Time series analysis of fatigue crack growth rate data

Abstract Previous treatments of fatigue crack growth rate (FCGR) statistics have sought to determine the best testing and data analysis techniques with which to process fatigue crack growth data. The best techniques were denned as the ones that produced the least scatter in the data. Recent studies suggest that the scatter in FCGR data has physical significance, which must be understood in order to predict the growth of small cracks. This paper presents a stochastic model which treats the material's resistance to fatigue crack growth as a spatial stochastic process evolving along the path of the crack. The parameters of the model are found by a time series analysis which accounts for the statistical correlation that has been observed between adjacent FCGR measurements. The data to be analyzed is assumed to consist of an ensemble of replicate crack growth tests sampled at equal increments of crack growth. The model is shown to be useful for explaining the moderate scatter observed in mid-range ΔK tests. It is also likely to be useful for understanding the large scatter observed in small crack tests.

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