This paper presents an efficient method for updating the structural finite element model. Model updating is performed through minimizing the difference between the recorded acceleration of a real damaged structure and a hypothetical damaged one. This is performed by updating physical parameters (module of elasticity in this study) in each step using iterative process of modified nonlinear conjugate gradient (M-NCG) and modified Broyden-Fletcher-Goldfarb-Shanno algorithm (M-BFGS) separately. These algorithms are based on sensitivity analysis and provide a solution for nonlinear damage detection problem. Three illustrative test examples are considered to assess the performance of the proposed method. Finally, it is demonstrated that the proposed method is satisfactory for detecting the location and ratio of structural damage in presence of noise.

We have previously demonstrated a microfluidic elastomer, which changes apparent color and could have potential applications in smart windows. The practical use of such functional microfluidic systems requires rapid and uniform fluid displacement throughout the channel network with minimal amount of liquid supply. The goal of this simulation study is to design various microfluidic networks for similar applications including, but not limited to, the color-switching windows and compare the liquid displacement speed and efficiency of the designs. We numerically simulate and analyze the liquid displacement in the microfluidic networks with serpentine, parallel and lattice channel configurations, as well as their modified versions with wide or tapered distributor and collector channels. The data are analyzed on the basis of numerical criteria defined to evaluate the performance of the corresponding functional systems. We found that the lattice channel network geometry with the tapered distributors and collectors provides most rapid and uniform fluid displacement with minimum liquid waste. The simulation results could give an important guideline for efficient liquid supply/displacement in emerging functional systems with embedded microfluidic networks.

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

The main purpose of this paper is to study the effects of initial stress, gravity, anisotropy and porosity on the propagation of shear wave (SH-waves) in a fiber-reinforced layer placed over a porous media. The frequency equations in a closed form have been derived for SH-waves by applying suitable boundary conditions. The frequency equations have been expanded and approximated up to $2^{nd}$ order of Whittaker's function. It has been observed that the SH-wave velocity decreases as width of fiber-reinforced layer increases. However, with the increase of initial stress, gravity parameter and porosity, the phase velocity increases. The results obtained are in perfect agreement with the standard results investigated by other relevant researchers.

In this paper, the effects of mass eccentricity of superstructure as well as stiffness eccentricity of isolators on the amplification of seismic responses of base-isolated structures are investigated by using mathematical near-fault pulse models. Superstructures with 3, 6 and 9 stories and aspect ratios equal to 1, 2 and 3 are mounted on a reasonable variety of Triple Concave Friction Pendulum (TCFP) bearings considering different period and damping ratio. Three-dimensional linear superstructure mounted on nonlinear isolators are subjected to simplified pulses including fling step and forward directivity while various pulse period ($T_p$) and Peak Ground Velocity (PGV) amounts as two crucial parameters of these pulses are scrutinized. Maximum isolator displacement and base shear as well as peak superstructure acceleration and drift are selected as the main engineering demand parameters. The results indicate that the torsional intensification of different demand parameters caused by superstructure mass eccentricity is more significant than isolator stiffness eccentricity. The torsion due to mass eccentricity has intensified the base shear of asymmetric 6-story model 2.55 times comparing to symmetric one. In similar circumstances, the isolator displacement and roof acceleration are increased 49 and 116 percent respectively in the presence of mass eccentricity. Furthermore, it is demonstrated that torsional effects of mass eccentricity can force the drift to reach the allowable limit of ASCE 7 standard in the presence of forward directivity pulses.

Recent studies integrating vibration control and structural health monitoring (SHM) use control devices and control algorithms to enable system identification and damage detection. In this study real-time SHM is used to enhance structural vibration control and reduce damage. A newly proposed control algorithm, including integrated real-time SHM and semi-active control strategy, is presented to mitigate both damage and seismic response of the main structure under strong seismic ground motion. The semi-active independently variable stiffness (SAIVS) device is used as semi-active control device in this investigation. The proper stiffness of SAIVS device is obtained using a new developed semi-active control algorithm based on real-time damage tracking of structure by damage detection algorithm based on identified system Markov parameters (DDA/ISMP) method. A three bay five story steel braced frame structure, which is equipped with one SAIVS device at each story, is employed to illustrate the efficiency of the proposed algorithm. The obtained results show that the proposed control algorithm could significantly decrease damage in most parts of the structure. Also, the dynamic response of the structure is effectively reduced by using the proposed control algorithm during four strong earthquakes. In comparison to passive on and off cases, the results demonstrate that the performance of the proposed control algorithm in decreasing both damage and dynamic responses of structure is significantly enhanced than the passive cases. Furthermore, from the energy consumption point of view the maximum and the cumulative control force in the proposed control algorithm is less than the passive-on case, considerably.

