Dynamic Reliability Design of Multicomponent Structure with Improved Weighted Regression Distributed Collaborative Surrogate Model Method

Abstract

For dynamic reliability design of complex structures with multiple components, an improved weighted regression distributed collaborative surrogate model method (IWRDCSMM) is developed from the extremum response surface method (ERSM), decomposed-coordinated thought, and improved weighted regression principle. e ERSM is used to address the dynamic reliability and sensitivity analyses of multicomponent structures and enhance the computing efficiency. e decomposedcoordinated thought is applied to handle the relationship among multiple components. e improved weighted regression method is used to find the efficient samples with smaller errors to improve the modeling accuracy. e proposed method is first introduced for dynamic probabilistic analysis (including reliability analysis and sensitivity analysis) of multicomponent structures. e method is then mathematically modeled by adopting the efficient samples selected based on the improved weighted regression method. Finally, the radial deformation dynamic probabilistic analysis of an aeroengine turbine blisk assembled by blade and disk is accomplished, in respect of the IWRDCSMM, fluid-thermal-structure interaction, and the randomness of input parameters within the time domain [0, T]. e results illustrate that the reliability degree of turbine blisk radial deformation is 0.9951 when the allowable value u allow is 2.30 × 10 −3 m, and all the input parameters affecting the turbine blisk radial deformation are gas temperature, angular speed, inlet velocity, outlet pressure, material density, and inlet pressure, successively. As revealed by the comparison of different methods, the IWRDCSMM has high fitting speed and simulation efficiency with the guarantee of accuracy. e efforts of this study provide a promising dynamic probabilistic analysis technique for complex structures with multiple components and enrich mechanical reliability theory.

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

“…Therefore, the performances of the turbine are not constant, but obey a probability distribution [23]. Due to these uncertainties, the failure of the turbine shows significant dispersion in nature, namely exposing reliability problems [6]. According to research on turbines, probabilistic analysis methods are widely used to investigate the problems such as probabilistic low cycle fatigue life prediction of turbine disks and their reliability assessment [13.…”

Improved Hybrid Response Surface Method Based on Double Weighted Regression and Vector Projection

“…Xiong et al [16] proposed a weighted stochastic response surface method that considered the sample probabilistic weights in regression. Dong et al [17] proposed an improved weighted regression distributed collaborative surrogate model method. Lu et al [18] proposed a weighted regression-based extremum response surface method.…”