Dynamic Modal Correlation of an Automotive Rear Subframe, with Particular Reference to the Modelling of Welded Joints

This paper presents a comparison between the experimental investigation and the Finite Element (FE) modal analysis of an automotive rear subframe. A modal correlation between the experimental data and the forecasts is performed. The present numerical model constitutes a predictive methodology able to forecast the experimental dynamic behaviour of the structure. The actual structure is excited with impact hammers and the modal response of the subframe is collected and evaluated by the PolyMAX algorithm. Both the FE model and the structural performance of the subframe are defined according to the Ferrari S.p.A. internal regulations. In addition, a novel modelling technique for welded joints is proposed that represents an extension of ACM2 approach, formulated for spot weld joints in dynamic analysis. Therefore, the Modal Assurance Criterion (MAC) is considered the optimal comparison index for the numerical-experimental correlation. In conclusion, a good numerical-experimental agreement from 50 Hz up to 500 Hz has been achieved by monitoring various dynamic parameters such as the natural frequencies, the mode shapes, and frequency response functions (FRFs) of the structure that represent a validation of this FE model for structural dynamic applications

Numerical Modeling of Aluminum Alloys Fracture for Automotive Applications

Nowadays, finite element analysis assumes a key-role in the automotive industry. Predictivity of FE models has been strongly improved during the last years and the research on this topic involves both industrial and academic fields. The main focus of this paper is the prediction of the failure of aluminum alloys used for extruded components. Material fracture affects the capacity of absorbing energy and the crashworthiness of the structure as well. In extracting the samples directly from the components involved in the crash event, it has been possible to take into account the whole manufacturing process. The methodology has been developed to improve the correlation of the FE models as well as to answer to the industrial requirements