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An efficient D-vine copula-based coupling uncertainty analysis for variable-stiffness composites

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成果类型:
期刊论文
作者:
Li, Qidi;Cai, Yong*;Wang, Hu;Lv, Zhiwei;Li, Enying
通讯作者:
Cai, Yong
作者机构:
[Wang, Hu; Cai, Yong; Li, Qidi; Lv, Zhiwei] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha, Hunan, Peoples R China.
[Wang, Hu; Cai, Yong] Joint Ctr Intelligent New Energy Vehicle, Changsha, Hunan, Peoples R China.
[Li, Enying] Cent South Univ Forestry & Technol, Coll Mech & Elect Engn, Changsha, Hunan, Peoples R China.
通讯机构:
[Cai, Yong] H
Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha, Hunan, Peoples R China.
语种:
英文
关键词:
Coupling uncertainty analysis;D-vine copula;Reanalysis;Surrogate modeling techniques;Variable-stiffness composite
期刊:
Composite Structures
ISSN:
0263-8223
年:
2019
卷:
219
页码:
221-241
基金类别:
This work has been supported by Project of the Key Program of National Natural Science Foundation of China under the Grant Nos. 11572120 and 51621004 , National Key Research and Development Program of China 2017YFB0203701 , Key Projects of the Research Foundation of Education Bureau of Hunan Province ( 17A224 ).
机构署名:
本校为其他机构
院系归属:
机电工程学院
摘要:
This study suggests a coupling uncertainty analysis for investigating the uncertainty of stiffness characteristics for variable-stiffness (VS) composites. The uncertainty analysis is based on the Monte Carlo Simulation (MCS) and a novel one-step Bayesian copula model selection assisted D-vine sampling method (OBCS-D) is proposed to realize the coupling of random variables. Compared with other uncertainty analysis methods, the suggested method is capable of identifying suitable copula function and marginal cumulative distribution function (CDF) ...

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