The present paper is concerned with the optimal control and/or design of symmetric and antisymmetric composite laminate with two piezoelectric layers bonded to the opposite surfaces of the laminate, and placed symmetrically with respect to the middle plane. For the optimal control problem, Liapunov-Bellman theory is used to minimize the dynamic response of the laminate. The dynamic response of the laminate comprises a weight sum of the control objective (the total vibrational energy) and a penalty functional including the control force. Simultaneously with the active control, thicknesses and the orientation angles of layers are taken as design variables to achieve optimum design. The formulation is based on various plate theories for various boundary conditions. Explicit solutions for the control function and controlled deflections are obtained in forms of double series. Numerical results are given to demonstrate the effectiveness of the proposed control and design mechanism, and to investigate the effects of various laminate parameters on the control and design process.

This paper deals with the experimental validation of the use of PVDF Patches for the assessment of spatial derivatives of displacement field. It focuses more exactly on the shear Force Identification by using Specific forms of PVDF patcHes (FISH) on beams. An overview of the theoretical approach is exposed. The principle is based on the use of the weak form of the equation of motion of the beam which allows the shear forces to be extracted at one edge of the sensor when this last has a specific form. The experimental validation is carried out with a cantilever steel beam, excited by a shaker at its free boundary. The validation consists in comparing the shear force measured by the designed sensor glued at the free edge and the directly measured force applied by the shaker. The sensor is made of two patches, called the "stiffness" patch and the "mass" patch. The use of both patches allows one to identify correctly the shear force on a large frequency domain. The use of only the stiffness patch is valid in the low frequency domain and has the advantage to have a frequency-independent gain that allows its use in real time.

In the present paper, a method for identifying damage in a multi storeyed shear building structure is presented using minimum number of modal parameters of the structure. A damage at any level of the structure may lead to a major failure if the damage is not attended at appropriate time. Hence an early detection of damage is essential. The proposed identification methodology requires experimentally determined sparse modal data of any particular mode as input to detect the location and extent of damage in the structure. Here, the first natural frequency and corresponding partial mode shape values are used as input to the model and results are compared by changing the sensor placement locations at different floors to conclude the best location of sensors for accurate damage identification. Initially experimental data are simulated numerically by solving eigen value problem of the damaged structure with inclusion of random noise on the vibration characteristics. Reliability of the procedure has been demonstrated through a few examples of multi storeyed shear structure with different damage scenarios and various noise levels. Validation of the methodology has also been done using dynamic data obtained through experiment conducted on a laboratory scale steel structure.

This study investigates the problem of crack detection in post-buckled beam-type structures. The beam under the axial compressive force has a crack, assumed to be open and through the width. The crack, which is modeled by a massless rotational spring, divides the beam into two segments. The crack detection is considered as an optimization problem, and the weighted sum of the squared errors between the measured and computed natural frequencies is minimized by the bees algorithm. To find the natural frequencies, the governing nonlinear equations of motion for the post-buckled state are first derived. The solution of the nonlinear differential equations of the two segments consists of static and dynamic parts. The differential quadrature method along with an arc length strategy is used to solve the static part, while the same method is utilized for the solution of the linearized dynamic part and the extraction of the natural frequencies of the cracked beam. The investigation includes several numerical as well as experimental case studies on the post-buckled simply supported and clamped-clamped beams having open cracks. The results show that several parameters such as the amount of applied compressive force and boundary conditions influences the outcome of the crack detection scheme. The identification results also show that the crack position and depth can be predicted well by the presented method.

In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization (PSO) are applied to the problem of damage detection using frequencies and mode shapes of the structures. The objective is to identify the location and extent of multi-damage in structures. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including two beams and two trusses are considered. A comparison between the PSO and MCSS is conducted to show the efficiency of the MCSS in finding the global optimum. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data.

Helical structures made of superelastic shape memory alloys are widely used as interventional medical devices and active actuators. These structures generally undergo large deformation during expansion or actuation. Currently their behaviour is modelled numerically using the finite element method or obtained through experiments. Analytical tools are absent. In this paper, an analytical approach has been developed for analyzing the mechanical responses of such structures subjected to axial and torsional loads. The simulation results given by the analytical approach have been compared with both numerical and experimental data. Good agreements between the results indicate that the analysis is valid.

