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Experiment‐based statistical distribution of buckling loads of cylindrical shells

Author(s): (Technical University of Berlin Berlin Germany)
(Brandenburg University of Technology Cottbus Germany)
(Technical University of Berlin Berlin Germany)
Medium: journal article
Language(s): English
Published in: ce/papers, , n. 3-4, v. 6
Page(s): 1816-1820
DOI: 10.1002/cepa.2593
Abstract:

A silo structure is usually constructed in the form of a cylindrical steel shell. It has the advantages of being lightweight, having a short construction period, and possessing a large storage space. It has been widely used in many fields of industry. Thin‐walled cylindrical shells often exhibit buckling failure and the experimental buckling load is usually lower than calculation results from classical theory and simulation without geometrical imperfection. Besides, test results with carefully conducted similar specimens still have substantial scatter due to imperfection sensitivity. The nonlinear analysis with FEM can obtain a high‐precision result comparing the experiment if the geometric parameters of the shell are fully known. However, this is almost impossible in practical engineering. The initial geometric imperfections and shell thickness of cylindrical shells are complex and random properties. Theoretically, these geometric imperfections can be described using a random field. This paper presents the experimental investigation of buckling analysis of cylindrical shells under axial compression considering the randomness of geometric imperfections and thickness. A total of 12 cylindrical shell specimens were fabricated and tested. Based on the test results, the optimal statistical distribution is obtained by the maximum entropy fitting method and the obtained results were compared with geometric imperfections based on laser scan measurements.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1002/cepa.2593.
  • About this
    data sheet
  • Reference-ID
    10766823
  • Published on:
    17/04/2024
  • Last updated on:
    17/04/2024
 
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