| Teardown Data: Particle Distributions | ||||
| Author | D. Gary Harlow
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| Abstract | Constituent particles within the metal matrix of aluminum alloys play a critical role in the initiation of corrosion and fatigue crack growth in these materials. Thus, statistical characterization of the geometrical features of particles is critical to the modeling for either corrosion or fatigue damage evolution. One of the more important statistics is the particle size distribution. Extensive optical microscopy on common 7075-T6 aluminum alloy has resulted in rather large sets of data for particle geometry. Furthermore, similar data have also been collected from teardown specimens taken from seven different outer wing panels constructed from 7075-T6 aluminum alloy. The primary purpose of this effort is to analyze this extensive set of data by using advanced multimodal statistical modeling methods to appropriately characterize the geometrical properties of constituent particles in these specimens. The dominant mode model is well suited to characterize particle statistics. The underlying distribution functions are assumed to be three parameter Weibull distribution functions for subpopulations.
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| Keywords | 7075 Aluminum alloy, Bimodal distributions, Particle geometry, Particle statistics, Weibull distribution | |||
| Article #: 1874 | ||||
July 26-28, 2012 - Boston, Massachusetts, U.S.A. |