Probabilistic Prediction of Aviation Engine Critical Parts Lifetime

Abstract

Lifetime of disks and other aviation engine parts critical for safe operation is currently probabilistically predicted using mainly two methods. One method to predict lifetime is to confirm lifetime to low-cycle fatigue (LCF) cracking of a part without initial defects. The other method to predict lifetime is to confirm lifetime for safe propagation of a crack from initial defects available in a part. Combination of the above stated methods along with usage of margins on cyclic durability that ensure the required nonfracture probability presents another more conservative approach. Confirmation of lifetime to LCF cracking of a part without initial defects is usually performed based on results of cyclic tests of parts. The safe life determination algorithms were developed in Central Institute of Aviation Motors (CIAM) that take into account a difference in test outcome (“failure”–“no failure”). The developed software makes possible to consider the admissible failure probability, use the actual cyclic durability spread characteristics of the parts involving both lognormal and Weibull durability distributions. This paper discusses the examples of application of the elaborated methods and software. To confirm lifetime for safe propagation of a crack from defects available in a part, a program of statistical determination of durability of powder alloy disks with random fields of ceramic inclusions was developed in CIAM. This program allows performing the partition of disks into typical elements, the generation of realizations of initial defects for each typical disk element and calculation of life realizations corresponding to them, the statistical processing of the obtained data made with usage of asymptotic theory of extreme values, and the determination of technical risk functions for a disk as a whole. While developing the software, the problems of crack initiation and its stable propagation from ceramic inclusions were sequentially decided. Example of the calculation made according to the developed program is given in this paper. The probabilistically-justified approaches to determine the safe life shall be supplemented with the methods of economical and ecological risk analysis. In this case these approaches may become a good support for arranging the engine service to Reliability Centered Maintenance.

Steady and Transient Thermal State of Turbine Disk Estimation for Life Time Monitoring

“…Such systems help to fully use the assigned resource of the engine as well as increase its reliability. Different approaches were developed for this reason, like the ones based on finite element analysis [3], statistical methods [4], and neural networks [5]. However, in order to improve the lifetime prediction accuracy, it is necessary to perform estimation of the lifetime in real time using actual conditions.…”