Semi-active control equipments are used to effectually enhance the seismic behavior of structures. Magneto-rheological (MR) dampers are semi-active devices that can be utilized to control the response of structures during seismic loads and have received voracious attention for response suppression. They supply the adaptability of active devices and stability and reliability of passive devices. This paper presents an optimal fuzzy logic control scheme for vibration mitigation of buildings using magneto-rheological dampers subjected to near-fault ground motions. Near-fault features including a directivity pulse in the fault-normal direction and a fling step in the fault-parallel direction are considered in the requisite ground motion records. The membership functions and fuzzy rules of fuzzy controller were optimized by genetic algorithm (GA). Numerical study is performed to analyze the influences of near-fault ground motions on a building that is equipped with MR dampers. Considering the uncontrolled system response as the base line, the proposed method is scrutinized by analogy with that of a conventional maximum dissipation energy (MED) controller to accentuate the effectiveness of the fuzzy logic algorithm. Results reveal that the fuzzy logic controllers can efficiently improve the structural responses and MR dampers are quite promising for reducing seismic responses during near-fault earthquakes.

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.

In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.

In this paper, a wireless sensing system for structural field evaluation and rating of bridges is presented. The system uses a wireless platform integrated with traditional analogue sensors including strain gages and accelerometers along with the operating software. A wireless vehicle position indicator is developed using a tri-axial accelerometer node that is mounted on the test vehicle, and was used for identifying the moving truck position during load testing. The developed software is capable of calculating the theoretical bridge rating factors based on AASHTO Load and Resistance Factor Rating specifications, and automatically produces the field adjustment factor through load testing data. The sensing system along with its application in bridge deck rating was successfully demonstrated on the Evansville Bridge in West Virginia. A finite element model was conducted for the test bridge, and was used to calculate the load distribution factors of the bridge deck after verifying its results using field data. A confirmation field test was conducted on the same bridge and its results varied by only 3% from the first test. The proposed wireless sensing system proved to be a reliable tool that overcomes multiple drawbacks of conventional wired sensing platforms designed for structural load evaluation of bridges.

In this paper the application of the Interpolation Damage Detection Method to the numerical model of a suspension bridge instrumented with a network of Micro-Electro-Mechanical System sensors is presented. The method, which, in its present formulation, belongs to Level II damage identification method, can identify the presence and the location of damage from responses recorded on the structure before and after a seismic damaging event. The application of the method does not require knowledge of the modal properties of the structure nor a numerical model of it. Emphasis is placed herein on the influence of recorded signals noise on the reliability of the results given by the Interpolation Damage Detection Method. The response of a suspension bridge to seismic excitation is computed from a numerical model and artificially corrupted with random noise characteristic of two families of Micro-Electro-Mechanical System accelerometers. The reliability of the results is checked for different damage scenarios.

The purpose of this paper is to identify through experiments the finite element (FE) model of a building structure using a magnetorheological (MR) fluid damper. The FE model based system identification (FEBSI) technique evaluates the control performance of an MR damper that has nonlinear characteristics as equivalent linear properties such as mass, stiffness, and damping. The Bingham and Bouc-Wen models were used for modeling the MR damper and the equivalent damping increased by the MR damper was predicted by applying an equivalent linearization technique. Experimental results indicate that the predicted equivalent damping matches well with the experimentally obtained damping.