Analysis of CFRP laminated plates with spatially varying non-Gaussian inhomogeneities using SFEM

Experimental characterisation of random field models for CFRP composite panels

“…For failure probability analysis of the composite plate with spatial material inhomogeneities, the OLE based SFEM formalism developed in [21,20] was considered. Though each of the material property random fields can be assumed to have different correlation models, for the sake of brevity and for the simplicity in exposition, the auto-correlation models for the various properties were assumed to be identical and of the form of Model III with the following constants: C 1 ¼ 0:46, C 2 =lx ¼ 0:66, C 3 =ly ¼ 0:65, C 4 ¼ 0:54, C 5 =lx ¼ 0:05442, C 6 =ly ¼ 0:27.…”

“…Random field discretisation forms the basis for the subject of stochastic finite element method (SFEM) [15][16][17]. Recent studies in composite literature have focussed on the use of random field discretisation schemes that enable the treatment of spatially varying uncertainties for response and reliability analysis [1,[18][19][20][21]. It has been shown that random variable models lead to underestimation of the failure probabilities and hence lead to less conservative designs, thus, highlighting the importance of random field modelling for the uncertainties.…”

Probabilistic mesh-independent discrete damage analyses of laminate composites

“…(6) Our strategy to generate ensemble data of cross-correlated random fields is to combine the spectral decomposition of the cross-covariance matrix defined in Eq. […”

“…Previous researches have focused on probabilistic models of strength and stiffness properties of PMC materials referring experimental test data in order to statistically characterize FRP composites [2], use them in probabilistic design [3], develop stochastic finite element basis [4][5][6], predict statistical failure [6,7], conduct strength analyses in various stochastic analysis studies [8][9][10], evaluate reliability [11], etc. Sriramula, et al provided comprehensive reviews on quantification of uncertainties in PMC materials [12].…”

A data driven polynomial chaos based approach for stochastic analysis of CFRP laminated composite plates

“…It has been shown that the discretisation error is zero at the nodal points for any random field of any distributions, implying that the method adequately captures the first order non-Gaussian characteristics of the field. Studies by the present authors have extended this technique for uncertainty quantification in beams and plates [18,19]. The choice in selecting the number of nodal points in OLE, and in turn, the stochastic dimension, is based on minimising the global mean square error.…”