. (2026) studied this question.

synapsesocial.com/papers/6980ffa4c1c9540dea812573https://doi.org/10.1002/srin.202500984
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