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Calculation of hybrid reliability of turbine disk based on self-evolutionary game model with few shot learning

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Abstract

A turbine disk design based on uncertainty quantifies the risks and improves the structural reliability. An optimized design issue related to turbine disk fatigue life reliability with subjective and objective multi-source uncertainties is a three-layer nested analysis process, where each iterative step requires a double-layer nested analysis containing probability and improbability. A self-evolution game model is proposed to solve the efficiency problem of the optimized design issue under a specific accuracy requirement. In the initial state, only a few sample points are needed to start the game. In the process of its evolution, the most valuable points are searched automatically, and performance functions are identified only at the points where the game diverges. The maximum failure probability is obtained after game consistency is achieved. Accuracy and efficiency are verified with typical numerical examples. The method is adopted to analyze the hybrid low cycle fatigue reliability of a real turbine disk. It is found that, owing to the elimination of an unnecessary artificial distribution hypothesis, the reliability is lower under the same safety life, and the results are more in line with engineering practice.

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Data availability

The results reported in this study were obtained using our in-house code. The experimental data were obtained from measurements and fatigue experiments on real turbine disks. The data for producing the reported results will be made available upon request.

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Code availability

The results reported in this study were obtained using our in-house code. The basic code of this work is available from the corresponding author upon reasonable request.

Funding

This work is financially supported by National Natural Science Foundation of China (Grant Nos. 51875023 and 51775015) and National Science and Technology Major Project (Grant Nos. 2017-I-0003-0003 and 2017-I-0008-0009).

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Authors and Affiliations

  1. School of Energy and Power Engineering, Beihang University, Beijing, 100191, China

    Gaoxiang Chen, Jiang Fan & Hongbin Xu

  2. Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA

    Bo Li

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  1. Gaoxiang Chen
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  2. Jiang Fan
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  3. Hongbin Xu
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  4. Bo Li
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Correspondence to Jiang Fan.

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Replication of results

The results reported in this study were obtained using our in-house code. The experimental data were obtained from measurements and fatigue experiments on real turbine disks. The basic code and data in this work can be made available from the corresponding author upon reasonable request.

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Chen, G., Fan, J., Xu, H. et al. Calculation of hybrid reliability of turbine disk based on self-evolutionary game model with few shot learning. Struct Multidisc Optim 63, 807–819 (2021). https://doi.org/10.1007/s00158-020-02734-w

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  • DOI: https://doi.org/10.1007/s00158-020-02734-w

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