Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties
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.
312-334
Naskar, Susmita
5f787953-b062-4774-a28b-473bd19254b1
Mukhopadhyay, T.
30a52c74-d9f7-4617-af88-32d44f07aca6
Sriramula, Srinivas
1f89db01-ff5c-4033-a39c-4df483fcba8c
Adhikari, S.
82960baf-916c-496e-aa85-fc7de09a1626
16 October 2016
Naskar, Susmita
5f787953-b062-4774-a28b-473bd19254b1
Mukhopadhyay, T.
30a52c74-d9f7-4617-af88-32d44f07aca6
Sriramula, Srinivas
1f89db01-ff5c-4033-a39c-4df483fcba8c
Adhikari, S.
82960baf-916c-496e-aa85-fc7de09a1626
Naskar, Susmita, Mukhopadhyay, T., Sriramula, Srinivas and Adhikari, S.
(2016)
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties.
Composite Structures, 160, .
(doi:10.1016/j.compstruct.2016.10.035).
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.
This record has no associated files available for download.
More information
Accepted/In Press date: 15 October 2016
Published date: 16 October 2016
Identifiers
Local EPrints ID: 450993
URI: http://eprints.soton.ac.uk/id/eprint/450993
ISSN: 0263-8223
PURE UUID: 1fc881eb-0a3a-4c3a-abfd-4453e89a8cbc
Catalogue record
Date deposited: 01 Sep 2021 16:30
Last modified: 17 Mar 2024 04:07
Export record
Altmetrics
Contributors
Author:
T. Mukhopadhyay
Author:
Srinivas Sriramula
Author:
S. Adhikari
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics