A D-vine copula-based coupling uncertainty analysis for stiffness predication of variable-stiffness composite

• DOI: 10.48550/arxiv.1804.06203
• Publication Date: 2018-01-01
• Authors: Qidi Li; Hu Wang; Yang Zeng; Zhiwei Lv
• Keywords: Vine copula; Vine

This study suggests a coupling uncertainty analysis method to investigate the stiffness characteristics of variable (VS) composite. The D-vine copula function is used address random variables. To identify relation between variables, novel one-step Bayesian model selection (OBCS) proposed obtain suitable as well marginal CDF entire process Monte Carlo simulation (MCS). However, due expensive computational cost complete finite element (FEA) in MCS, fast solver, reanalysis introduced. further improve efficiency procedure, back propagation neural network (BPNN) also introduced based on method. Compared with method, BPNN shows higher sufficient accuracy. Finally, fiber angle deviation VS composite investigated by suggested strategy. Two numerical examples are presented verify feasibility this