Self-piercing riveting formation results in additional straining and property variations of the sheet material and rivet of the joint. As the riveted forming strain was concentrated within a limited area, it was difficult to characterize the properties of the pre-strained materials through conventional tensile tests. The present study dealt with the effects of considering riveted forming strain on the mechanical behavior prediction accuracy of the self-piercing riveted (SPR) joints of DP590 high-strength steel and AC43500-T7 cast aluminum alloy sheets. Main efforts were put on the evaluation of the failure parameters and behaviors of the pre-strained sheet materials. Equivalent specimens of the two sheet materials with different pre-strain levels were prepared via a flat rolling process for the characterization of the sheet deformation during the riveting process. Based on the material parameters obtained from the tensile tests of the rolled sheets and the compression tests of the rivet, a three-dimensional simulation model of the SPR joints was established. The mechanical behaviors of the joints were investigated under three loading conditions of 0° pull-out, 90° lap shear, and 45° tension–shear. The prediction accuracies of pull-off displacement under the three loading conditions reached 94.07%, 91.61% and 94.02%, and were 5.57%, 26.43% and 6.18% higher than those predicted by the model without considering the riveted forming history, respectively. The prediction accuracies of the peak force under the three loading conditions were 98.43%, 89.70% and 95.35%, respectively. The error difference of predicted peak force of the two models was less than 3%. 

Equivalent characterization of pre-strained material properties and mechanical behavior prediction of steel/aluminum self-piercing riveted joints

Currently the design of mechanical joining processes like self-pierce riveting with semi-tubular rivet (SPR-ST) and clinching for production is subject to complex and experimental test series in which process parameters such as the rivet or die geometry are varied iteratively and based on experience until a suitable joint contour and strength is achieved. To simplify the use of mechanical joining technologies these development cycles and thereby the effort for implementation into production must be reduced. In this paper, the numerical data-acquisition and the development of algorithm-based and analytical models for strength prediction for SPR-ST and Clinching is described. Therefore, an extensive experimental and numerical database regarding the SPR-ST process and strength of steel and aluminum joints with tensile strengths of the sheets between 200 - 1000 MPa was generated for the building of the models. This process data could then be used for the training and evaluation of different prediction models. The goal of the research presented here is to enable an immediate prediction of the quasi-static joint strength, based on the input parameters such as properties of the parts to be joined and process parameters.

Data-Based and Analytical Models for Strength Prediction of Mechanical Joints

Abstract. A torsion specimen is removed from the as-received thick high strength steel sheet (S700MC with a nominal thickness of 12 mm). The test material has a maximum uniform tensile strain of about 12 %. The torsion test is conducted up to fracture. The experimentally acquired torque-angle curve is then used to inversely identify the large strain flow curve up to an equivalent plastic strain of approximately 1. The identification strategy is based on the Finite Element Model Updating (FEMU) approach.

Niels Vancraeynest

Papers

Data-Based and Analytical Models for Strength Prediction of Mechanical Joints

Identification of the large strain flow curve of high strength steel via the torsion test and FEMU