Engineering structure optimization design method used in uncertain environment

Abstract

The invention provides an engineering structure optimization design method used in an uncertain environment, and relates to the technical field of engineering structure reliability optimization. According to the method, an uncertain engineering structure optimization design problem is defined first, an engineering structure and uncertain information in the use environment are described as random variables, interval variables or combinations of the random variables and the interval variables according to existing samples, corresponding optimization models are established according to different types of uncertain variables, reliability indexes in the optimization models are calculated on the basis of the point collocation random/interval propagation analysis method, and finally different optimization solvers are selected according to actual problems for outer layer optimization. Reliability indexes of an inner layer failure function are obtained through efficient uncertain propagation analysis, and formation of the nested optimization problem is avoided; hybrid uncertainty models including random parameters and interval parameters in the same problem are considered, and the method has a practical engineering significance in interval parameter optimization problem under random process stimulation.

Description

technical field [0001] The invention relates to the technical field of engineering structure reliability optimization, in particular to an engineering structure optimization design method in an uncertain environment. Background technique [0002] Uncertain factors generally exist in the optimal design of engineering structures. Traditional optimization design techniques do not consider the uncertainties in the design, production and operation process. However, due to the uncertainties of material properties, load environment and geometric dimensions, the structural performance often has a certain variability. If these uncertainties are ignored factors, unexpected failures may occur as a result of design for deterministic results. Therefore, the optimization design process must reasonably take into account the influence of system uncertainty. [0003] Traditional deterministic design procedures address uncertainty and reliability issues by using safety factors or worst-case...

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Problems solved by technology

Second, it is necessary to solve the computational efficiency problem of double-level nested optimization

However, the work in this area is only in its infancy and needs further development and improvement.

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