Numerical prediction of fretting fatigue crack trajectory in a railway axle using XFEM

2017 ◽  
Vol 100 ◽  
pp. 32-49 ◽  
Author(s):  
Juan Carlos Martínez ◽  
Libardo Vicente Vanegas Useche ◽  
Magd Abdel Wahab
Author(s):  
Michael P. Enright ◽  
Kwai S. Chan ◽  
Jonathan P. Moody ◽  
Patrick J. Golden ◽  
Ramesh Chandra ◽  
...  

Fretting fatigue is a random process that continues to be a major source of damage associated with the failure of aircraft gas turbine engine components. Fretting fatigue is dominated by the fatigue crack growth phase and is strongly dependent on the magnitude of the stress values in the contact region. These stress values often have the most influence on small cracks where traditional long-crack fracture mechanics may not apply. A number of random variables can be used to model the uncertainty associated with the fatigue crack growth process. However, these variables can often be reduced to a few primary random variables related to the size and location of the initial crack, variability associated with applied stress and crack growth life models, and uncertainty in the quality and frequency of non-deterministic inspections. In this paper, an approach is presented for estimating the risk reduction associated with non-destructive inspection of aircraft engine components subjected to fretting fatigue. Contact stress values in the blade attachment region are estimated using a fine mesh finite element model coupled with a singular integral equation solver and combined with bulk stress values to obtain the total stress gradient at the edge of contact. This stress gradient is applied to the crack growth life prediction of a mode I fretting fatigue crack. A probabilistic model of the fretting process is formulated and calibrated using failure data from an existing engine fleet. The resulting calibrated model is used to quantify the influence of inspection on the probability of fracture of an actual military engine disk under real life loading conditions. The results can be applied to quantitative risk predictions of gas turbine engine components subjected to fretting fatigue.


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