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steel_11
Figure 9 shows the relationship between the stress intensity factor at the crack tip and the size of pre-corrosion pits.
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By using the numerical fitting method, the regression formula to represent the relationship between the stress intensity factor and the depth of the pre-corrosion pits is derived as: = 0.273 . 0.731 (4)where KIS is the pre-corroded stress intensity factor, KI0 is the non-corroded stress intensity factor, and φ is the depth of corrosion pits.
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The fatigue life can be estimated according to the Paris formula [25].
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The Paris formula is shown as follows:
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= ∆
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(5)where da/dN is the fatigue crack propagation, ΔK is the stress intensity factor at the tip of cracks, and C and m are the equation coefficients, respectively.
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For the 42CrMo steel, the coefficients of C and m are taken as 4.349 × 10−12 and 3.07, respectively [40].
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Through the integration of Equation (5), the fatigue life of 42CrMo steel can be estimated as:
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where N is the fatigue life of pre-corroded specimens and N0 is the fatigue life of non-corroded specimens.
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Figure 9. The relationship between the stress intensity factor and the depth of pre-corrosion pits.
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Under different stress ranges and corrosion degrees, the residual fatigue life of pre-corrosion specimens is predicted through the use of Equation (7).
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The comparison of predicted fatigue life and experimental fatigue life is summarized in Table 3.
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Table 3. Comparison of predicted fatigue life and experimental fatigue life.
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Table 2 shows that the fatigue life predicted by the coupled formula agreed well with experiment results, and the percentage errors between predicted values and experimental values were less than 10%.
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In the case of low corrosion degrees and low stress levels, the percentage errors were less than 5%.
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With the increase of pre-corroded time and stress levels, the percentage error was increased to approximately 9.3%.
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The stress intensity factor at the tip of cracks was calculated on the basis of the linear elastic model and the morphology of the pre-corrosion pits simulated by FEM took pre-set defects in the middle of the specimen, while the practical corrosion pits had the characteristics of the uneven distribution and size of the specimen.
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Thus, the percentage errors between the predicted values and the experimental values were slightly increased with the increase of pre-corroded time and stress levels.
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4. Recommendation for Future Research
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In this research, the effect of pre-corrosion pits on the residual fatigue life of the 42CrMo steel was experimentally and numerically studied.
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It was demonstrated in this paper that the corrosion pit size can be used as a damage index to assess the residual fatigue life.
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Therefore, the monitoring of corrosion pit size is important not only to know the corrosion status, but also to predict the residual fatigue life of the steel.
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With the recent development of structural health monitoring technology [41–44], especially the piezoceramic-based active sensing method [45–47], electromechanical impedance (EMI) approach [48–50], and imaging technology [51,52], it is now possible to monitor corrosion pit number and size [10].
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Future work should include the real-time monitoring of the onset and growth of the corrosion pit and the prediction of the residual fatigue life of the 42CrMo steel specimens.
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Future works should also focus on the quantitative analysis of corrosion pits to improve the predicted accuracy of the residual fatigue life for the corroded 42CrMo steel.
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5. Conclusions
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In summary, this study investigated the effect of pre-corrosion pits on the residual fatigue life of the 42CrMo steel.
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It was found that higher stress amplitude and longer pre-corroded time significantly decreased the residual fatigue life of the steel.
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The investigation of the residual fatigue life of pre-corrosion specimens was conducted through the use the regression formula and experimental measures, and the fatigue life predicted by the regression formula agreed well with experiment results.
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Moreover, it was found that the rate of crack extension accelerated when the crack length increased.
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It is also demonstrated in this paper that the corrosion pit size can be used as a damage variable to assess the residual fatigue life.
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The recommendation for future research is to monitor corrosion pit characteristics and to predict the residual fatigue life of the 42CrMo steel.
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Author Contributions:
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Conceptualization, D.L.; methodology, D.L. and J.Z.; software, D.L. and Y.L.; validation, Y.L.; formal analysis, X.X.; writing—original draft preparation, D.L.; writing—review and editing, X.X.; visualization, Y.L.; supervision, X.X.; project administration, D.L.
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Funding:
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This research was funded by Hubei Superior and Distinctive Discipline Group of “Mechatronics and Automobiles” (No.XKQ2019009).
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Conflicts of Interest:
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The authors declare no conflict of interest.
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