File(s) under permanent embargo
Recovery of capacity lost due to openings in cylindrical shells under compression
journal contributionposted on 2023-05-19, 06:32 authored by Ali AlsalahAli Alsalah, Damien HollowayDamien Holloway, Ghanbari Ghazijahani, T
Cylindrical shell structures such as silos and wind turbine towers often feature openings for internal access, and these may have a significant detrimental effect on the buckling load. This paper numerically investigates the buckling of cylindrical shells with cutouts near the cylinder end using nonlinear finite element analysis. The finite element (FE) model was validated against published experiments on the axial compression of moderately thin-walled cylinders with cutouts of various sizes and shapes. The results indicate excellent qualitative and quantitative agreements for loads, deflections, and buckled mode shapes. Using the validated FE model, it was found that the opening width is the most critical geometric parameter in terms of loss of carrying capacity. The model was then extended to explore a variety of stiffener configurations aimed at recovering the capacity lost due to the opening. These configurations included a frame ring, as well as the simpler option of straight ribs on either side of and above the hole. Thickness and protrusion were also considered in the analysis. It was found that the frame ring achieved full recovery of the lost capacity, while the straight stiffeners were effective where only up to 67% recovery was required. The results also indicated that the optimum placement of stiffeners was immediately adjacent to the cutout. This study demonstrates that the optimum stiffener is a fully enclosed ring immediately adjacent to the cutout edge, and that full load recovery can be achieved with an appropriate design.
Publication titleJournal of Constructional Steel Research
Department/SchoolSchool of Engineering
PublisherElsevier Sci Ltd
Place of publicationThe Boulevard, Langford Lane, Kidlington, Oxford, England, Oxon, Ox5 1Gb
Rights statement© 2017 Elsevier Ltd. All rights reserved.