Issue |
MATEC Web Conf.
Volume 80, 2016
NUMIFORM 2016: The 12th International Conference on Numerical Methods in Industrial Forming Processes
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|
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Article Number | 10006 | |
Number of page(s) | 5 | |
Section | MS10: Design, Optimization, Inverse Methods and Uncertainties in Forming Processes | |
DOI | https://doi.org/10.1051/matecconf/20168010006 | |
Published online | 24 October 2016 |
Fast variable stiffness composite cylinder uncertainty analysis by using reanalysis assisted Copula function
1 State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, 410082, PR China
2 School of Logistics, Central South University of Forestry and Teleology, Changsha, 41004, P.R. China
3 Joint Centre for Intelligent New Energy Vehicle, Shanghai, China
a Corresponding author: wanghu@hnu.edu.cn
There are lots of uncertainties in variable-stiffness composite materials such as material properties, fibre volume fraction, geometries at various scale and matrix porosity. Commonly, these uncertainties are not always mutually independent and there exist correlations among these random input variables. These correlations may affect the output of composite significantly. To address these correlations, a novel approach for uncertainty analysis based on copula function assisted by reanalysis method is suggested. The Copula function is utilized to address the correlations of random input variables. Monte Carlo simulation (MCS) is employed to obtain the uncertainty analysis. Therefore, a large number of samples should be generated and the expensive computational cost is not feasible when the popular finite element (FE) model is utilized. To save the computational cost and make the uncertainty analysis feasible in practice, an efficient fast computation method, reanalysis method is integrated in the frame. The numerical test demonstrates that the proposed approach is an efficient uncertainty analysis tool for the practical engineering problems.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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