Substructure-based distributed collaborative probabilistic analysis method for low-cycle fatigue damage assessment of turbine blade–disk

Abstract

A numerical simulation-based probabilistic analysis methodology, substructure-based distributed collaborative probabilistic analysis method (SDCPAM), is proposed for accurate and efficient fatigue prognosis based on distributed collaborative response surface method (DCRSM) and substructure analysis method. This paper focuses on the low-cycle fatigue (LCF) damage assessment for turbine blade–disk system. Based on the established probabilistic strain–life models and fatigue reliability model for tandem system, the LCF damage principle of turbine blade–disk system is proposed and integrated with SDCPAM. Following that, the LCF life prediction of the turbine blade–disk is completed, and probabilistic sensitivity analyses of blade and disk to the LCF life of the turbine blade–disk system are achieved. According to the above efforts, the feasibility and effectiveness of SDCPAM is verified. Finally, the LCF damage assessment for the blade–disk system is accomplished, and the influences of applied cycle and reliability level on the LCF damage are investigated. Through the comparisons of the proposed with traditional fatigue reliability model, it is illustrated that the proposed fatigue reliability model is reasonable. The results show that blade and disk almost have the same great influence on the blade–disk LCF life. In addition, applied cycles under normal and lognormal distributions produce the same LCF damage reliability that decreases with increasing applied cycle and reliability level. The efforts of this study indicate the reasonability of the proposed method and models in describing the LCF damage reliability of the blade–disk system, and enrich the reliability theory and method for the complex structure with multi-component and multi-failure mode.