A comparison between macro-element and finite element solutions for the stress analysis of functionally graded single-lap joints

Abstract : The interest in functionally graded adhesive (FGA) joints has been increasing in recent years. For example, FGAs offer the opportunity to optimize the strength of multi-material bonded joints by locally tailoring the adhesive properties and without modifying the design of the adherends to be joined. The development of dedicated stress analyses to predict the stress distribution is then of the highest interest to control the strength of such joints. The Finite Element (FE) method is able to address the stress analysis of FGA joints but is computationally costly. Simplified stress analyses have then been developed. The objective of this paper is to assess the prediction of simplified stress analyses, solved through the macro-element (ME) technique, with respect to those of FE models. It is shown that the predictions of ME models are in a sufficient agreement with the FE models to be employed at a pre-sizing stage. The influence of the overlap length is then investigated by the means of the simplified stress analyses. A noticeable result is the existence of an overlap length for which the adhesive peak shear stress is minimal, in the 1D-bar kinematics framework.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-02049917
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Tuesday, February 26, 2019 - 4:55:59 PM
Last modification on : Friday, October 11, 2019 - 8:23:00 PM
Long-term archiving on : Monday, May 27, 2019 - 3:24:08 PM

File

Paroissien_22890.pdf
Files produced by the author(s)

Identifiers

Citation

Eric Paroissien, Frederic Lachaud, Lucas Filipe Martins Da Silva, Salah Hammidi Seddiki. A comparison between macro-element and finite element solutions for the stress analysis of functionally graded single-lap joints. Composite Structures, Elsevier, 2019, 215, pp.331-350. ⟨10.1016/j.compstruct.2019.02.070⟩. ⟨hal-02049917⟩

Share

Metrics

Record views

64

Files downloads

6