Prediction of corrosion fatigue crack growth rate in alloys. Part I: General corrosion fatigue model for aero-space aluminum alloys

Kovalov, Danyil; Fekete, Balázs; Engelhardt, George R.; Macdonald, Digby D.

doi:10.1016/j.corsci.2018.06.034

Cited by 26 publications

(12 citation statements)

References 21 publications

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“…At stress levels of 100 and 125 MPa, the crack growth curves (Figure 7) show a significant decrease in crack growth rate in the EXCO environment, and a significant quantity of corrosion product is observed in the propagation zone (Figure 9). This is attributed to passivation of the crack tip and inhibition of crack propagation by the crack closure effect 34 . In the EXCO environment, as shown in Figure 13A, the matrix around the crack tip undergoes anodic dissolution (

Al \to {Al}^{3 +} + 3 e^{‐}

), and hydrolysis of metal ions proceeds with secondary reactions (

{Al}^{3 +} + 3 H_{2} normalO \to 3 H^{+} + Al {(OH)}_{3}

), resulting in the corrosion product Al(OH) 3 stacking.…”

Section: Discussionmentioning

confidence: 99%

“…This is attributed to passivation of the crack tip and inhibition of crack propagation by the crack closure effect. 34 In the EXCO environment, as shown in Figure 13A, the matrix around the crack tip undergoes anodic dissolution (Al ! Al 3þ þ 3e -), and hydrolysis of metal ions proceeds with secondary reactions…”

Section: Fatigue Damage Evolution Characteristicsmentioning

confidence: 99%

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Fatigue damage evolution and failure of pre‐corroded aluminum alloy 7075‐T651 under air and corrosion environments

Song

Jiang

Sun

et al. 2023

Fatigue Fract Eng Mat Struct

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This paper presents characterization for fatigue failure analysis of precorroded AA7075‐T651 under air and exfoliation corrosion (EXCO) environments, with respect to damage accumulation, macrocrack and microcrack behavior via 3D digital image correlation (DIC), scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD). It is shown that that corrosion pits induce fatigue cracking with different nucleation times, and locations. It is furthermore shown that while the corrosive environment accelerates crack formation, it significantly hinders fatigue crack propagation at low stress amplitudes due to crack closure and tip passivation. Five dominant fatigue microcrack initiation types (pit bottom, corrosion tunnel, corrosion micropit, corrosion jut‐in, and chapped feature) and relevant mechanisms were identified, related to corrosion pit macro–micro morphology, material microdefect, local material grain structure, and loading condition.

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Al \to {Al}^{3 +} + 3 e^{‐}

), and hydrolysis of metal ions proceeds with secondary reactions (

{Al}^{3 +} + 3 H_{2} normalO \to 3 H^{+} + Al {(OH)}_{3}

), resulting in the corrosion product Al(OH) 3 stacking.…”

Section: Discussionmentioning

confidence: 99%

Section: Fatigue Damage Evolution Characteristicsmentioning

confidence: 99%

Fatigue damage evolution and failure of pre‐corroded aluminum alloy 7075‐T651 under air and corrosion environments

Song

Jiang

Sun

et al. 2023

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

show abstract

“…Factors influencing CF have long been categorised into mechanical, metallurgical, and environmental (Wei and Speidel 1972). Some mechanical factors include peak stress (Zhao et al 2017), cyclic frequency, stress ratio, load waveform (Adedipe et al 2016;Igwemezie and Mehmanparast 2020), residual stress (RS) ; metallurgical factors like alloy composition, microstructure (Nicolas et al 2019), wielding defects, heat treatment (Mehmanparast et al 2017); environmental factors like pH (Kolawole et al 2019), temperature (Atkinson and Chen 1993), electrochemical potential (Kovalov et al 2018), inhibitors (Lindley and Rudd 2001). Material and environmental factors including temperature and pH seem to have a direct impact on pitting CF.…”

Section: Understanding Fatigue and Corrosion In Offshore Structuresmentioning

confidence: 99%

A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines

Okenyi

Bodaghi

Mansfield

et al. 2022

Ships and Offshore Structures

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Digital tools such as machine learning and the digital twins are emerging in asset management of offshore wind structures to address their structural integrity and cost challenges due to manual inspections and remote sites of offshore wind farms. The corrosive offshore environments and salt-water effects further increase the risk of fatigue failures in offshore wind turbines. This paper presents a review of corrosion fatigue research in horizontal-axis offshore wind turbines (HAOWT) support structures, including the current trends in using digital tools that address the current state of asset integrity monitoring. Based on the conducted review, it has been found that digital twins incorporating finite element analysis, material characterisation and modelling, machine learning using artificial neural networks, data analytics, and internet of things (IoT) using smart sensor technologies, can be enablers for tackling the challenges in corrosion fatigue (CF) assessment of offshore wind turbines in shallow and deep waters.

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“…At present, many scholars have established a variety of the corrosion FCP rate models, most of which are modified based on the Paris model. 17,18 Wang R considered the crack closure effect and the process of metal surface exposure, crack tip passivation, and re-sharpening during the corrosion FCP. The Paris model was modified by introducing the corrosion FCP coefficient B f .…”

Section: Introductionmentioning

confidence: 99%

Effect of corrosion on the fatigue crack propagation properties of butt weld with G20Mn5QT cast steel and Q355D steel in 3.5‐wt% NaCl solution

Han,

Li,

et al. 2023

Fatigue Fract Eng Mat Struct

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The corrosion fatigue crack propagation (FCP) of the butt weld with G20Mn5QT cast steel and Q355D steel in 3.5‐wt% NaCl solution was investigated experimentally. Considering the influences of stress ratio and loading frequency, the corrosion FCP rate curve was obtained. The results indicated that the corrosion FCP rate in the corrosion environment is three times that in air. Increasing the stress ratio or decreasing the loading frequency will increase the corrosion FCP rate. The fracture morphology of the specimens in the corrosion environment had more corrosion pits and intergranular characteristics due to anodic dissolution than that in air. Anodic dissolution and hydrogen embrittlement jointly promoted the corrosion FCP of butt weld in simulated seawater. The corrosion FCP rate model was established considering the effects of stress ratio and loading frequency.

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Prediction of corrosion fatigue crack growth rate in alloys. Part I: General corrosion fatigue model for aero-space aluminum alloys

Cited by 26 publications

References 21 publications

Fatigue damage evolution and failure of pre‐corroded aluminum alloy 7075‐T651 under air and corrosion environments

Fatigue damage evolution and failure of pre‐corroded aluminum alloy 7075‐T651 under air and corrosion environments

A review of challenges and framework development for corrosion fatigue life assessment of monopile-supported horizontal-axis offshore wind turbines

Effect of corrosion on the fatigue crack propagation properties of butt weld with G20Mn5QT cast steel and Q355D steel in 3.5‐wt% NaCl solution

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