A reliability analysis method for earthquake resistance of large complex building structure

被引:0
作者
Xiao Y. [1 ]
Zhang X. [1 ]
Xue R. [1 ,2 ]
机构
[1] School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi'an
[2] Norendar International Ltd., Shijiazhuang
来源
Xue, Ronggang (26452850@qq.com) | 1600年 / Northwestern Polytechnical University卷 / 39期
关键词
Earthquake resistance; Kriging; Mega-sub controlled structural system; Surrogate model;
D O I
10.1051/jnwpu/20213910055
中图分类号
学科分类号
摘要
The seismic reliability calculation of complex building structures requires a lot of simulation analysis and therefore the calculation cost is high. Fitting performance function with surrogate model can improve computational efficiency, but how to ensure the calculation accuracy while improving the reliability analysis efficiency of the engineering structure is a problem worthy of study. This paper proposes a Kriging-based reliability analysis method, which establishes the Kriging surrogate model with fewer calculations of the performance function, improves the accuracy of the surrogate model of performance function by infill-sampling, and obtains the approximate failure probability combined with Monte Carlo simulation. Two numerical examples are analyzed; the results show that this method is efficient and accurate. The method is applied to the seismic reliability calculation of mega-sub controlled structural system, in which the randomness of structure and seismic action is considered. The application results show that it is an effective method for reliability analysis of complex building structures. © 2021 Journal of Northwestern Polytechnical University.
引用
收藏
页码:55 / 61
页数:6
相关论文
共 12 条
[1]  
HAN Zhonghua, Kriging surrogate model and its application to design optimization: a review of recent progres, Acta Aeronautica et Astronautica Sinica, 37, 11, pp. 3197-3225, (2016)
[2]  
KAYMAZ I., Application of Kriging method to structural reliability problems, Structural Safety, 27, 2, pp. 133-151, (2005)
[3]  
BICHON B J, ELDRED M S, SWILER L P, Et al., Efficient global reliability analysis for nonlinear implicit performance functions, AIAA Journal, 46, 10, pp. 2459-2468, (2008)
[4]  
BICHON B J, ELDRED M S, MAHADEVAN S, Et al., Efficient global surrogate modeling for reliability-based design optimization, Journal of Mechanical Design, 135, 1, pp. 1-13, (2013)
[5]  
ECHARD B, GAYTON N, LEMAIRE M., AK-MCS: an active learning reliability method combining Kriging and Monte Carlo simulation, Structural Safety, 33, 2, pp. 145-154, (2011)
[6]  
PEIJUAN Z, MING W C, ZHOUHONG Z, Et al., A new active learning method based on the learning function U of the AK-MCS reliability analysis method, Engineering Structures, 148, pp. 185-194, (2017)
[7]  
SUN Z, WANG J, LI R, Et al., LIF: a new Kriging based learning function and its application to structural reliability analysis, Reliability Engineering & System Safety, 157, pp. 152-165, (2017)
[8]  
JIA B, YU X L, YAN Q S., A new sampling strategy for Kriging-based response surface method and its application in structural reliability, Advances in Structural Engineering, 20, 4, pp. 564-581, (2017)
[9]  
ZHOU T, PENG Y., Structural reliability analysis via dimension reduction, adaptive sampling, and Monte Carlo simulation, Structural and Multidisciplinary Optimization, 62, 5, pp. 2629-2651, (2020)
[10]  
ZHANG Xun'an, WANG Dong, JIANG Jiesheng, The controlling mechanism and the controlling effectiveness of passive mega-sub-controlled frame subjected to random wind loads, Journal of sound and vibration, 283, 3, pp. 543-560, (2005)