Statistical analysis of the influence of defects on fatigue life using a Gumbel distribution

Anderson, Kellie; Daniewicz, S.R.

doi:10.1016/j.ijfatigue.2018.03.008

Cited by 33 publications

(31 citation statements)

References 11 publications

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“…Following up, the statistical distribution of the very extremal defects are deduced by means of a maximum-likelihood function fit [62]. As suggested by preliminary studies in [12,14], the cumulative distribution of the extreme value distribution type 1 is utilised, to describe the extremal flaws (see Equation (13)). This methodology is invoked, as it is proposed to estimate the parameters of the distribution best by [63].…”

Section: Resultsmentioning

confidence: 99%

“…In order to enhance the survival probabilities of crucial cast components, it is therefore inevitable to consider local pore size distributions in the fatigue design process. Preliminary studies revealed that the statistical distribution of fatigue-initiating defect sizes in cast parts can be described well by extreme value statistics such as the generalized extreme value (GEV) distribution and extreme value distribution of type one [11,12,13,14]. The latter is also referred to as Gumbel distribution and facilitates the assessment of maximum extreme values of the distribution—see Equation (1) [15].…”

Section: Introductionmentioning

confidence: 99%

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Modification of a Defect-Based Fatigue Assessment Model for Al-Si-Cu Cast Alloys

et al. 2018

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Cast parts usually inherit internal defects such as micro shrinkage pores due to the manufacturing process. In order to assess the fatigue behaviour in both finite-life and long-life fatigue regions, this paper scientifically contributes towards a defect-based fatigue design model. Extensive fatigue and fracture mechanical tests were conducted whereby the crack initiating defect size population was fractographically evaluated. Complementary in situ X-ray computed tomography scans before and during fatigue testing enabled an experimental estimation of the lifetime until crack initiation, acting as a significant input for the fatigue model. A commonly applied fatigue assessment approach introduced by Tiryakioglu was modified by incorporating the long crack threshold value, which additionally enabled the assessment of the fatigue strength in the long-life fatigue regime. The presented design concept was validated utilising the fatigue test results, which revealed a sound agreement between the experiments and the model. Only a minor deviation of up to about five percent in case of long-life fatigue strength and up to about 9% in case of finite-lifetime were determined. Thus, the provided extension of Tiryakioglu’s approach supports a unified fatigue strength assessment of cast aluminium alloys in both the finite- and long-life regimes.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modification of a Defect-Based Fatigue Assessment Model for Al-Si-Cu Cast Alloys

et al. 2018

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“…The probabilistic Coffin-Manson strain fatigue life model was obtained by substituting Equation (18) with (21) and then substituting it with Equation (19). Hence, the newly proposed probabilistic modeling equations for the Coffin-Manson, Morrow, and SWT strain fatigue life models can be modeled as follows:…”

Section: Proposed Mathematical Model Based On Probabilistic For Straimentioning

confidence: 99%

“…In addition, the R 2 values exhibited a good agreement for the two strain life models of approximately 0.9833 and 0.9962 (Figures 18 and 20). In the meantime, some data from Figures 15,17,and 19 were indicated in beyond the boundary conditions because the results of fatigue life prediction between the measured strain life and proposed probabilistic models were not in the same range.…”

Section: Validation Of Fatigue Life Predictionmentioning

confidence: 99%

“…In non-Gaussian distributions, the fatigue life reliability and probability of structures are usually analyzed using statistical strain-and stress-life models, such as the Gumbel, Weibull, Gamma, lognormal, and logistic distributions. Anderson [19] proposed a statistical method to represent stress-fatigue life based on the Gumbel distribution. This researcher determined the influence of scale and location parameters on fatigue life prediction.…”

Section: Introductionmentioning

confidence: 99%

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Fatigue Reliability Assessment of an Automobile Coil Spring under Random Strain Loads Using Probabilistic Technique

Manouchehrynia

Abdullah

Singh

2019

Metals

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This paper presents a mathematical model to estimate strain-life probabilistic modeling based on the fatigue reliability prediction of an automobile coil spring under random strain loads. The proposed technique was determined using a probabilistic method of the Gumbel distribution for strain-life models of automobile suspension systems. Strain signals from different road excitations in experimental tests were measured. The probability density function of the Gumbel distribution was considered to estimate model parameters using maximum likelihood estimation (MLE). The Akaike information criterion (AIC) method was performed to specify which model can estimate the best fit model parameters. Results demonstrated a good agreement between the predicted fatigue lives of the proposed probabilistic model and the measured strain fatigue life models. The root-mean-square errors (RMSE) based on the Coffin–Manson, Morrow, and Smith–Watson–Topper strain-life models were approximately 0.00114, 0.00107, and 0.00509, respectively, indicating a high correlation with the proposed model and experimental data. The results demonstrated that the proposed probabilistic model is effective for the fatigue life prediction of automobile coil springs using strain and stress fatigue life approaches.

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A review on high-cycle fatigue size effect of selective laser melted metals

Zhao,

Yao,

Cao

et al. 2024

Applied Materials Today

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Statistical analysis of the influence of defects on fatigue life using a Gumbel distribution

Cited by 33 publications

References 11 publications

Modification of a Defect-Based Fatigue Assessment Model for Al-Si-Cu Cast Alloys

Modification of a Defect-Based Fatigue Assessment Model for Al-Si-Cu Cast Alloys

Fatigue Reliability Assessment of an Automobile Coil Spring under Random Strain Loads Using Probabilistic Technique

A review on high-cycle fatigue size effect of selective laser melted metals

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