Fatigue crack growth versus plastic CTOD in the 304L stainless steel

Antunes, F.V.; Ferreira, Marques; Branco, R.; Prates, Pedro A.; Gardin, C.; Sarrazin-Baudoux, C.

doi:10.1016/j.engfracmech.2019.04.013

Cited by 34 publications

(13 citation statements)

References 53 publications

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“…Note that the 12th node is at a distance of 96 μm from crack tip, ie, nearly 0.1 mm. The da/dN‐δ p models developed for nodes 1 and 12 were, respectively:

\frac{da}{dN} = 0.003374 \times δ_{p}^{3} + 0.014074 \times δ_{p}^{2} ‐ 0.000047 \times δ_{p},

\frac{da}{dN} = 0.017034 \times δ_{p}^{3} + 0.067298 \times δ_{p}^{2} 0.002689 \times δ_{p} .

…”

Section: Numerical Resultsmentioning

confidence: 99%

“…These 2 models were obtained at a stress ratio R = 0.1 and plane strain state. They were subsequently used to predict d a /d N for other stress ratios ( R = −0.1; 0.3; 0.5 and 0.7) in plane stress and plane strain conditions . Figure compares the predictions obtained with these models based on nodes 1 and 12.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The rate of variation of CTOD p increases progressively with load. In previous works, the plastic CTOD range, δ p , was correlated with fatigue crack growth rate, assuming that FCG is controlled by crack tip plastic deformation and that δ p is able to quantify this deformation.…”

Section: Numerical Determination Of Plastic Ctod δPmentioning

confidence: 99%

“…Assuming that fatigue crack growth is linked to crack tip cyclic plastic deformation, a model d a /d N ‐ δ p was proposed, where δ p is the range of plastic CTOD. This approach has several advantages, namely, the natural inclusion of crack closure, the nonconsideration of elastic deformation and the ability to predict the effect of stress state, stress ratio, overloads, and load blocks, at least in qualitative terms …”

Section: Introductionmentioning

confidence: 99%

“…This approach has several advantages, namely, the natural inclusion of crack closure, the nonconsideration of elastic deformation and the ability to predict the effect of stress state, stress ratio, overloads, and load blocks, at least in qualitative terms. 3 The CTOD is a classical fracture parameter, which has also been used to study fatigue crack propagation (FCP). Pelloux,4 using microfractography, showed that the concept of CTOD allowed the prediction of fatigue striations spacing and therefore of crack growth rate.…”

mentioning

confidence: 99%

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Numerical determination of plastic CTOD

Antunes

Díaz

Vasco-Olmo

et al. 2018

Fatigue Fract Eng Mat Struct

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In previous works, a da/dN versus plastic crack tip opening displacement model was proposed to study fatigue crack growth. The plastic crack tip opening displacement, δp, which quantifies the crack tip plastic deformation, is determined numerically using the finite element method. The predictions are affected by different numerical parameters which must be identified and studied. The main parameters are the crack propagation distance, the distance of measurement points relatively to the crack tip, the size of crack tip elements, and the number of load cycles between crack increments. Some crack propagation is required for the stabilization of δp, which occurs when δp reaches its minimum value. The measurement point behind crack tip has a major effect on δp. The peak value occurs at the first node behind crack tip and a progressive decrease of sensitivity is observed with the increase of distance to crack tip. A mesh refinement study showed a coincidence of the predictions obtained with different meshes, which is a good indication for the robustness of the procedure. Finally, there is a significant effect of the number of load cycles between crack increments, NLC, in the presence of crack closure. The increase of NLC reduces the crack opening level and so increases δp.

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“…Note that the 12th node is at a distance of 96 μm from crack tip, ie, nearly 0.1 mm. The da/dN‐δ p models developed for nodes 1 and 12 were, respectively:

\frac{da}{dN} = 0.003374 \times δ_{p}^{3} + 0.014074 \times δ_{p}^{2} ‐ 0.000047 \times δ_{p},

\frac{da}{dN} = 0.017034 \times δ_{p}^{3} + 0.067298 \times δ_{p}^{2} 0.002689 \times δ_{p} .

…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Determination Of Plastic Ctod δPmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Numerical determination of plastic CTOD

Antunes

Díaz

Vasco-Olmo

et al. 2018

Fatigue Fract Eng Mat Struct

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A level set model for stress‐dependent corrosion pit propagation

Dekker

Meer

Maljaars

et al. 2021

Numerical Meth Engineering

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A numerical model for corrosion pit propagation under mechanical loading is presented. The level set method is used for corrosion front tracking and also enables the domain to be split into a solid and a pit domain. In the pit the diffusion of atoms originating from the dissolution process occurring at the pit front is simulated. The model is capable of automatically capturing lacy cover formation due to the inclusion of activation control, diffusion control, and passivation. In the solid static equilibrium is solved to obtain strains and stresses. A parameter, dependent on the signs of the plastic strain increment and the back stress, is introduced to define the influence of plasticity on the corrosion rate. The model is used to study pit growth under electrochemical and mechanical loading. Under activation control combined with an elastic material response, pits propagate faster under constant loading than under cyclic loading. When plastic deformation occurs, cyclic loading can significantly increase the pit growth rate. Increasing the cyclic load frequency results in faster propagation due to kinematic hardening. Under diffusion control, mechanical loading does not influence the pit growth rate, given that the salt layer leading to diffusion control remains intact.

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