Dynamic substructuring methods serve as a powerful tool in the analysis of modern complex systems. The coupling of substructures has been successful with analytically obtained results. However, substructuring with experimentally obtained data remains challenging. One of the main problems associated with experimental substructuring is the coupling of the rotational degrees of freedom (RDoFs). A promising method where RDoFs are included implicitly is the virtual point transformation. Even though the transformation has been successfully used in the substructuring process, it is still highly susceptible to inaccuracies in the sensor sensitivity and positioning. In this paper an expansion to the virtual point transformation is proposed, which enables the projection of a directly measured rotation response on the interface deformation modes. A novel formulation of the weighting matrix is introduced to consistently include the measured rotations in the transformation. The proposed expansion is demonstrated on a numerical model of a simple beam-like structure and compared with the standard transformation. The effects of inaccuracies in the sensor sensitivity and placement on the overall quality of both transformation are analysed with a global sensitivity analysis. Finally, an experimental validation of the proposed expansion is carried out on a steel beam.
COBISS.SI-ID: 17033755
An inovatie algorithm for identifying inconsistent experimental frequency response functions is introduced. Algorithm is based on coupling of equivalent numerical and experimental models into a hybrid model. The method for coupling structures in the frequency domain with Lagrange multipliers enables calculation of frequency response functions of the coupled system based on the assembly of dynamic models of individual substructures. The proposed algorithm provides more consistent experimental model, which leads to more accurate coupling results.
COBISS.SI-ID: 16816667
Especially when dealing with the nonlinear dynamic systems, numerical analysis of complex structures can be computationally expensive. In such case model order reduction methods are of great interest. The procedure of modal truncation which is well established in the linear analysis can be further expanded by the concept of modal derivatives for the reduction of nonlinear systems. In the article the presented procedure in implemented on a simple case study. The comparison of the full and reduced integration indicates significant decrease in computation times with minimal effect on the accuracy of the results.
COBISS.SI-ID: 16816923