Toggle Main Menu Toggle Search

Open Access padlockePrints

A multiscale uncertainty propagation method for dynamic analysis of laminated FRP composite plates with hybrid random and interval uncertainties

Lookup NU author(s): Professor Peter Gosling



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2023 Elsevier LtdIn this paper, a multi-scale uncertainty analysis framework to deal with hybrid random and interval uncertainties is presented to analyse dynamic characteristics of FRP composite structures. The proposed method consists of a perturbation-based probabilistic analysis, particle swarm optimization interval analysis to address the hybrid uncertainties, and the Mori–Tanaka method based homogenization theory to propagate uncertainties from microscale to macroscale. The proposed numerical approach provides estimates of the natural frequencies of composite plates, with mean and standard deviation lower and upper bounds, at a low computational cost. Numerical examples are presented to demonstrate the feasibility of the proposed method for different forms of composite structures, and also to verify its effectiveness and accuracy in predicting natural frequencies. Results show that the proposed method is highly accurate in calculating the upper and lower frequency bounds for advanced composite laminates under complicated uncertainties.

Publication metadata

Author(s): Zhou X-Y, Qian S-Y, Wang N-W, Wu W-Q, Jiang C, Cai CS, Gosling PD

Publication type: Article

Publication status: Published

Journal: Composite Structures

Year: 2023

Volume: 321

Print publication date: 01/10/2023

Online publication date: 05/06/2023

Acceptance date: 01/06/2023

Date deposited: 08/08/2023

ISSN (print): 0263-8223

ISSN (electronic): 1879-1085

Publisher: Elsevier Ltd


DOI: 10.1016/j.compstruct.2023.117223

ePrints DOI: 10.57711/jyny-mb98


Altmetrics provided by Altmetric


Funder referenceFunder name
National Nature Science Funding of China (Grant No. 52278149).
Natural Science Foundation of Jiangsu Province, China [Grant No. BK20211174]