Engineering Failure Analysis 

Abstract: The macroscopic and microscopic characteristics as well as the proposed mechanisms of Type I (high-temperature) and Type II (low-temperature) hot corrosion are reviewed. Two case histories of gas turbine blade failures are presented. Different practical approaches to minimize hot corrosion are described.

Abstract: Modern aviation gas turbine engines are considered to be highly reliable in that failures in service are rare. In fact this is a misconception, and freedom from service failures is largely the result of stringent standards imposed during frequent inspections. Most failures are thus detected at the incipient stage and appropriate action taken to prevent service failure. The common failure mechanisms found in gas turbine blades are discussed and illustrated.

Abstract: Low cycle fatigue, high cycle fatigue, fatigue crack propagation and thermo-mechanical fatigue in Ni-base superalloys are reviewed in terms of fundamental deformation mechanisms, environmental effects, and interactions between environment and deformation mode. These factors are related to the chemical composition and underlying microstructure for all currently-used product forms (i.e. powder metallurgy, wrought, conventionally cast and single crystal). The basic principles that are developed are used to show how both intrinsic and extrinsic variables can be manipulated to control fatigue behaviour and as a guide for formulation of engineering life prediction models.

Abstract: Gear tooth crack will cause changes in vibration characteristics of gear system, based on which, operating condition of the gear system is always monitored to prevent a presence of serious damage. However, it is also a unsolved puzzle to establish the relationship between tooth crack propagation and vibration features during gear operating process. In this study, an analytical model is proposed to investigate the effect of gear tooth crack on the gear mesh stiffness. Both the tooth crack propagations along tooth width and crack depth are incorporated in this model to simulate gear tooth root crack, especially when it is at very early stage. With this analytical formulation, the mesh stiffness of a spur gear pair with different crack length and depth can be obtained. Afterwards, the effects of gear tooth root crack size on the gear dynamics are simulated and the corresponding changes in statistical indicators – RMS and kurtosis are investigated. The results show that both RMS and kurtosis increase with the growth of tooth crack size for propagation whatever along tooth width and crack length. Frequency spectrum analysis is also carried out to examine the effects of tooth crack. The results show that sidebands caused by the tooth crack are more sensitive than the mesh frequency and its harmonics. The developed analytical model can predict the change of gear mesh stiffness with presence of a gear tooth crack and the corresponding dynamic responses could supply some guidance to the gear condition monitoring and fault diagnosis, especially for the gear tooth crack at early stage.

Abstract: Traditionally, failure mode and effects analysis (FMEA) only considers the impact of single failure on the system. For large and complex systems, since multiple failures of components exist, assessing multiple failure modes with all possible combinations is impractical. Pickard et al. [1] introduced a useful method to simultaneously analyze multiple failures for complex systems. However, they did not indicate which failures need to be considered and how to combine them appropriately. This paper extends Pickard’s work by proposing a minimum cut set based method for assessing the impact of multiple failure modes. In addition, traditional FMEA is made by addressing problems in an order from the biggest risk priority number (RPN) to the smallest ones. However, one disadvantage of this approach is that it ignores the fact that three factors (Severity (S), Occurrence (O), Detection (D)) (S, O, D) have the different weights in system rather than equality. For examples, reasonable weights for factors S, O are higher than the weight of D for some non-repairable systems. In this paper, we extended the definition of RPN by multiplying it with a weight parameter, which characterize the importance of the failure causes within the system. Finally, the effectiveness of the method is demonstrated with numerical examples.