Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62002
Title: Advanced multiple response surface method of sensitivity analysis for turbine blisk reliability with multi-physics coupling
Authors: Zhang, C
Song, L
Fei, C
Lu, C
Xie, Y
Keywords: Advanced multiple response surface method
Artificial neural network
Intelligent algorithm
Multi-failure mode
Reliability analysis
Turbine blisk
Issue Date: 2016
Publisher: Elsevier
Source: Chinese journal of aeronautics, 2016, v. 29, no. 4, p. 962-971 How to cite?
Journal: Chinese journal of aeronautics 
Abstract: To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method (AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability. The mathematical model of AMRSM was established and the basic principle of multi-failure mode sensitivity analysis for reliability with AMRSM was given. The important parameters of turbine blisk failures are obtained by the multi-failure mode sensitivity analysis of turbine blisk. Through the reliability sensitivity analyses of multiple failure modes (deformation, stress and strain) with the proposed method considering fluid–thermal–solid interaction, it is shown that the comprehensive reliability of turbine blisk is 0.9931 when the allowable deformation, stress and strain are 3.7 × 10−3 m, 1.0023 × 109 Pa and 1.05 × 10−2 m/m, respectively; the main impact factors of turbine blisk failure are gas velocity, gas temperature and rotational speed. As demonstrated in the comparison of methods (Monte Carlo (MC) method, traditional response surface method (RSM), multiple response surface method (MRSM) and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy. The efforts of this study provide the AMRSM with high precision and efficiency for multi-failure mode reliability analysis, and offer a useful insight for the reliability optimization design of multi-failure mode structure.
URI: http://hdl.handle.net/10397/62002
ISSN: 1000-9361
DOI: 10.1016/j.cja.2016.06.017
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