Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

This paper addresses the problem of damage detection in suspension bridge hangers, with an emphasis on the modal flexibility method. It aims at evaluating the capability and the accuracy of the modal flexibility method to detect and locate single and multiple damages in suspension bridge hangers, with different level of severity and various locations. The study is conducted numerically and experimentally on a laboratory suspension bridge mock-up. First, the covariance-driven stochastic subspace identification is used to extract the modal parameters of the bridge from experimental data, using only output measurements data from ambient vibration. Then, the method is demonstrated for several damage scenarios and compared against other classical methods, such as: Coordinate Modal Assurance Criterion (COMAC), Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC) and Modal Strain Energy (MSE). The paper demonstrates the relative merits and shortcomings of these methods which play a significant role in the damage detection ofsuspension bridges.

The present study investigate the compressive stress, shear stress, tensile stress, vertical electrical displacement and horizontal electrical displacement induced due to a load moving with uniform velocity on the free rough surface of an irregular transversely isotropic functionally graded piezoelectric material (FGPM) substrate. The closed form expressions ofsaid induced stresses and electrical displacements for both electrically open condition and electrically short condition have been deduced. The influence of various affecting parameters viz. maximum depth of irregularity, irregularity factor, parameter of functionally gradedness, frictional coefficient of the rough upper surface, piezoelectricity/dielectricity on said induced stresses and electrical displacements have been examined through numerical computation and graphical illustration for both electrically open and short conditions. The comparative analysis on the influence of electrically open and short conditions as well as presence and absence of piezoelectricity on the induced stresses and induced electrical displacements due to a moving load serve as the salient features of the present study. Moreover, some important peculiarities have also been traced out by means of graphs.

This paper is devoted to proposing a new approach for damage detection of structures. In this technique, the biconjugate gradient method (BCG) is employed. To remedy the noise effects, a new preconditioning algorithm is applied. The proposed preconditioner matrix significantly reduces the condition number of the system. Moreover, based on the characteristics of the damage vector, a new direct search algorithm is employed to increase the efficiency of the suggested damage detection scheme by reducing the number of unknowns. To corroborate the high efficiency and capability of the presented strategy, it is applied for estimating the severity and location of damage in the well-known 31-member and 52-member trusses. For damage detection of these trusses, the time history responses are measured by a limited number of sensors. The results of numerical examples reveal high accuracy and robustness of the proposed method.

Offshore structures are generally exposed to harsh environments such as strong tidal currents and wind loadings. Monitoring the structural soundness and integrity of offshore structures is crucial to prevent catastrophic collapses and to prolong their lifetime; however, it is intrinsically challenging because of the difficulties in accessing the critical structural members that are located under water for installing and repairing sensors and data acquisition systems. Virtual sensing technologies have the potential to alleviate such difficulties by estimating the unmeasured structural responses at the desired locations using other measured responses. Despite the usefulness of virtual sensing, its performance and applicability to the structural health monitoring of offshore structures have not been fully studied to date. This study investigates the use of virtual sensing of offshore structures. A Kalman filter based virtual sensing algorithm is developed to estimate responses at the location of interest. Further, this algorithm performs a multi-sensor data fusion to improve the estimation accuracy under non-stationary tidal loading. Numerical analysis and laboratory experiments are conducted to verify the performance of the virtual sensing strategy using a bottom-fixed offshore structural model. Numerical and experimental results show that the unmeasured responses can be reasonably recovered from the measured responses.

In general, it may be advantageous to measure the pressure pulsation near a valve to detect a valve defect in a linear compressor. However, the acceleration signals are more advantageous for rapid classification in a mass-production line. This paper deals with the performance improvement of fault classification using only the compressor-shell acceleration signal based on the relation between the refrigerant pressure pulsation and the shell acceleration of the compressor. A transfer function was estimated experimentally to take into account the signal noise ratio between the pressure pulsation of the refrigerant in the suction pipe and the shell acceleration. The shell acceleration signal of the compressor was modified using this transfer function to improve the defect classification performance. The defect classification of the modified signal was evaluated in the acceleration signal in the frequency domain using Fisher's discriminant ratio (FDR). The defect classification method was validated by experimental data. By using the method presented, the classification of valve defects can be performed rapidly and efficiently during mass production.

The shear behavior of soil-concrete interface is mainly affected by the surface roughness of the two contact surfaces. The present research emphasizes on investigating the effect of roughness of soil-concrete interface on the interface shear behavior in two-layered laboratory testing samples. In these specially prepared samples, clay silt layer with density of $2027kg/m^3$ was selected to be in contact a concrete layer for simplifying the laboratory testing. The particle size testing and direct shear tests are performed to determine the appropriate particles sizes and their shear strength properties such as cohesion and friction angle. Then, the surface undulations in form of teeth are provided on the surfaces of both concrete and soil layers in different testing carried out on these mixed specimens. The soil-concrete samples are prepared in form of cubes of 10*10*30 cm. in dimension. The undulations (inter-surface roughness) are provided in form of one tooth or two teeth having angles $15^{\circ}$ and $30^{\circ}$, respectively. Several direct shear tests were carried out under four different normal loads of 80, 150, 300 and 500 KPa with a constant displacement rate of 0.02 mm/min. These testing results show that the shear failure mechanism is affected by the tooth number, the roughness angle and the applied normal stress on the sample. The teeth are sheared from the base under low normal load while the oblique cracks may lead to a failure under a higher normal load. As the number of teeth increase the shear strength of the sample also increases. When the tooth roughness angle increases a wider portion of the tooth base will be failed which means the shear strength of the sample is increased.

Adopting sloped rolling-type isolation devices underneath a raised floor system has been proved as one of the most effective approaches to mitigate seismic responses of the protected equipment installed above. However, pounding against surrounding walls or other obstructions may occur if such a base-isolated raised floor system is subjected to long-period excitation, leading to adverse effects or even more severe damage. In this study, real-time hybrid simulation (RTHS) is adopted to assess the control performance of a smart base-isolated raised floor system as it is an efficient and cost-effective experimental method. It is composed of multiple sloped rolling-type isolation devices, a rigid steel platen, four magnetorheological (MR) dampers, and protected high-tech equipment. One of the MR dampers is physically tested in the laboratory while the remainders are numerically simulated. In order to consider the effect of input excitation characteristics on the isolation performance, the smart base-isolated raised floor system is assumed to be located at the roof of a building and the ground level. Four control algorithms are designed for the MR dampers including passive-on, switching, modified switching, and fuzzy logic control. Six artificial spectrum-compatible input excitations and three slope angles of the isolation devices are considered in the RTHS. Experimental results demonstrate that the incorporation of semi-active control into a base-isolated raised floor system is effective and feasible in practice for high-tech industry.