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Abstract: Free vibration response of laminated composite shells with delamination is presented using the finite element method based on first order shear deformation theory. The shell theory used is the extension of dynamic, shear deformable theory according to the Sanders'' first approximation for doubly curved shells, which can be reduced to Love''s and Donnell''s theories by means of tracers. An eight-noded C 0 continuity, isoparametric quadrilateral element with five degrees of freedom per node is used in the formulation. For modeling the delamination, multipoint constraint algorithm is incorporated in the finite element code. The natural frequencies of the delaminated cylindrical (CYL), spherical (SPH) and hyperbolic paraboloid (HYP) shells are determined by using the above mentioned shell theories, namely Sanders'', Love''s, and Donnell''s. The validity of the present approach is established by comparing the authors'' results with those available in the literature. Additional studies on free vibration response of CYL, SPH and HYP shells are conducted to assess the effects of delamination size and number of layers considering all three shell theories. It is shown that shell theories according to Sanders and Love always predict practically identical frequencies. Donnell''s theory gives reliable results only for shallow shells. Moreover, the natural frequency is found to be very sensitive to delamination size and number of layers in the shell. [Copyright &y& Elsevier]

The present computational study investigates on stochastic natural frequency analyses of laminated composite curved panels with cutout based on support vector regression (SVR) model. The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to achieve computational efficiency. The convergence of the present algorithm for laminated composite curved panels with cutout is validated with original finite element (FE) analysis along with traditional Monte Carlo simulation (MCS). The variations of input parameters (both individual and combined cases) are studied to portray their relative effect on the output quantity of interest. The performance of the SVR based uncertainty quantification is found to be satisfactory in the domain of input variables in dealing low and high dimensional spaces. The layer-wise variability of geometric and material properties are included considering the effect of twist angle, cutout sizes and geometries (such as cylindrical, spherical, hyperbolic paraboloid and plate). The sensitivities of input parameters in terms of coefficient of variation are enumerated to project the relative importance of different random inputs on natural frequencies. Subsequently, the noise induced effects on SVR based computational algorithm are presented to map the inevitable variability in practical field of applications. [ABSTRACT FROM AUTHOR]