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Stochastic free vibration analyses of composite shallow doubly curved shells – A Kriging model approach |
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| Affiliation: | 1. ISEL, IPL, Av. Conselheiro Emídio Navarro, 1, 1959-007 Lisboa, Portugal;2. LAETA, IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-01 Lisboa, Portugal;1. Centre for Infrastructure Engineering and Safety (CIES), School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW 2052, Australia;2. School of Mathematics and Statistics, The University of New South Wales, Sydney, NSW 2052, Australia;1. Sorbonne universités, Université de Technologie de Compiègne, Laboratoire Roberval UMR CNRS 7337, Centre de Recherche de Royallieu, CS 60319, 60203 Compiègne Cedex, France;2. Université de Lorraine, LEM3 UMR 7239, Ile du Saulcy, F-57045 Metz Cedex 01, France;1. School of Engineering, Indian Institute of Technology Mandi, Himachal Pradesh 175 001, India;2. Department of Aerospace Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721 302, India;1. Mechanical Engineering Department, National Institute of Technology Silchar, India;2. Department of Engineering Science, University of Oxford, Oxford, UK |
| Abstract: | This paper presents the Kriging model approach for stochastic free vibration analysis of composite shallow doubly curved shells. The finite element formulation is carried out considering rotary inertia and transverse shear deformation based on Mindlin’s theory. The stochastic natural frequencies are expressed in terms of Kriging surrogate models. The influence of random variation of different input parameters on the output natural frequencies is addressed. The sampling size and computational cost is reduced by employing the present method compared to direct Monte Carlo simulation. The convergence studies and error analysis are carried out to ensure the accuracy of present approach. The stochastic mode shapes and frequency response function are also depicted for a typical laminate configuration. Statistical analysis is presented to illustrate the results using Kriging model and its performance. |
| Keywords: | A Polymer–matrix composites (PMCs) B Vibration C Finite element analysis (FEA) C Computational modelling Uncertainty quantification |
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