Most components or structures experience in service a variety of cyclic stresses. In the case of cyclic constant amplitude loading the fatigue crack growth depends only on the crack, the component geometry and the applied loading. In the case of variable amplitude loading it also depends on the preceding cyclic loading history. Various types of load sequence (overloads, under-loads, or combination of them) may induce different load-interaction effects which can cause either acceleration or reduction of the fatigue crack growth rate.
The previously developed UniGrow fatigue crack growth model for constant amplitude loading histories which was based on the analysis of the local stress-strain material behaviour at the crack tip has been improved, modified and extended to such a level of sophistication that it can be used for fatigue crack growth analyses of cracked bodies subjected to arbitrary variable amplitude loading spectra. It was shown that the UniGrow model enables to correctly predict the effect of the applied compressive stress and tensile overloads by accounting for the existence of the internal (residual) stresses induced by the reversed cyclic plasticity around the crack tip. This idea together with additional structural memory effect model has been formalized mathematically and coded into computer program convenient for predicting fatigue crack growth under arbitrary variable amplitude loading spectra.
The experimental verification of the proposed model was performed using 7075-T6, 2024-T3, 2324-T7, 7010-T7, 7050-T7 aluminium alloys, Ti-17 titanium alloy, and 350WT steel. The good agreement between theoretical and experimental data proved the ability of the UniGrow model to predict fatigue crack growth and fatigue crack propagation life under a wide variety of real variable amplitude loading spectra.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/4402 |
| Date | January 2009 |
| Creators | Mikheevskiy, Semen |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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