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In the area of semi-active control of civil structures, Magneto-Rheological (MR) damper has been an efficient mechanism for reducing the seismic response of structures. In this paper, an effective method based on defining an optimization problem for designing MR dampers has been proposed. In the proposed method, the parameters of semi-active control system are determined so that the maximum response of structure is minimized. To solve the optimization problem, the Genetic algorithm (GA) has been utilized. The modified Bouc-Wen model has been used to represent the dynamic behavior of MR damper while to determine the input voltage at any time step, the clipped optimal control algorithm with LQR controller has been applied. To evaluate the performance of the proposed method, a ten-storey shear frame subjected to the El-Centro excitation and for two different kinds of objective functions, optimal MR dampers have been designed. Then the performance of optimal MR damper has been tested under different excitations. The results of the numerical simulations have shown the effectiveness of the proposed method in designing optimal MR dampers that have the capability of reducing the response of the structures up to a significant level. In addition, the effect of selecting a proper objective function to achieve the best performance of MR dampers in decreasing different responses of structure has been shown.

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Detecting the location and severity of damage, particularly in the early stages, is a significant topic in structural engineering. This study proposes a new identification method that can achieve third-level damage detection of structures. The approach involves conducting a static load test to measure the structure's static responses, along with a finite element model updating method that utilizes an optimization strategy. Based on the structure's static responses, a new damage index is introduced. This index comprises two components: a location index, which represents the residual values between structural responses in intact and damaged states, and a severity index, which is defined based on the correlation coefficient between structural responses in actual damage scenarios and the outcomes from the model updating process. Jaya optimization algorithm is used in this regard. The effectiveness of the proposed method is assessed through four numerical examples involving beam and frame structures under various damage scenarios. In addition, the method's performance is evaluated for noisy data. The results demonstrate the proposed method's effectiveness and high precision in identifying structural damage. However, the results also indicate that the proposed approach is highly sensitive to noisy data.