The improvement of Bootstrap method and its application in structure parameter uncertainty quantification and propagation

doi:10.16385/j.cnki.issn.1004-4523.2020.04.005

	The improvement of Bootstrap method and its application in structure parameter uncertainty quantification and propagation
	Luo, Yong-Peng 1,3; Liu, Jing-Liang 3; Han, Jian-Ping 2; Lu, Si-Ping 4; Huang, Fang-Lin 4
刊名	Zhendong Gongcheng Xuebao/Journal of Vibration Engineering
	2020-08-01
卷号	33 期号:4 页码:679-687
关键词	Cable stayed bridges Data flow analysis Density functional theory Distribution functions Population statistics Probability density function Distribution characteristics Dynamic characteristics Empirical distribution functions Response surface modeling Sensitivity indices Structure parameter Uncertain parameters Uncertainty parameters
ISSN号	10044523
DOI	10.16385/j.cnki.issn.1004-4523.2020.04.005
英文摘要	The population distributions of the measured data or parameters are usually assumed during uncertainty analysis in structure parameter uncertainty quantification and propagation. In fact, the different probability distributions can bring different uncertain results, which will have impact on judgments of the structure. The overall distribution characteristics can be statistically inferred without the assumption of distribution based on Bootstrap method. However, this method limits the generating range of the self-help sample, which causes the self-help sample being similar to the original sample, and the non-self-help probability distribution disagreeing with the genuine distribution. Therefore, a new method for structure parameter uncertainty quantification and propagation based on improved Bootstrap method and response surface model (RSM) is proposed. Firstly, the information diffuse theory is introduced to estimate the probability density function of the limited measured data, which can be regarded as a surrogate function of the empirical distribution function and used to establish random samples. Secondly, the random samples of uncertain parameters are put into the RSM to calculate the response. A new sensitivity index is defined to judge the influence of the uncertainty parameters on the response. Finally, the dynamic characteristic uncertainty analysis of a cable-stayed bridge is presented to investigate the feasibility and effectiveness of the proposed method. © 2020, Nanjing Univ. of Aeronautics an Astronautics. All right reserved.
语种	中文
出版者	Nanjing University of Aeronautics an Astronautics
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/151106]
专题	教务处（创新创业学院）
作者单位	1.Key Laboratory for Structural Engineering and Disaster Prevention of Fujian Province, Huaqiao University, Xiamen; 361021, China 2.School of Civil Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 3.College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou; 350108, China; 4.School of Civil Engineering, Central South University, Changsha; 410075, China;
推荐引用方式 GB/T 7714	Luo, Yong-Peng,Liu, Jing-Liang,Han, Jian-Ping,et al. The improvement of Bootstrap method and its application in structure parameter uncertainty quantification and propagation[J]. Zhendong Gongcheng Xuebao/Journal of Vibration Engineering,2020,33(4):679-687.
APA	Luo, Yong-Peng,Liu, Jing-Liang,Han, Jian-Ping,Lu, Si-Ping,&Huang, Fang-Lin.(2020).The improvement of Bootstrap method and its application in structure parameter uncertainty quantification and propagation.Zhendong Gongcheng Xuebao/Journal of Vibration Engineering,33(4),679-687.
MLA	Luo, Yong-Peng,et al."The improvement of Bootstrap method and its application in structure parameter uncertainty quantification and propagation".Zhendong Gongcheng Xuebao/Journal of Vibration Engineering 33.4(2020):679-687.