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An important energy source in commercial aircrafts is the high pressure, high temperature air that is bled from the engines and routed throughout the airframe to secondary systems. This hot air is transported by the engine bleed system, a set of thin-walled ducts whose reliability and durability are important for flight safety. Among the various materials suited for use in this system, titanium stands out because of its favorable characteristics, such as high strength-to-weight ratio and corrosion resistance. The effects of aging must be taken in account when predicting the useful life of the bleed system parts. In order to understand and describe the damage accumulation process suffered by the titanium ducts, a set of cyclic pressurization tests simulating the service conditions was conducted in a pneumatic workbench. Tensile and fatigue ring-shaped specimens were further cut from these ducts and tested in laboratory air at room temperature in a servo-hydraulic machine.

The aluminum alloy 2524 was developed during the 90's mainly to be employed in aircraft fuselage panels. It is basically an improvement of the standard Al 2024 alloy, and its more rigorous processing control results in a reduced amount of impurities, especially iron and silicon. The pre-straining of aluminum alloys by stretching cold-rolled parts from their extremities is usually performed in order to obtain a more homogeneous precipitates distribution, accompanied by an increase in the yield strength. An improvement of the material's fatigue properties is also expected to occur. However, these effects can vary as the pre-straining direction is changed. The purpose of the present work is to evaluate the resistance of Al 2524 T3 sheet samples to the growth fatigue cracks having the L-T orientation. The influence of the R-ratio on the crack growth behavior is quantified by means of two-parameter modeling.

The study of fatigue crack growth (FCG) in structural materials is aimed at residual life estimations in order to apply the fail-safe design criterion. Because of their excellent strength-to-weight ratio, titanium and its alloys are the most suitable metallic materials for use in the aircraft industry. Recently a new research topic is being developed, in which FCG behavior is predicted by means of statistical tools. In the present work, two of the most promising methods are tested in the description of FCG in unalloyed titanium sheet samples: 1) Artificial Neural Networks (ANNs) and 2) Stochastic Differential Equations (SDEs). These techniques are employed together with a set of 30 experimental curves obtained from constant amplitude FCG tests of center-cracked titanium specimens, conducted in laboratory air under room temperature. Additional numerical data obtained from a predictive damage accumulation model code, were also employed in the work with ANNs.