Robustness of empirical vibration correlation techniques for predicting the instability of unstiffened cylindrical composite shells in axial compression

Journal Article (2020)
Author(s)

Eduards Skukis (Riga Technical University)

Gints Jekabsons (Riga Technical University)

Jānis Andersons (University of Latvia)

Olgerts Ozolins (Riga Technical University)

Edgars Labans (TU Delft - Aerospace Structures & Computational Mechanics)

Kaspars Kalnins (Riga Technical University, Ikskile Centre of Composite Competence Ltd.)

DOI related publication
https://doi.org/10.3390/polym12123069 Final published version
More Info
expand_more
Publication Year
2020
Language
English
Issue number
12
Volume number
12
Article number
3069
Pages (from-to)
1-18
Downloads counter
232
Collections
Institutional Repository
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Thin-walled carbon fiber reinforced plastic (CFRP) shells are increasingly used in aerospace industry. Such shells are prone to the loss of stability under compressive loads. Furthermore, the instability onset of monocoque shells exhibits a pronounced imperfection sensitivity. The vibration correlation technique (VCT) is being developed as a nondestructive test method for evaluation of the buckling load of the shells. In this study, accuracy and robustness of an existing and a modified VCT method are evaluated. With this aim, more than 20 thin-walled unstiffened CFRP shells have been produced and tested. The results obtained suggest that the vibration response under loads exceeding 0.25 of the linear buckling load needs to be characterized for a successful application of the VCT. Then the largest unconservative discrepancy of prediction by the modified VCT method amounted to ca. 22% of the critical load. Applying loads exceeding 0.9 of the buckling load reduced the average relative discrepancy to 6.4%.