Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (1): 46-52.doi: 10.13229/j.cnki.jdxbgxb20200502

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Interval analysis of structural fatigue life under random load

Guang-wei MENG1(),Chuan-xin REN2,Feng LI1(),Tong-hui WEI1   

  1. 1.School of Mechanical and Aerospace Engineering，Jilin University，Changchun 130022，China
    2.Institute of Optics and Electronics，Chinese Academy of Science，Chengdu 610041，China
  • Received:2020-06-07 Online:2022-01-01 Published:2022-01-14
  • Contact: Feng LI E-mail:mgw@jlu.edu.cn;fengli@jlu.edu.cn

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Abstract:

Traditional probabilistic methods require large number of samples to determine the probability density distribution of the dependent variable when analyzing the fatigue life of structures， and a small error in the probability density function will cause a large error in the fatigue life of the structure. To solve this problem， an interval analysis model for structural fatigue life under random loads were proposed. The uncertain factors that affect the fatigue life of the structure were regarded as interval variables. The dimensionality reduction expression of the fatigue life of the structure under random load was given. Combined with the interval mathematical method， the upper and lower limits of the fatigue life of the structure were obtained. Numerical examples show that compared with the Taylor method， the structural fatigue life interval analysis method based on dimensionality reduction algorithm proposed in this paper has higher accuracy. For the strength limit and fatigue parameters， the first-order dimensionality reduction algorithm has almost the same accuracy compared with the second-order Taylor method. For fatigue loads， when the variation range is large， the Taylor method cannot meet the accuracy requirements， but the second-order dimensionality reduction algorithm is still steady. It has high calculation accuracy and stability. Its calculation accuracy is roughly equivalent to genetic algorithm within a certain range， but the calculation efficiency is much higher than that of the genetic algorithm.

Key words: engineering mechanics, fatigue life, random load, interval analysis, dimensionality reduction algorithm, Taylor expansion

CLC Number: 

  • TP202.1

Fig.1

Structure diagram"

Fig.2

Load spectrum"

Fig.3

Comparison of fatigue life interval with βSb"

Fig.4

Comparison of fatigue life interval with βC"

Fig.5

Comparison of fatigue life interval with βq"

Fig.6

Comparison of error of upper limit of fatigue life varying with βSb"

Fig.7

Comparison of error of upper limit of fatigue life varying with βC"

Fig.8

Comparison of error of upper limit of fatigue life varying with βq"

Table 1

Comparison of calculation accuracy of fatigue life median"

βqMCS二阶降维算法遗传算法
中值/105中值/105误差/%中值/105误差/%
0.0252.0062.0050.02.0030.1
0.0502.1642.1620.12.1610.1
0.0752.4232.4190.22.4130.4
0.1002.8012.7900.42.7900.4
0.1253.3253.3020.73.2980.8
0.1504.0333.9921.04.0010.8
0.1754.9804.9091.44.9420.8
0.2006.2406.1261.86.1920.8
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