Stochastic natural frequency analysis of skewed sandwich plates. Issue 7 (15th July 2019)

• Record Type: Journal Article
• Authors: Kumar, R.R.; Karsh, P.K.; , Vaishali; Pandey, K.M.; Dey, S.
• Is Part Of: Engineering computations. Volume 36:Issue 7(2019)
• Page Start: 2179
• Page End: 2199
• Publication Date: 2019-07-15
• Subjects: Monte Carlo simulation -- Sandwich plates -- Stochastic natural frequency -- Radial basis function -- Uncertainty quantification -- Higher-order-zigzag theory; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-01-2019-0034
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: The purpose of this paper is to investigate the first three stochastic natural frequencies of skewed sandwich plates, considering uncertain system parameters. To conduct the sensitivity analysis for checking the criticality of input parameters. Design/methodology/approach: The theoretical formulation is developed based on higher-order-zigzag theory in accordance with the radial basis function (RBF) and stochastic finite element (FE) model. A cubic function is considered for in-plane displacement over thickness while a quadratic function is considered for transverse displacement within the core and remains constant in the facesheet. RBF is used as a surrogate model to achieve computational efficiency and accuracy. In the present study, the individual and combined effect of ply-orientation angle, skew angle, number of lamina, core thickness and material properties are considered for natural frequency analysis of sandwich plates. Findings: Results presented in this paper illustrates that the skewness in the sandwich plate significantly affects the global dynamic behaviour of the structure. RBF surrogate model coupled with stochastic FE approach significantly reduced the computational time (more than 1/18 times) compared to direct Monte Carlo simulation approach. Originality/value: The stochastic results for dynamic stability of sandwich plates show that the inevitable source uncertainties present in the input parameters result in significant variation from the deterministic value demonstrates the need for inclusive design paradigm considering stochastic effects. The present paper comprehensively establishes a generalized new RBF-based FE approach for efficient stochastic analysis, which can be applicable to other complex structures too.