3D two adjacent buildings with different heights founded in different kinds of soil connected with viscous dampers groups, with especial arrangement in plane, were investigated. Soil structure interaction for three different kinds of soil (stiff, medium and soft) were modeled as 3D Winkler model to give the realistic behavior of adjacent buildings connected with viscous dampers under various earthquake excitations taking in the account the effect of different kinds of soil beneath the buildings, using SAP2000n to model the whole system. A range of soil properties and soil damping characteristics are chosen which gives broad picture of connected structures system behavior resulted from the influence soil-structure interaction. Its conclusion that the response of connected structures system founded on soft soil are more critical than those founded on stiff soil. The behavior of connected structures is different from those with fixed base bigger by nearly 20%, and the efficiency of viscous dampers connecting the two adjacent buildings is reduced by nearly 25% less than those founded on stiff soil.

In this paper, we have applied a new class of approximate analytical methods called Variational Approach (VA) for high nonlinear vibration equations. Three examples have been introduced and discussed. The effects of important parameters on the response of the problems have been considered. Runge-Kutta's algorithm has been used to prepare numerical solutions. The results of variational approach are compared with energy balance method and numerical and exact solutions. It has been established that the method is an easy mathematical tool for solving conservative nonlinear problems. The method doesn't need small perturbation and with only one iteration achieve us to a high accurate solution.

The stiffness of a structure is one of several structural signals that are useful indicators of the amount of damage that has been done to the structure. To accurately estimate the stiffness, an equation of motion containing a stiffness parameter must first be established by expansion as a linear series model, a Taylor series model, or a power series model. The model is then used in multivariate autoregressive modeling to estimate the structural stiffness and compare it to the theoretical value. Stiffness assessment for modeling purposes typically involves the use of one of three statistical model refinement approaches, one of which is the efficient Akaike information criterion (AIC) proposed in this paper. If a newly added component of the model results in a decrease in the AIC value, compared to the value obtained with the previously added component(s), it is statistically justifiable to retain this new component; otherwise, it should be removed. This model refinement process is repeated until all of the components of the model are shown to be statistically justifiable. In this study, this model refinement approach was compared with the two other commonly used refinement approaches: principal component analysis (PCA) and principal component regression (PCR) combined with the AIC. The results indicate that the proposed AIC approach produces more accurate structural stiffness estimates than the other two approaches.

The present paper deals with the free vibration analysis of the functionally graded solid and annular circular plates with two functionally graded piezoelectric layers at top and bottom subjected to an electric field. Classical plate theory (CPT) is used for description of the all deformation components based on a symmetric distribution. All the mechanical and electrical properties except Poisson's ratio can vary continuously along the thickness direction of the plate. The properties of plate core can vary from metal at bottom to ceramic at top. The effect of non homogeneous index of functionally graded and functionally graded piezoelectric sections can be considered on the results of the system. $1^{st}$ and $2^{nd}$ modes of natural frequencies of the system have been evaluated for both solid and annular circular plates, individually.

Smart structures and intelligent systems play pivotal roles in numerous areas of applied sciences ranging from civil engineering to computer and communications systems engineering. Although such structures and systems have been intensively deployed in these areas, they have been, interestingly, very rarely deployed in the field of cultural heritage preservation.This paper presents one of thefirst such attempts. A new methodology is describedthat deploys smart structures andlinks them with artificial intelligence methods.These solutions are referred toas advanced hybrid engineering artefacts. By their use,important environmental factors can be monitoredin hard to access, remote or unsafe locationsby minimizing the need for human involvement. In addition toproviding safety the methodologyalso reduces costs and, most importantly,providesa new way to modelany particular micro-environment in a much more efficient way than this is possible with traditional ways. Last but not least, although themethodology has been developed for cultural heritage preservation, its application areas are much broader and it is expected that it will find its applicationin other domains like civil engineering and ecology.

Placing sensors at appropriate locations is an important task in the design of an efficient structural health monitoring (SHM) system for a large-scale civil structure. In this paper, a hybrid optimization algorithm called virus monkey algorithm (VMA) based on the virus theory of evolution is proposed to seek the optimal placement of sensors. Firstly, the dual-structure coding method is adopted instead of binary coding method to code the solution. Then, the VMA is designed to incorporate two populations, a monkey population and a virus population, enabling the horizontal propagation between the monkey and virus individuals and the vertical inheritance of monkey's position information from the previous to following position. Correspondingly, the monkey population in this paper is divided into the superior and inferior monkey populations, and the virus population is divided into the serious and slight virus populations. The serious virus is used to infect the inferior monkey to make it escape from the local optima, while the slight virus is adopted to infect the superior monkey to let it find a better result in the nearby area. This kind of novel virus infection operator enables the coevolution of monkey and virus populations. Finally, the effectiveness of the proposed VMA is demonstrated by designing the sensor network of the Canton Tower, the tallest TV Tower in China. Results show that innovations in the VMA proposed in this paper can improve the convergence of algorithm compared with the original monkey algorithm (MA).