Topic
Paris' law
About: Paris' law is a research topic. Over the lifetime, 13815 publications have been published within this topic receiving 224818 citations. The topic is also known as: Paris-Erdogan law.
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TL;DR: In this paper, a power law relationship between da/dN and the cyclic variation in the energy release rate ΔGI was found for both pure mode I and mixed mode II.
Abstract: Delamination fatigue crack growth experiments were carried out on unidirectional T300/914 C Graphite/Epoxy laminates. Both mode I and mixed mode (mode I and mode II in combination) situations were investigated for the stress ratios R = 0.1, 0.3 and 0.5. Double Cantilever Beam (DCB) specimens were used for the pure mode I tests and Cracked Lap Shear (CLS) specimens were used for the mixed mode tests. The initial delaminations were produced by inserting 0.03 mm thick PTFE films during laminate layup. The cyclic loading of the specimens was carried out at a frequency of 5 Hz and with a constant stress ratio maintained throughout the test. It was found that the mode I cyclic crack growth rate yielded a power law relationship between da/dN and the cyclic variation in the energy release rate ΔGI. This relation was virtually independent of the stress ratio, at least for 0.1 < R < 0.5. The mixed mode results showed a similar power law relation between da/dN and Δ(G I + GII). Here a small stress ratio dependence w...
84 citations
TL;DR: In this paper, the crack growth retardation and the location of fatigue crack initiation from stop-hole edge under different mode-mixities are examined by means of a developed fatigue code.
84 citations
TL;DR: In this article, a non-linear dynamical model of fatigue crack growth in ductile alloys under variable-amplitude loading including single-cycle overloads, irregular sequences, and random loads is presented.
84 citations
TL;DR: In this paper, the authors used finite element analysis to predict fatigue crack growth in a reference railway axle within the shaft and in the fillet zone near a press fit, and compared the results with the test results for standard M(T) specimens, as well as to respective analytical predictions.
83 citations
TL;DR: In this article, the fatigue crack growth rate of nickel base superalloys has been modelled using a neural network model within a Bayesian framework and a committee' model was also introduced to increase the accuracy of the predictions.
Abstract: The fatigue crack growth rate of nickel base superalloys has been modelled using a neural network model within a Bayesian framework. A committee' model was also introduced to increase the accuracy of the predictions. The rate was modelled as a function of some 51 variables, including stress intensity range ΔK, log ΔK, chemical composition, temperature, grain size, heat treatment, frequency, load waveform, atmosphere, R-ratio, the distinction between short crack growth and long crack growth, sample thickness and yield strength. The Bayesian method puts error bars on the predicted value of the rate and allows the significance of each individual factor to be estimated. In addition, it was possible to estimate the isolated effect of particular variables such as the grain size, which cannot in practice be varied independently. This demonstrates the ability of the method to investigate new phenomena in cases where the information cannot be accessed experimentally.
83 citations