Reliability analysis for aeroengine turbine disc fatigue life with multiple random variables based on distributed collaborative response surface method

• Published in: Journal of Central South University Vol. 22; no. 12; pp. 4693 - 4701
• Main Authors: Gao, Hai-feng, Bai, Guang-chen, Gao, Yang, Bao, Tian-wei
• Format: Journal Article
• Language: English
• Published: Changsha Central South University 01.12.2015
• Subjects: Engineering; Metallic Materials; distributed collaborative response surface method; complicated mechanical structure; reliability analysis; multi-component and multi-failure mode; multiple random variables
• ISSN: 2095-2899; 2227-5223
• DOI: 10.1007/s11771-015-3020-x

The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables, such as applied load, working temperature, geometrical dimensions and material properties. In order to ameliorate reliability analysis efficiency without loss of reliability, the distributed collaborative response surface method (DCRSM) was proposed, and its basic theories were established in this work. Considering the failure dependency among the failure modes, the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables. Then, the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion. Finally, the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method. Through the comparison of DCRSM, Monte Carlo method (MCM) and the traditional response surface method (RSM), the results show that the computational precision for DCRSM is more consistent with MCM than RSM, while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions. Thus, DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables, and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.