一种改进的航空发动机结构概率风险评估方法

doi:10.7527/S1000-6893.2015.0199

Abstract

Abstract:

In order to meet the probabilistic requirements of engine life limited parts(ELLP) for FAR33.75, an improved approach of probabilistic risk assessment combined with Kriging and Monte Carlo radius-outside importance sampling(MCROIS) is presented. Concerning the issue of high dimensions and low failure probabilities including implicit and highly nonlinear limit state function, Kriging model is used to approximate the unknown implicit limit state functions and calculate the most probable point(MPP) with iterative algorithm of active learning function; the accuracy of Kriging model is improved when design of experiments(DOE) is updated. Using Kriging model, optimal sampling radius is determined and the joint probability density function of importance sampling is constructed; meanwhile sampling center is moved to the area of optimal sampling radius, then active learning function is constructed to ensure that more random sample points are drawn belonging to the sphere domain which is determined by optimal sampling radius, and the efficiency of failure probability is improved, so the structural risk probabilistic model of ELLP is established and the given approach is to perform engine risk assessment involving the issue of high dimensions and low failure probabilities. Finally, the numerical example of lower pressure compressor disk of aeroengine demonstrates the efficiency, robustness and accuracy of the approach compared with Monte Carlo simulation(MCS) algorithm.

Key words: risk assessment, importance sampling, active learning, failure probability, aeroengine

CLC Number:

V19
TB114.3

LI Yan, ZHANG Shuguang, GONG Qi. An improved probabilistic risk assessment method of structural parts for aeroengine[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016, 37(2): 597-608.

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An improved probabilistic risk assessment method of structural parts for aeroengine

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