Failure Modes of Composite Sandwich Beams

  • Isaac M. DanielEmail author
  • Emmanuel E. Gdoutos


The overall performance of sandwich structures depends in general on the properties of the facesheets, the core, the adhesive bonding the core to the skins, as well as geometrical dimensions. Sandwich beams under general bending, shear and in-plane loading display various failure modes. Their initiation, propagation and interaction depend on the constituent material properties, geometry, and type of loading. Failure modes and their initiation can be predicted by conducting a thorough stress analysis and applying appropriate failure criteria in the critical regions of the beam. This analysis is difficult because of the nonlinear and inelastic behavior of the constituent materials and the complex interactions of failure modes. Possible failure modes include tensile or compressive failure of the facesheets, debonding at the core/facesheet interface, indentation failure under localized loading, core failure, wrinkling of the compression facesheet, and global buckling.

In the present work failure modes of sandwich beams were studied. Facesheet materials were typically unidirectional and carbon fabric/epoxy and glass fab-ric/vinylester. Core materials discussed include four types of a closed-cell PVC foam (Divinycell H80, H100, H160 and H250, with densities of 80, 100, 160 and 250 kg/m3, respectively) and balsa wood. The facesheet and core materials were fully characterized mechanically. The various failure modes were studied separately and both initiation and ultimate failure were determined. Following initiation of a particular failure mode, this mode may trigger and interact with other modes and final failure may follow a different failure path. The transition from one failure mode to another for varying loading or state of stress and beam dimensions was discussed. Experimental results were compared with analytical predictions.


Failure Mode Interfacial Crack Core Material Sandwich Plate Sandwich Panel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work discussed in this chapter was sponsored by the Office of Naval Research (ONR). The authors are grateful to Dr. Y.D.S. Rajapakse of ONR for his support, encouragement and cooperation.


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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Robert R. McCormick School of Engineering and Applied ScienceNorthwestern UniversityEvanstonUSA
  2. 2.School of EngineeringDemocritus University of ThraceXanthiGreece

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