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Residual Stresses and Plastic Deformation in Self-Pierce Riveting of Dissimilar Aluminum-to-Magnesium Alloys

Journal Article
05-11-02-0015
ISSN: 1946-3979, e-ISSN: 1946-3987
Published May 08, 2018 by SAE International in United States
Residual Stresses and Plastic Deformation in Self-Pierce Riveting of Dissimilar Aluminum-to-Magnesium Alloys
Sector:
Citation: Moraes, J., Jordon, J., Su, X., Brewer, L. et al., "Residual Stresses and Plastic Deformation in Self-Pierce Riveting of Dissimilar Aluminum-to-Magnesium Alloys," SAE Int. J. Mater. Manf. 11(2):139-150, 2018, https://doi.org/10.4271/05-11-02-0015.
Language: English

Abstract:

In this work, the complex relationship between deformation history and residual stresses in a magnesium-to-aluminum self-pierce riveted (SPR) joint is elucidated using numerical and experimental approaches. Non-linear finite element (FE) simulations incorporating strain rate and temperature effects were performed to model the deformation in the SPR process. In order to accurately capture the deformation, a stress triaxiality-based damage material model was employed to capture the sheet piercing from the rivet. Strong visual comparison between the physical cross-section of the SPR joint and the simulation was achieved. To aid in understanding of the role of deformation in the riveting process and to validate the modeling approach, several experimental measurements were conducted. To quantify the plastic deformation from the piercing of the rivet, micro hardness mapping was performed on a cross-section of the SPR joint. The FE model showed very strong correlation to the experimental hardness mapping results suggesting the nonlinear model captured the plastic deformation with high accuracy. To measure the elastic residual stresses in the SPR joint, neutron and x-ray diffraction mapping techniques were conducted and in general, the FE model correlated well to the trends and magnitudes of the elastic stresses. While some error occurred in between the model and the neutron and x-ray diffraction results, the numerical approach developed in this study shows potential as a tool for understanding SPR behavior as well as optimizing the process parameters.