Damped DQE Model Updating of a Three-Story Frame Using Experimental Data

Abstract

In this paper, following a two-stage methodology, the differential quadrature element (DQE) model of a three-story frame structure is updated for the vibration analysis. In the first stage, the mass and stiffness matrices are updated using the experimental natural frequencies. Then, having the updated mass and stiffness matrices, the structural damping matrix is updated to minimize the error between the experimental and numerical damping ratios. Note that two different damping models are used, including a diagonal matrix with unknown diagonal elements and a general damping model. Since the structural joints of the frames are not completely rigid in practice, several parameters are used to model the flexibility of these joints. The optimum values of the material and geometrical design parameters are obtained by updating the DQE model using the experimental modal parameters obtained through modal testing. Considering the robustness of the evolutionary optimization algorithms in the model updating practice, a combination of particle swarm optimization and artificial bee colony algorithm, that benefits from the advantages of both approaches, is utilized. By updating the DQE model, the effectiveness of the evolutionary optimization algorithms, especially in a high-dimensional optimization problem, e.g., finding the optimum general damping matrix, is studied. The results show that, considering the geometrical lengths of the frame as the design parameters, the natural frequencies of the updated model match better with the experimental ones. In addition, using the general damping matrix, the errors of the damping ratios significantly are decreased.