Predicting Fatigue Crack Behavior in Titanium with the use of Statistical Tools 2007-01-2812
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. Some possibilities of these tools in determining the residual life and the crack growth history, without disregarding the statistical nature of these phenomena, are explored in the development of the work.
Citation: Siqueira, A., Baptista, C., and Guimarães, O., "Predicting Fatigue Crack Behavior in Titanium with the use of Statistical Tools," SAE Technical Paper 2007-01-2812, 2007, https://doi.org/10.4271/2007-01-2812. Download Citation
Author(s):
Adriano F. Siqueira, Carlos A. R. P. Baptista, Oswaldo L. C. Guimarães
Affiliated:
EEL/USP - Escola de Engenharia de Lorena da Universidade de São Paulo.
Pages: 9
Event:
SAE Brasil 2007 Congress and Exhibit
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Titanium alloys
Fatigue
Neural networks
Titanium
Statistical analysis
Tools and equipment
Historical reference
Technical review
Aircraft
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