The need for application of probabilistic methods to fatigue life prediction of gas turbine engine components is being increasingly recognized by the U.S. Military. A physics-based probabilistic approach to risk assessment provides improved accuracy compared to a statistical assessment of failure data because it can be used to (1) predict future risk and (2) assess the influences of both deterministic and random variables that are not included in the failure data. Probabilistic risk and fatigue life prediction of gas turbine engine fracture critical components requires estimates of the applied stress and temperature values throughout the life of the component. These values are highly dependent upon the mission type and may vary from flight to flight within the same mission. Currently, standard missions are specified and used during the engine design process, but the associated stresses can differ significantly from stress values that are based on flight data recorder (FDR) information. For this reason, efforts are made to periodically update the standard missions and to assess the impact on component structural integrity and associated risk of fracture. In this paper, the influence of mission type and variability on fracture risk is illustrated for an actual gas turbine engine disk subjected to a number of different mission loadings. Disk stresses associated with each mission were obtained by scaling finite element model results based on RPM values obtained from engine flight recorder data. The variability in stress values throughout the life of the component was modeled using two different approaches to identify the upper and lower bound value influences on the risk of fracture. The remaining variables were based on default values provided in FAA Advisory Circular (AC) 33.14-1 “Damage Tolerance for High Energy Turbine Engine Rotors”. The risk of fracture was computed using a probabilistic damage tolerance computer code called DARWIN® (Design Assessment of Reliability With Inspection) and compared for each mission type to illustrate the maximum influence of mission type on fracture risk. The results can be used to gain insight regarding the influence of mission type and associated variability on the risk of fracture of realistic engine components.

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