This paper presents the application of a semi-active fuzzy based control system for seismic response reduction of a single degree-of-freedom (SDOF) framed structure using a Magnetorheological (MR) damper. Semi-active vibration control with MR dampers has been shown to be a viable approach to protect building structures from earthquake excitation. Moreover, intelligent damping systems based on soft-computing techniques such as fuzzy logic models have the inherent robustness to deal with typical uncertainties and non-linearities present in civil engineering structures. Thus, the proposed semi-active control system uses fuzzy logic based models to simulate the behavior of MR damper and also to develop the control algorithm that computes the required control signal to command the actuator. The results of the numerical simulations show the effectiveness of the suggested semi-active control system in reducing the response of the SDOF structure.

In this paper, a novel simple shear deformation theory for buckling analysis of single layer graphene sheet is formulated using the nonlocal differential constitutive relations of Eringen. The present theory involves only three unknown and three governing equation as in the classical plate theory, but it is capable of accurately capturing shear deformation effects, instead of five as in the well-known first shear deformation theory (FSDT) and higher-order shear deformation theory (HSDT). A shear correction factor is, therefore, not required. Nonlocal elasticity theory is employed to investigate effects of small scale on buckling of the rectangular nano-plate. The equations of motion of the nonlocal theories are derived and solved via Navier's procedure for all edges simply supported boundary conditions. The results are verified with the known results in the literature. The influences played by Effects of nonlocal parameter, length, thickness of the graphene sheets and shear deformation effect on the critical buckling load are studied. Verification studies show that the proposed theory is not only accurate and simple in solving the buckling nanoplates, but also comparable with the other higher-order shear deformation theories which contain more number of unknowns.

In structural health monitoring, it is meaningful to comprehensively utilize accelerometers and strain gauges to obtain the modal information of a structure. In this paper, a modal estimation theory is proposed, in which the displacement modes of the locations without accelerometers can be estimated by the strain modes of selected strain gauge measurements. A two-stage sensor placement method, in which strain gauges are placed together with triaxial accelerometers to obtain more structural displacement mode information, is proposed. In stage one, the initial accelerometer locations are determined through the combined use of the modal assurance criterion and the redundancy information. Due to various practical factors, however, accelerometers cannot be placed at some of the initial accelerometer locations; the displacement mode information of these locations are still in need and the locations without accelerometers are defined as estimated locations. In stage two, the displacement modes of the estimated locations are estimated based on the strain modes of the strain gauge locations, and the quality of the estimation is seen as a criterion to guide the selection of the strain gauge locations. Instead of simply placing a strain gauge at the midpoint of each beam element, the influence of different candidate strain gauge positions on the estimation of displacement modes is also studied. Finally, the modal assurance criterion is utilized to evaluate the performance of the obtained multitype sensor placement. A bridge benchmark structure is used for a numerical investigation to demonstrate the effectiveness of the proposed multitype sensor placement method.

Carbon fiber reinforced polymer (CFRP) cable has good mechanical properties and corrosion resistance. However, the anchorage of CFRP cable is a big issue due to the anisotropic property of CFRP material. In this article, a high-efficient bonding anchorage with novel configuration is developed for CFRP cables. The acoustic emission (AE) technique is employed to evaluate the performance of anchorage in the fatigue test and post-fatigue ultimate bearing capacity test. The obtained AE signals are analyzed by using a combination of unsupervised K-means clustering and supervised K-nearest neighbor classification (K-NN) for quantifying the performance of the anchorage and damage evolutions. An AE feature vector (including both frequency and energy characteristics of AE signal) for clustering analysis is proposed and the under-sampling approaches are employed to regress the influence of the imbalanced classes distribution in AE dataset for improving clustering quality. The results indicate that four classes exist in AE dataset, which correspond to the shear deformation of potting compound, matrix cracking, fiber-matrix debonding and fiber fracture in CFRP bars. The AE intensity released by the deformation of potting compound is very slight during the whole loading process and no obvious premature damage observed in CFRP bars aroused by anchorage effect at relative low stress level, indicating the anchorage configuration in this study is reliable.

This paper reports the development of a theoretically rigorous method for permanent way engineers to assess the condition of railway ballast under a concrete sleeper with the potential to be extended to a smart system for long-term health monitoring of railway ballast. Owing to the uncertainties induced by the problems of modeling error and measurement noise, the Bayesian approach was followed in the development. After the selection of the most plausible model class for describing the damage status of the rail-sleeper-ballast system, Bayesian model updating is adopted to calculate the posterior PDF of the ballast stiffness at various regions under the sleeper. An obvious drop in ballast stiffness at a region under the sleeper is an evidence of ballast damage. In model updating, the model that can minimize the discrepancy between the measured and model-predicted modal parameters can be considered as the most probable model for calculating the posterior PDF under the Bayesian framework. To address the problems of non-uniqueness and local minima in the model updating process, a two-stage hybrid optimization method was developed. The modified evolutionary algorithm was developed in the first stage to identify the important regions in the parameter space and resulting in a set of initial trials for deterministic optimization to locate all most probable models in the second stage. The proposed methodology was numerically and experimentally verified. Using the identified model, a series of comprehensive numerical case studies was carried out to investigate the effects of data quantity and quality on the results of ballast damage detection. Difficulties to be overcome before the proposed method can be extended to a long-term ballast monitoring system are discussed in the conclusion.

