Fatigue variability in Al–Si cast alloys

Casellas, Daniel; Pérez, Rebeca; Prado, J. M.

doi:10.1016/j.msea.2005.03.034

Cited by 45 publications

(27 citation statements)

References 16 publications

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“…To model the effect of structural defects on the fatigue performance of metals, two main approaches have been taken by researchers in the literature: (1) taking the entire pore size distribution into account [8,13,14] or (2) modeling the distribution of the largest defects or inclusions [4,15,16] that initiate fracture. For instance, the model of Yi et al [8,9] assumes that pore size follows the lognormal distribution, which is consistent with their histograms as well as statistical analysis of pore sizes for Mg alloy castings.…”

Section: A Defect Size Distributionmentioning

confidence: 99%

“…Equation [4] can be rearranged to obtain the inverse function of the Gumbel distribution for equivalent defect diameter as…”

Section: Estimating the Fatigue Life Distribution From The Defecmentioning

confidence: 99%

“…It has been of interest to engineers to model variability in fatigue life, so that parts can be designed accordingly. In a majority of the cases found in the literature, the variability in the fatigue life of aluminum alloy castings has been modeled by either the lognormal [3] or two-parameter Weibull, [2,4,5] the cumulative probability (P) functions of which are written as…”

Section: Introductionmentioning

confidence: 99%

“…Casellas et al [4] followed the approach taken by Jayatilaka and Trustrum [6] to fit a power equation to the upper tail of the defect size distribution, which was originally developed for ceramics. [7] Casellas et al showed that the Weibull modulus for the distribution of fatigue life is a function of the power of the equation fitted to the upper tail of the defect size distribution.…”

Section: Introductionmentioning

confidence: 99%

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Relationship between Defect Size and Fatigue Life Distributions in Al-7 Pct Si-Mg Alloy Castings

Tiryakioğlu

2009

Metall Mater Trans A

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A new method for predicting the variability in fatigue life of castings was developed by combining the size distribution for the fatigue-initiating defects and a fatigue life model based on the Paris-Erdog˘an law for crack propagation. Two datasets for the fatigue-initiating defects in Al-7 pct Si-Mg alloy castings, reported previously in the literature, were used to demonstrate that (1) the size of fatigue-initiating defects follow the Gumbel distribution; (2) the crack propagation model developed previously provides respectable fits to experimental data; and (3) the method developed in the present study expresses the variability in both datasets, almost as well as the lognormal distribution and better than the Weibull distribution.

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Section: A Defect Size Distributionmentioning

confidence: 99%

“…Equation [4] can be rearranged to obtain the inverse function of the Gumbel distribution for equivalent defect diameter as…”

Section: Estimating the Fatigue Life Distribution From The Defecmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Relationship between Defect Size and Fatigue Life Distributions in Al-7 Pct Si-Mg Alloy Castings

Tiryakioğlu

2009

Metall Mater Trans A

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“…Since the results of Green and Campbell [11] were published, the two-parameter Weibull distribution has been used extensively in the casting literature to characterize fracture-related mechanical properties such as tensile strength (S T ), [14] elongation and fatigue life (N f ), [15][16][17] without determining whether r T is indeed zero. Some issues need to be addressed concerning this approach.…”

Section: Introductionmentioning

confidence: 99%

Weibull Analysis of Mechanical Data for Castings: A Guide to the Interpretation of Probability Plots

Tiryakioğlu

Campbell

2010

Metall Mater Trans A

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The Weibull statistics used in the analysis of mechanical data from castings are reviewed. The insight that can be gained from the three-parameter analysis is introduced, and in particular, the meaning of the threshold value in the three-parameter Weibull distribution from a casting process standpoint is discussed. Weibull mixtures, which are necessary when different defect populations are present in castings, are discussed in detail. Data sets from the literature are reinterpreted for demonstration of the guidelines.Step-by-step procedures are outlined for analysis of Weibull mixtures and for fatigue life data sets with run-outs. The results indicate that knowledge of the casting process is necessary for the accurate interpretation of Weibull probability plots. Because the filling systems of most castings currently are designed poorly, a mixture of Weibull distributions can be expected to be the norm rather than the exception. A single Weibull distribution can be expected only in castings whose filling systems were designed so that no new damage to liquid metal takes place during filling.

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Guidelines for 2‐Parameter Weibull Analysis For Castings

Tiryakioğlu

Hudak

2011

Shape Casting

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Fatigue variability in Al–Si cast alloys

Cited by 45 publications

References 16 publications

Relationship between Defect Size and Fatigue Life Distributions in Al-7 Pct Si-Mg Alloy Castings

Relationship between Defect Size and Fatigue Life Distributions in Al-7 Pct Si-Mg Alloy Castings

Weibull Analysis of Mechanical Data for Castings: A Guide to the Interpretation of Probability Plots

Guidelines for 2‐Parameter Weibull Analysis For Castings

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