This thesis focuses on the growth of cracks which are small in relation to the material microstructure especially the situation of clusters of small cracks grown from smooth surfaces, termed micro-multi-site cracking, as is frequently the case for components in service. A proper understanding of this regime of crack growth will allow for less conservative maintenance schedules as well as the application of more sensitive health monitoring systems which are currently under development.
To address the problem a significant experimental investigation of micro-multi-site cracking was conducted on 7075-T7351 aluminum alloy. Using the resulting data a micro-structurally based transition crack length is defined to determine the point which separates small and long crack growth. This definition is based upon the observed evolution of scatter in the growth rates of growing small cracks. It is shown that this scatter falls with growth until the transition point is reached where it assumes a constant value for the growth of long cracks.
It is then shown that the total population of cracks within the clusters can be considered as bi-modal. One distribution consists of primary cracks which can grow and ultimately cause specimen failure. The second distribution consists of secondary cracks, the growth of which ultimately arrests. Several methods for experimentally separating the two distributions have been developed. The first method relies upon the defined transition point between small and long crack behavior. A second method based upon the second derivative of the crack length versus cycle count data has also been developed. Since the secondary cracks cannot lead to failure their data must be discarded prior to any analysis. It is then shown that failure to do so will lead to erroneous non-conservative predictions of crack growth.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/14554 |
| Date | 04 April 2007 |
| Creators | Cappelli, Marcus Domenic |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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