A method for predicting the fatigue life of pre-corroded 2024-T3 aluminum from breaking load tests
Characterization of material properties is necessary for design purposes and has been a topic of research for many years. Over the last several decades, much progress has been made in identifying metrics to describe fracture mechanics properties and developing procedures to measure the appropriate values. However, in the context of design, there has not been as much success in quantifying the susceptibility of a material to corrosion damage and its subsequent impact on material behavior in the framework of fracture mechanics. A natural next step in understanding the effects of corrosion damage was to develop a link between standard material test procedures and fatigue life in the presence of corrosion. Simply stated, the goal of this investigation was to formulate a cheaper and quicker method for assessing the consequences of corrosion on remaining fatigue life. ^ For this study, breaking load specimens and fatigue specimens of a single nominal gage (0.063″) of aluminum alloy 2024-T3 were exposed to three levels of corrosion. The breaking load specimens were taken from three different material lots, and the fatigue tests were carried out at three stress levels. All failed specimens, both breaking load and fatigue specimens, were examined to characterize the damage state(s) and failure mechanism(s). Correlations between breaking load results and fatigue life results in the presence of corrosion damage were developed using a fracture mechanics foundation and the observed mechanisms of failure. Where breaking load tests showed a decrease in strength due to increased corrosion exposure, the corresponding set of fatigue tests showed a decrease in life. And where breaking load tests from different specimen orientations exhibited similar levels of strength, the corresponding set of fatigue specimens showed similar lives. The spread from shortest to longest fatigue lives among the different corrosion conditions decreased at the higher stress levels. Life predictions based on breaking load data were generally shorter than the experimental lives by an average of 20%. The life prediction methodology developed from this investigation is a very valuable tool for the purpose of assessing material substitution for aircraft designers, alloy differentiation for manufacturers, or inspection intervals and aircraft retirement schedules for aircraft in service. ^
Major Professor: Ben M. Hillberry, Purdue University.
Engineering, Aerospace|Engineering, Mechanical|Engineering, Materials Science
Off-Campus Purdue Users:
To access this dissertation, please log in to our