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| Reliability analysis method of frame structures considering spatial variability |
| Received:September 18, 2019 Revised:July 09, 2020 |
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| DOI：10.7511/jslx20190918004 |
| KeyWord:reliability spatial variability random field local average stochastic finite element method |
| Author | Institution |
| 刘敬敏 |
广西科技大学 土木建筑工程学院, 柳州 |
| 杨绿峰 |
广西大学 土木建筑工程学院, 工程防灾与结构安全教育部重点实验室, 广西防灾减灾与工程安全重点实验室, 南宁 |
| 余波 |
广西大学 土木建筑工程学院, 工程防灾与结构安全教育部重点实验室, 广西防灾减灾与工程安全重点实验室, 南宁 |
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| Abstract: |
| Spatial variability is an inherent property of parameters,which has an important influence on the stochastic response and reliability of engineering structures.In this paper,a reliability method for planar frame structures considering spatial variability of parameters was proposed based on the local average theory and the perturbation stochastic finite element method (PSFEM).Meanwhile,the influence rule of spatial variability of parameters on structural reliability was quantitatively analyzed.Considering the spatial variability of random factors,the continuous random field was discretized into a group of random variables by using the local average theory of two-dimensional linear random field discretization,while the double integral expression of local average covariance matrix of the random field was established by theoretical derivation.Then the stochastic structural response and its gradient vector to the basic random variables were analyzed by using the PSFEM,and a reliability method for planar frame structures considering spatial variability of parameters was proposed by calculating the structural reliability index utilizing the gradient optimization method of reliability analysis.Analysis results show that the method proposed in this paper has high accuracy and efficiency.Moreover,the local average theory of random field discretization is insensitive to the correlation function types,and the reliability index of the structure decreases gradually with the increase of the skewness and variability,which shows that the influence of spatial variability of parameters on structural reliability cannot be ignored. |
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