Reliability Evaluation Of Payload Fairing Separation Based On Dimension Reduction

Payload fairing is an important part of the structure of the launch vehicle,which can protect the payload from being damaged by the external environment.When the rocket flies to a certain altitude,the fairing needs to be separated from the rocket body to ensure the orderly progress of the follow-up mission,and the reliability of its separation is a crucial link in the launch mission.Because the structure has a lot of uncertainties in the design,manufacture and environment,the separation of fairing is affected by the uncertainties from multi-sources.In this thesis,the performance of payload fairing separation under multi-source uncertainty is studied,and a set of analytical framework is proposed to solve the difficulties in the separation such as time-consuming simulation analysis,high dimensional variables and strong nonlinear responses,which has important theoretical and engineering application value.The main research contents of this thesis are as follows:1)In view of the contradiction between the calculation efficiency and the calculation precision in the reliability analysis of practical engineering,a MPP-based simplified bivariate dimension reduction method is proposed to calculate the structural reliability.The traditional reliability analysis mainly includes the simulation method and the approximate reliability method.The simulation method represented by the Monte Carlo method has high accuracy but huge calculation cost,while the approximate reliability method represented by the first order second moment expands the structural failure surface approximately,which improves the calculation efficiency but has poor accuracy.The MPP-based simplified bivariate dimensionality reduction method proposed in this thesis expands the structural failure surface at the MPP with the bivariate dimensionality reduction,which retains a lot of higher-order information,thus greatly improving the accuracy of the analysis method and improving the performance of the analysis method under high-dimensional strong nonlinear functional functions.2)Aiming at the difficulties faced by the reliability analysis of fairing separation,such as multiple failure modes,high dimension and strong nonlinearity,a framework of reliability analysis process was proposed.The effective failure modes were screened through the failure mode analysis to reduce the complexity of the model.By efficient and accurate global sensitivity analysis,uncertain variables had a greater influence on the response is screened out and reduces the complexity of the uncertainty model,building dynamic surrogate model,combining MPP-based SBDRM,the reliability of the fairing separation is calculated efficiently and accurately.3)With the help of finite element software ABAQUS,the detailed model of the fairing is established,and the reliability analysis process proposed in this thesis is used for calculation.First determine the manufacture,assembly,power,environmental four sources of 17 uncertainty variables and failure modes of excessive elastic deformation and irregular angular velocity.Through the analysis of the failure mode,the irregular angular velocity is screened out as active failure mode.By the global sensitivity analysis,17 dimensions uncertainty model down to 6 dimensions.The failure probability of fairing separation was calculated by using the reduced dimensional model to construct a dynamic surrogate model and MPP-based SBDRM.4)The modeling of uncertain variables is discussed and the uncertainty of distribution types under small sample data is explored by using Bayesian hypothesis test method.Four groups of variables with different distribution types were set up for reliability analysis.The results show that the distribution types of variables have little influence on the results of global sensitivity analysis,but have significant influence on the calculation of failure probability.