Non-probabilistic reliability pneumatic structure coupling optimization design method for hypersonic velocity three-dimensional wing

Abstract

The invention discloses a non-probabilistic reliability pneumatic structure coupling optimization design method for a hypersonic velocity three-dimensional wing. The method comprises the following steps: expressing beam and rib thickness size, elasticity modulus and density into interval variables, and acquiring a sample space of input parameters by utilizing an interval vertex method; finishing finite element parametric modeling of the hypersonic velocity three-dimensional wing according to sample points in the sample space; finishing pneumatic structure coupling analysis of all sample points in the sample space by utilizing an iterative algorithm; screening to obtain internal upper and lower limits of the maximum displacement and maximum stress, and finishing propagation analysis of uncertain parameters in a coupling system; introducing a volume method thought, and defining non-probabilistic reliability indexes of a pneumatic structure coupling system; taking wing structure weight as an optimization object and taking the reliability of the structural maximum displacement and maximum stress smaller than allowable values as a constraint condition, realizing the non-probabilistic reliability optimization design of the wing structure. According to the method disclosed by the invention, the wing structure mass is reduced under the condition that the hypersonic velocity wing is high in reliability, and the wing performance is improved.

Description

technical field [0001] The invention relates to the field of optimal design of hypersonic wing structure, in particular to a non-probabilistic reliability aerodynamic structure coupling optimization design method of hypersonic three-dimensional wing. Background technique [0002] The hypersonic wing is an elastic structure, and the coupling effect generated by the interaction of aerodynamic and elastic forces has a significant impact on the load and performance of the wing. There are two mainstream numerical solutions for aerodynamic structural coupling problems: strong coupling aeroelastic calculation and weak coupling aeroelastic calculation. Among them, the strong coupling aeroelastic calculation writes the control equations of computational structural mechanics and computational fluid dynamics into independent modules, but the two types of equations are solved in an executable program to achieve accurate numerical analysis of aerodynamic structural coupling. However, th...

AI Technical Summary

Problems solved by technology

This method is easy to implement and efficient in calculation, and has great advantages in engineering practice, but there are still the following problems: ① The CFD calculation of the three-dimensional wing is large and the calculation efficiency is low, especially when the nested optimization of the aerodynamic structure coupling is performed. This leads to a great reduction in optimization efficiency; ②The final coupling analysis results are highly sensitive to the accuracy of the data exchange algorithm between the aerodynamic model and the structural model in the interface program, and poor data exchange accuracy may lead to serious distortion of the results

However, there are some defects in these two reliability models in engineering applications: both models need to obtain a large amount of experimental data through experiments to determine the probability distribution and membership function of the model; For the fuzzy reliability model, it is very sensitive to the parameters, and a small error in the selection of the distribution function may lead to a large deviation in the reliability analysis; for the fuzzy reliability model, the subjectivity is strong and the theory is not perfect, resulting in unreliable calculation results, which limits the reliability to a certain extent. its application in practical engineering

Because there are many kinds of uncertain information such as random, fuzzy, unknown but bounded in engineering structural systems, and the experimental data of structural samples is often relatively scarce, so the above two models often cannot describe the uncertainty well from the perspective of probability. and measure the reliability of the system

Images