Stiffened Panels Damage Tolerance Determination using an Optimization Procedure based on a Linear Delamination Growth Approach

Journal Title: American Journal of Engineering and Applied Sciences - Year 2016, Vol 9, Issue 4

Abstract

Abstract The damage tolerance of delaminated composite panels under compressive load is usually numerically evaluated by means of computationally expensive non-linear approaches. In this study, an alternative numerical linear approach, able to mimic the delamination propagation initiation, is proposed. With the aim to exploit its benefits, in terms of computational costs reduction, the proposed linear methodology has been used in this study in conjunction with an optimization analysis to assess the damage tolerance of stiffened composite panels with an impact induced delamination under compression. Indeed, the optimization was aimed to find the minimum delamination growth initiation load for a delaminated stiffened panel with variable delamination size and position, providing indications on the damage tolerance capability of the stiffened panel with an arbitrary positioned and sized delamination induced (as an example) by a low energy impact. Copyright © 2016 Aniello Riccio, Francesco Di Caprio, Francesco Scaramuzzino, Andrea Sellitto and Mauro Zarrelli. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Authors and Affiliations

Aniello Riccio, Francesco Di Caprio, Andrea Sellitto, Mauro Zarrelli

Keywords

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  • EP ID EP202532
  • DOI 10.3844/ajeassp.2016.1301.1317
  • Views 58
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How To Cite

Aniello Riccio, Francesco Di Caprio, Andrea Sellitto, Mauro Zarrelli (2016). Stiffened Panels Damage Tolerance Determination using an Optimization Procedure based on a Linear Delamination Growth Approach. American Journal of Engineering and Applied Sciences, 9(4), 1301-1317. https://europub.co.uk/articles/-A-202532