Affiliation:
1. School of Mechatronic Engineering Southwest Petroleum University Chengdu Sichuan China
2. Oil and Gas Equipment Technology Sharing and Service Platform of Sichuan Province Southwest Petroleum University Chengdu Sichuan China
3. School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu Sichuan China
4. Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu Sichuan China
Abstract
AbstractThe combined high and low cycle fatigue (CCF) loading condition and random uncertainty exert a considerable impact on the design of turbine shafts. To enhance the fatigue life and reliability, this research proposes a CCF reliability analysis and optimization method for turbine shafts. A CCF fatigue reliability analysis framework is established, which focuses on the quantification of CCF loading characteristics and random uncertainty. The consideration of CCF loading characteristics contain the loading frequency ratio of high cycle fatigue (HCF) to low cycle fatigue (LCF), the stress amplitude ratio of HCF to LCF, as well as their interaction. The consideration of random uncertainty contains material, geometry and load, and a surrogate model‐based method is introduced to improve the quantification efficiency. Through the validation by comparing with experimental data and traditional methods, the proposed method is with higher accuracy and efficiency. By integrating the proposed fatigue reliability analysis method with design optimization, optimal design values for the turbine shaft were identified. This method theoretically extends the shaft's CCF life and provides practical engineering guidance for its reliability analysis and design.
Funder
National Science and Technology Major Project
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献