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Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations
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School of Mechanical Engineering and Automation, Northeastern University, China
School of Mechanical, Shenyang Institute of Engineering, China
Submission date: 2023-03-29
Final revision date: 2023-05-28
Acceptance date: 2023-06-25
Online publication date: 2023-07-05
Publication date: 2023-07-05
Corresponding author
Wenxue Qian   

School of Mechanical Engineering and Automation, Northeastern University, 110819, Shenyang, China
Eksploatacja i Niezawodność – Maintenance and Reliability 2023;25(3):168771
  • The stress distribution of the turbine under multiple loads is determined by the flowthermal solid coupling analysis method.
  • The stress distribution with dispersion characteristics is obtained through the coupling analysis process and response surface method.
  • This reliability analysis model considers the failure dependency between the failure sites.
  • The accuracy of this reliability model is verified by Monte Carlo simulation.
The harsh environmental loads may lead to strength failure in the turbine in an aero-engine. To accurately assess the strength reliability of the turbine under multiple loads, the stress distributions of 41 danger sites of a turbine under thermal, centrifugal, and pneumatic loads were determined by the flow-thermal-solid coupling analysis using ANSYS. Second, based on the flow-thermal-solid coupling analysis and response surface method, the probabilistic analysis model of stress at the danger site was established. And the probabilistic distribution of stress was determined by sampling and hypothesis testing. Finally, the reliability model of the turbine with multi-site damage and failure dependency was established, by which a reliability of 0.99802 was calculated. And the actual reliability of the turbine was 0.99626 determined by the Monte Carlo simulations, which verified the model in precision. The results indicated that the reliability model has a high efficiency and higher precision than the traditional reliability model with failure independence.
This work was partially supported by the National Natural Science Foundation of China (Grant No. 52175131), the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. J2019-IV-0016-0084).
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