Nowadays, there are two classes of methods for damage detection in structures consisting of static and dynamic. The dynamic methods are based on studying the changes in structure's dynamic characteristics. The theoretical basis of this method is that damage causes changes in dynamic characteristics of structures. The dynamic methods are divided into two categories: signal based and modal based. The modal based methods utilize the modal properties consisting of natural frequencies, modal damping and mode shapes. As the modal properties are sensitive to changes in the structure, these can be used for detecting the damages. In this study, using dynamic method and modal based approach (natural frequencies and mode shapes), the objective function is formulated. Then, detection of damages of truss structures is addressed by using Simplified Dolphin Echolocation algorithm and solving inverse optimization problem. Many scenarios are used to simulate the damages. To demonstrate the ability of the algorithm, different truss structures with several multiple elements scenarios are tested using a few runs. The influence of the two different levels of noise in the modal data for these scenarios is also considered. The last example of this article is investigated using a different mutation. This mutation obtains the exact answer with fewer loops and population by limited computational effort.

Two novel semi-active control methods for a seismically excited nonlinear benchmark building equipped with magnetorheological dampers are presented and evaluated in this paper. While a primary controller is designed to estimate the optimal control force of a magnetorheological (MR) damper, the required voltage input for the damper to produce such desired control force is achieved using two different methods. The first technique uses an optimal compact Takagi-Sugeno-Kang (TSK) fuzzy inverse model of MR damper to predict the required voltage to actuate the MR dampers (TSKFInv). The other voltage regulator introduced here works based on the maximum and minimum capacities of MR damper at each time-step (MaxMin). Both semi-active algorithms developed here, use acceleration feedback only. The results demonstrate that both TSKFInv and MaxMin algorithms are quite effective in seismic response reduction for wide range of motions from moderate to severe seismic events, compared with the passive systems and performs better than original and Modified clipped optimal controller systems, known as COC and MCOC.

In this research, the nonlinear free vibration analysis of boron-nitride micro ribbon (BNMR) on the Pasternak elastic foundation under electrical, mechanical and thermal loadings using modified strain gradient theory (MSGT) is studied. Employing the von $K{\acute{a}}rm{\acute{a}}n$ nonlinear geometry theory, the nonlinear equations of motion for the graphene micro ribbon (GMR) using Euler-Bernoulli beam model with considering attached mass and size effects based on Hamilton's principle is obtained. These equations are converted into the nonlinear ordinary differential equations by elimination of the time variable using Kantorovich time-averaging method. To determine nonlinear frequency of GMR under various boundary conditions, and considering mass effect, differential quadrature element method (DQEM) is used. Based on modified strain MSGT, the results of the current model are compared with the obtained results by classical and modified couple stress theories (CT and MCST). Furthermore, the effect of various parameters such as material length scale parameter, attached mass, temperature change, piezoelectric coefficient, two parameters of elastic foundations on the natural frequencies of BNMR is investigated. The results show that for all boundary conditions, by increasing the mass intensity in a fixed position, the linear and nonlinear natural frequency of the GMR reduces. In addition, with increasing of material length scale parameter, the frequency ratio decreases. This results can be used to design and control nano/micro devices and nano electronics to avoid resonance phenomenon.

Taking advantage of the high sensitivity and long-distance detection capability of acoustic emission (AE) technique, this paper focuses on the crack detection in rail head, which is one of the most vulnerable parts of rail track. The AE source location and noise cancellation were studied on the basis of practical rail profile, material and operational noise. In order to simulate the actual AE events of rail head cracks, field tests were carried out to acquire the AE waves induced by pencil lead break (PLB) and operational noise of the railway system. Wavelet transform (WT) was first utilized to investigate the time-frequency characteristics and dispersion phenomena of AE waves. Here, the optimal mother wavelet was selected by minimizing the Shannon entropy of wavelet coefficients. Regarding the obvious dispersion of AE waves propagating along the rail head and the high operational noise, the wavelet transform-based modal analysis location (WTMAL) method was then proposed to locate the AE sources (i.e. simulated cracks) respectively for the PLB-induced AE signals with and without operational noise. For those AE signals inundated with operational noise, the Hilbert transform (HT)-based noise cancellation method was employed to improve the signal-to-noise ratio (SNR). Finally, the experimental results demonstrated that the proposed crack detection strategy could locate PLB-simulated AE sources effectively in the rail head even at high operational noise level, highlighting its potential for field application.