Abstract

During the years 1994 through 1999, a European research project under the title “Design and Validation of Imperfection-Tolerant Laminated Shells” (DEVILS) was carried out. In this project, 11 European partners were involved. A goal of the project was an analytical and experimental study of the buckling behavior of thin-walled carbon fibre reinforced polymer (CFRP) laminated shells under combined axial and torsion loading. An additional aim was to compose a guideline for the dimensioning of such shells. This paper deals with the experimental and the analytical work conducted by DLR (Institute of Structural Mechanics, Braunschweig), ETH Zürich (former Institute of Lightweight Structures and Ropeways) and EMPA Dübendorf (Department of Polymers/Composites) in that project. The study was aimed at the determination of buckling loads of circular cylindrical shells of different laminate lay-ups. Nine shells were tested at DLR in Braunschweig for axial compression and at EMPA in Dübendorf under axial load and under combined axial compression and superimposed torsion. To determine the geometrical quality, the internal and the external surfaces of the specimens were mapped. ETH used photogrammetry and laser scanning prior to loading, while EMPA applied coordinate measurements for the unloaded shells and Moiré projection to monitor the lateral deflection of the cylindrical wall during loading and after buckling. At DLR, strain measurements were performed to assess regularity of the load distribution throughout the loading. The investigation showed that buckling loads of cylinders which are imperfection-sensitive under axial loading may not be so sensitive to combined loads. Furthermore, it was found that the stiffness eccentricity of the laminate played a significant role on the magnitude of the axial buckling load, while for combined loads this effect was somewhat reduced. This paper contains the results of those tests and also the comparison with results of analytical investigations and FE modeling; the obtained data can be used as benchmark reference.

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