The correlation between fracture mechanics parameters and creep crack growth rate of Al 7050-T73651 at elevated temperature

Abachi, P.; Purazrang, K.

doi:10.1016/j.engfracmech.2015.06.023

Cited by 5 publications

(1 citation statement)

References 18 publications

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“…This is one factor to get accurate estimation of SIF in the crack growth propagation. The stresses at the crack tip and deformation can change depending on time or cycles (Abachi and Purazrang, 2015;Nejati et al, 2015). In LEFM, the SIF and the strain energy release rate are needed as the fracture criteria to determine the complication of crack tip at stress field.…”

Section: Introductionmentioning

confidence: 99%

Analysis of stress intensity factor for fatigue crack using bootstrap S-version finite element model

Noh

Romlay

Liang

et al. 2020

IJSI

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PurposeFailure of the materials occurs once the stress intensity factor (SIF) overtakes the material fracture toughness. At this level, the crack will grow rapidly resulting in unstable crack growth until a complete fracture happens. The SIF calculation of the materials can be conducted by experimental, theoretical and numerical techniques. Prediction of SIF is crucial to ensure safety life from the material failure. The aim of the simulation study is to evaluate the accuracy of SIF prediction using finite element analysis.Design/methodology/approachThe bootstrap resampling method is employed in S-version finite element model (S-FEM) to generate the random variables in this simulation analysis. The SIF analysis studies are promoted by bootstrap S-version Finite Element Model (BootstrapS-FEM). Virtual crack closure-integral method (VCCM) is an important concept to compute the energy release rate and SIF. The semielliptical crack shape is applied with different crack shape aspect ratio in this simulation analysis. The BootstrapS-FEM produces the prediction of SIFs for tension model.FindingsThe mean of BootstrapS-FEM is calculated from 100 samples by the resampling method. The bounds are computed based on the lower and upper bounds of the hundred samples of BootstrapS-FEM. The prediction of SIFs is validated with Newman–Raju solution and deterministic S-FEM within 95 percent confidence bounds. All possible values of SIF estimation by BootstrapS-FEM are plotted in a graph. The mean of the BootstrapS-FEM is referred to as point estimation. The Newman–Raju solution and deterministic S-FEM values are within the 95 percent confidence bounds. Thus, the BootstrapS-FEM is considered valid for the prediction with less than 6 percent of percentage error.Originality/valueThe bootstrap resampling method is employed in S-FEM to generate the random variables in this simulation analysis.

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Section: Introductionmentioning

confidence: 99%