A statistical distribution for crack growth technique is one of the important issues emerging from the fatigue crack propagation process. This study aims to compare three different statistical distributions for providing the best modelling of the fatigue data. The normal, the lognormal and the Weibull distribution are compared for determining a better fit for the variables. Kolmogorov-Smirnov has been chosen as the criterion of the best distribution of the variables. Ten replicate specimens of aluminium alloy A7075-T6 in constant amplitude crack tests were conducted. The number of cycles for the formation of the initial crack and initial crack length were taken as random variables. A Bootstrap approach was applied for ensuring that the chosen distribution was the best representative for this type of variables since small data was incorporated in this analysis, it was not suitable to justify the true population. Thus, the result showed that the lognormal distribution was the best distribution to represent the number of cycles and the length of the initial crack. It was found that whether the normal and lognormal types were suitable for those variables, the lognormal was more conservative for these types of variables. These two variables played the main role in life prediction. Therefore, an analysis of the statistical distribution is highly important. It is believed that these results lead to the significant prediction of fatigue lifetime.
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