In this paper, a theoretical and numerical study on bridge simultaneous damage detection procedure for identifying both the system parameters and input excitation mass, are presented. This method is called 'Adjoint Variable Method' which is an iterative gradient-based model updating method based on the dynamic response sensitivity. The main advantage of proposed method is inclusion of an analytical method to augment the accuracy and speed of the solution. Moving mass is a model which takes into account the inertia effects of the vehicle. This interaction model is a time varying system and proposed method is capable of detecting damage in this variable system. Robustness of proposed method is illustrated by correctly detection of the location and extension of predetermined single, multiple and random damages in all ranges of speed and mass ratio of moving vehicle. A comparison study of common sensitivity and proposed method confirms its efficiency and performance improvement in sensitivity-based damage detection methods. Various sources of errors including the effects of measurement noise and initial assumption error in stability of method are also discussed.

This paper presents a numerical solution for the thick cylinders made of functionally graded materials (FGMs) with a constant Poisson's ratio and an arbitrary Young's modulus. We define two fundamental solutions which are derived from an ordinary differential equation under two particular initial boundary conditions. In addition, for the single layer case, we can define the transfer matrix N. The matrix gives a relation between the values of stress and displacement at the interior and exterior points. By using the assumed boundary condition and the transfer matrix, we can obtain the final solution. The transfer matrix method also provides an effective way for the solution of multiply layered cylinder. Finally, a lot of numerical examples are present.

Shape memory alloys (SMA) exhibit superelasticity which refers to the capability of entirely recovering large deformation upon removal of applied forces and dissipating input energy during the cyclic loading reversals when the environment is above the austenite finish temperature. This property is increasingly favored by the earthquake engineering community, which is currently developing resilient structures with prompt recovery and affordable repair cost after earthquakes. Compared with the other SMAs, NiTi SMAs are widely deemed as the most promising candidate in earthquake engineering. This paper contributes to evaluate the seismic performance of properly designed concentrically braced frames (CBFs) equipped with NiTi SMA braces under earthquake ground motions corresponding to frequently-occurred, design-basis and maximum-considered earthquakes. An ad hoc seismic design approach that was previously developed for structures with idealized SMAs was introduced to size the building members, by explicitly considering the strain hardening characteristics of NiTi SMA particularly. The design procedure was conducted to compliant with a suite of ground motions associated with the hazard level of design-basis earthquake. A total of four six-story CBFs were designed by setting different ductility demands for SMA braces while designating with a same interstory drift target for the structural systems. The analytical results show that all the designed frames successfully met the prescribed seismic performance objectives, including targeted maximum interstory drift, uniform deformation demand over building height, eliminated residual deformation, controlled floor acceleration, and slight damage in the main frame. In addition, this study indicates that the strain hardening behavior does not necessarily impose undesirable impact on the global seismic performance of CBFs with SMA braces.

This article presents a finite element (FE) model to assess the free vibration and static response of a functionally graded skew magneto-electro-elastic (FGSMEE) plate. Through the thickness material grading of FGSMEE plate is achieved using power law distribution. The coupled constitutive equations along with the total potential energy approach are used to develop the FE model of FGSMEE plate. The transformation matrix is utilized in bringing out the element matrix corresponding to the global axis to a local axis along the skew edges to specify proper boundary conditions. The effect of skew angle on the natural frequency of an FGSMEE plate is analysed. Further, the study includes the evaluation of the static behavior of FGSMEE plate for various skew angles. The influence of skew angle on the primary quantities such as displacements, electric potential, and magnetic potential, and secondary quantities such as stresses, electric displacement and magnetic induction is studied in detail. In addition, the effect of power-law gradient, thickness ratio, boundary conditions and aspect ratio on the free vibration and static response characteristics of FGSMEE plate has been investigated.

The main purpose of this paper is to predict missing absolute out-of-plane displacements and failure limits of infill walls by artificial neural network (ANN) models. For this purpose, two shake table experiments are performed. These experiments are conducted on a 1:1 scale one-bay one-story reinforced concrete frame (RCF) with an infill wall. One of the experimental models is composed of unreinforced brick model (URB) enclosures with an RCF and other is composed of an infill wall with bed joint reinforcement (BJR) enclosures with an RCF. An artificial earthquake load is applied with four acceleration levels to the URB model and with five acceleration levels to the BJR model. After a certain acceleration level, the accelerometers are detached from the wall to prevent damage to them. The removal of these instruments results in missing data. The missing absolute maximum out-of-plane displacements are predicted with ANN models. Failure of the infill wall in the out-of-plane direction is also predicted at the 0.79 g acceleration level. An accuracy of 99% is obtained for the available data. In addition, a benchmark analysis with multiple regression is performed. This study validates that the ANN-based procedure estimates missing experimental data more accurately than multiple regression models.