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Fuzzy intelligent multiple response surface method for blade reliability optimization design

An optimized design and multiple response technology, applied in design optimization/simulation, calculation, genetic model, etc., can solve problems such as rarely integrated multiple response surface methods, achieve the effects of shortening calculation time, improving calculation efficiency, and convenient use

Inactive Publication Date: 2017-11-14
HARBIN UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, FLSSVR seldom incorporates Multiple Response Surface Method (MRSM) and applies it to the reliability optimization design of structures with multiple failure modes

Method used

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  • Fuzzy intelligent multiple response surface method for blade reliability optimization design

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Embodiment 1

[0022] A fuzzy intelligent multiple response surface method for blade reliability optimization design, comprising the following steps:

[0023] a. Comprehensively consider the nonlinear material properties of the blade material and the combined effect of mechanical loads, and find the maximum output response point of the blade through static analysis;

[0024] b. Select the input random variable, use the Latin hypercube sampling technique (LHS) to sample the input random variable sample, and solve the finite element basic equation for each sample to obtain the corresponding output response;

[0025] c. Construct the fuzzy intelligent multiple response surface function (FIMRSF) to complete the reliability sensitivity analysis of the blade structure;

[0026] d. Establish fuzzy reliability optimization design model (FRBDO) with high-sensitivity parameters as design variables;

[0027] e. Using FIMRSF instead of the limit state function of the blade structure to carry out fuzzy ...

Embodiment 2

[0029] According to the fuzzy intelligent multiple response surface method of the blade reliability optimization design described in embodiment 1, in the described step a, the density, rotating speed, temperature, aerodynamic pressure, gravity of the blade are used as input variables, considering the temperature load of the blade, mechanical The coupled action of loads solves the basic finite element equations of the blade, and conducts deterministic analysis to find the maximum stress point, maximum deformation point and maximum fatigue crack growth point of the blade.

Embodiment 3

[0031] According to the fuzzy intelligent multiple response surface method of the blade reliability optimization design described in embodiment 1, in the described step b, consider the randomness and fuzziness of the data, use the above-mentioned input variable as the input random variable, and use Latin hypercube sampling The technology extracts input random variable samples, solves the basic equation of finite element for each sample, and obtains the output response of the corresponding stress, deformation, and crack stress intensity factor (KI) in the analysis time domain.

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Abstract

The invention discloses a fuzzy intelligent multiple response surface method for a blade reliability optimization design. The method specifically comprises the processes of comprehensively considering joint action of non-linear material attribute and mechanical load of a blade material and finding out the maximum output response point of the blade by statics analysis; selecting the input random variable, extracting an input random variable sample by applying a Latin hypercube sampling (LHS) technology and solving finite element basic equation for each sample to obtain corresponding output response; constructing a fuzzy intelligent multiple response surface function (FIMRSF) to finish reliability sensitivity analysis of the blade structure; establishing a fuzzy reliability optimization design model (FRBDO) by taking a high sensitivity parameter as a design variable; and performing fuzzy reliability optimization design by replacing the limit state function of the blade structure with FIMRSF and solving the FRBDO model by means of a multi-target genetic algorithm. The method disclosed by the invention is a quick and efficient multi-failure mode structural reliability optimization design method.

Description

technical field [0001] The invention relates to an aeroengine blade reliability optimization design method, in particular to a fuzzy intelligent multiple response surface method for blade reliability optimization design. Background technique [0002] The aeroengine is the heart of the aircraft, and its reliability affects the performance of the aircraft. As an important part of an aero-engine, turbine blades are often subjected to complex dynamic mechanical loads, and experience composite failure modes such as stress, deformation, and fatigue crack growth. Therefore, it is of great significance to optimize the reliability design of the blade. [0003] At present, the structural reliability optimization design method has been widely used. Among them, the Response Surface Method (RSM) has the characteristics of high efficiency, rapidity, and certain accuracy, and has received extensive attention in the field of structural reliability optimization design. The reliability opt...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N3/12
CPCG06F30/15G06F30/23G06N3/126
Inventor 张春宜孙田王爱华井慧哲李成伟
Owner HARBIN UNIV OF SCI & TECH
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