Novel kriging-based decomposed-coordinated approach for estimating the clearance reliability of assembled structures

Turbine blisks are assembled using blades, disks and casings. They can endure complex loads at a high temperature, high pressure and high speed. The safe operation of assembled structures depends on the reliability of each component. Monte Carlo (MC) simulation is commonly used to analyze structural reliability, but this method needs to run thousands of computations. In order to assess the clearance reliability of assembled structures in an efficient and precise manner, the novel Kriging-based decomposed-coordinated (DC) (DCNK) approach is proposed by integrating the DC strategy, the Kriging model and the importance sampling-based Markov chain (MCIS) technique. In this method, the DC strategy is used to decompose a multi-objective problem into many single-objective problems. The relationships between these many single-objectives and the overall objective are then coordinated. The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems, while the MCIS method is used to assess the structural assembled clearance reliability. Moreover, a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective. Then, the reliability of an aeroengine high-pressure turbine (HPT) blade-tip radial running clearance (BTRRC) is analyzed to validate the DCNK approach by considering thermo-structural interaction. The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650 × 10⁻³ m. Compared with different methodologies (including direct simulation, the classical Kriging model, and the weighted response surface method (WRSM)), the proposed method holds obvious advantages in computing time and precision, as well as simulation efficiency and precision. The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory.