Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties

Naskar, S., Mukhopadhyay, T., Sriramula, S. and Adhikari, S. (2017) Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties. Composite Structures, 160, pp. 312-334. (doi: 10.1016/j.compstruct.2016.10.035)

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Abstract

This paper presents a stochastic approach to study the natural frequencies of thin-walled laminated composite beams with spatially varying matrix cracking damage in a multi-scale framework. A novel concept of stochastic representative volume element (SRVE) is introduced for this purpose. An efficient radial basis function (RBF) based uncertainty quantification algorithm is developed to quantify the probabilistic variability in free vibration responses of the structure due to spatially random stochasticity in the micro-mechanical and geometric properties. The convergence of the proposed algorithm for stochastic natural frequency analysis of damaged thin-walled composite beam is verified and validated with original finite element method (FEM) along with traditional Monte Carlo simulation (MCS). Sensitivity analysis is carried out to ascertain the relative influence of different stochastic input parameters on the natural frequencies. Subsequently the influence of noise is investigated on radial basis function based uncertainty quantification algorithm to account for the inevitable variability for practical field applications. The study reveals that stochasticity/ system irregularity in structural and material attributes affects the system performance significantly. To ensure robustness, safety and sustainability of the structure, it is very crucial to consider such forms of uncertainties during the analysis.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Adhikari, Professor Sondipon
Authors: Naskar, S., Mukhopadhyay, T., Sriramula, S., and Adhikari, S.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:Composite Structures
Publisher:Elsevier
ISSN:0263-8223
ISSN (Online):1879-1085
Published Online:18 October 2016

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