International Journal of Fracture

, Volume 134, Issue 3, pp 231–250

Failure Analysis of Adhesively Bonded Structures: From Coupon Level Data to Structural Level Predictions and Verification

  • De Xie
  • Jaeung Chung
  • Anthony M. Waas
  • Khaled W. Shahwan
  • Jessica A. Schroeder
  • Raymond G. Boeman
  • Vlastimil Kunc
  • Lynn B. Klett
Article

DOI: 10.1007/s10704-005-0646-y

Cite this article as:
De Xie, Chung, J., Waas, A.M. et al. Int J Fract (2005) 134: 231. doi:10.1007/s10704-005-0646-y

Abstract

This paper presents a predictive methodology and verification through experiment for the analysis and failure of adhesively bonded, hat stiffened structures using coupon level input data. The hats were made of steel and carbon fiber reinforced polymer composite, respectively, and bonded to steel adherends. A critical strain energy release rate criterion was used to predict the failure loads of the structure. To account for significant geometrical changes observed in the structural level test, an adaptive virtual crack closure technique based on an updated local coordinate system at the crack tip was developed to calculate the strain energy release rates. Input data for critical strain energy release rates as a function of mode mixity was obtained by carrying out coupon level mixed mode fracture tests using the Fernlund–Spelt (FS) test fixture. The predicted loads at failure, along with strains at different locations, were compared with those measured from the structural level tests. The predictions were found to agree well with measurements for multiple replicates of adhesively bonded hat-stiffened structures made with steel hat/adhesive/steel and composite hat/adhesive/steel, thus validating the proposed methodology for failure prediction.

Keywords

Adhesively bonded structuresfailure analysisfracture toughness of adhesivemixed-mode fracture envelopestrain energy release ratesvirtual crack closure technique

Copyright information

© Springer 2005

Authors and Affiliations

  • De Xie
    • 1
  • Jaeung Chung
    • 1
  • Anthony M. Waas
    • 1
  • Khaled W. Shahwan
    • 2
  • Jessica A. Schroeder
    • 3
  • Raymond G. Boeman
    • 4
  • Vlastimil Kunc
    • 4
  • Lynn B. Klett
    • 4
  1. 1.Department of Aerospace EngineeringThe University of MichiganAnn ArborUSA
  2. 2.Scientific LabsDaimlerChrysler CorporationAuburn HillsUSA
  3. 3.Research and Development CenterGeneral Motors CorporationWarrenUSA
  4. 4.Metals and Ceramics DivisionOak Ridge National LaboratoryOak RidgeUSA