Efficient probabilistic risk assessment for aeroengine turbine disks using probability density evolution

For the risk assessment of turbine rotor disks, the probability of failure for a certain type of disk (after N flight cycles) is a vital criterion for estimating whether the disk is safe enough to put into use. However, the computing process can be expensive. To increase the efficiency of the risk assessment, this study proposes a numerical integration method based on probability density evolution. That is, by establishing the relationship between the initial probability distribution (N = 0) and the actual distribution after N flight cycles, the probability of failure can be determined directly through an initial anomaly distribution using a numerical integration method. To validate the effectiveness and practicality of this method, this paper implements a simple test case to compare the classical Monte Carlo simulation method with the method based on probability density evolution. The results indicate that the method based on probability density evolution shows higher accuracy and speed. In addition, the nondestructive inspection schedule, other related random variables and interfaces with other methods (e.g., important sampling) can also be integrated based on the method proposed in this paper.