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During the fatigue process of unnotched smooth materials, small surface cracks often initiate, grow, and coalesce; these cracks are randomly distributed over the material surfaces in terms of size and location. This paper investigates the probabilistic laws these cracks follow, and proposes a quantitative method for the fatigue damage evaluation and residual-fatigue-life prediction of the materials. This method can be carried out in two ways. One is based on the variation of the statistical parameters (for example, the mean etc.) of the crack surface-length distribution with the number of load cycles. The other is based on the growth rate of the distributed small cracks and on the crack length distribution function.
The procedures of the method are described by taking the example of corrosion fatigue of a weldable structural steel, HT 60. The first step is the preparation of specimens having small cracks randomly distributed over their surfaces; the second step is the sampling of statistical data on the cracks from these specimens and from real structures; and, finally, the third step is fatigue damage evaluation and residual-life prediction based on various statistical treatments of the data obtained.
For the test of the goodness of the model and data in the present study, a Monte Carlo simulation analysis was made, which can deal with the initiation, growth, and coalescence behavior of distributed cracks.
Finally, the characteristic features and the scope of application of the method are described, and some comments are made on its applications to other fatigue fracture processes.
fatigue, quantitative measurement, fatigue damage evaluation, life prediction, inspection, small cracks, surface cracks, crack growth, statistical analysis, Monte Carlo simulation, fracture mechanics, corrosion fatigue
Professor, Institute of Industrial Science, University of Tokyo, Tokyo,
Researcher, National Research Institute for Metals, Tokyo,
Research Engineer, Topy Industries Ltd., Tokyo,