Shape memory alloys (SMAs) exhibit superelasticity given the ambient temperature is above the austenite finish temperature threshold, the magnitude of which significantly depends on the metal ingredients though. For the monocrystalline CuAlBe SMAs, their superelasticity was found being maintained even when the ambient temperature is down to $-40^{\circ}C$. Thus this makes such SMAs particularly favorable for outdoor seismic applications, such as the framed structures located in cold regions with substantial temperature oscillation. Due to the thermo-mechanical coupling mechanism, the hysteretic properties of SMAs vary with temperature change, primarily including altered material strength and different damping. Thus, this study adopted the monocrystalline CuAlBe SMAs as the kernel component of the SMA braces. To quantify the seismic response characteristics at various temperatures, a wide temperature range from -40 to $40^{\circ}C$ are considered. The middle temperature, $0^{\circ}C$, is artificially selected to be the reference temperature in the performance comparisons, as well the corresponding material properties are used in the seismic design procedure. Both single-degree-of-freedom systems and a six-story braced frame were numerically analyzed by subjecting them to a suite of earthquake ground motions corresponding to the design basis hazard level. To the frame structures, the analytical results show that temperature variation generates minor influence on deformation and energy demands, whereas low temperatures help to reduce acceleration demands. Further, attributed to the excellent superelasticity of the monocrystalline CuAlBe SMAs, the frames successfully maintain recentering capability without leaving residual deformation upon considered earthquakes, even when the temperature is down to $-40^{\circ}C$.

Sensors and systems in Civionics technology play an important role for continuously facilitating real-time structure monitoring systems by detecting and locating damage to or degradation of structures. An advanced materials, design processes, long-term sensing ability of sensors, electromagnetic interference, sensor placement techniques, data acquisition and computation, temperature, harsh environments, and energy consumption are important issues related to sensors for structural health monitoring (SHM). This paper provides a comprehensive survey of various sensor technologies, sensor classes and sensor networks in Civionics research for existing SHM systems. The detailed classification of sensor categories, applications, networking features, ranges, sizes and energy consumptions are investigated, summarized, and tabulated along with corresponding key references. The current challenges facing typical sensors in Civionics research are illustrated with a brief discussion on the progress of SHM in future applications. The purpose of this review is to discuss all the types of sensors and systems used in SHM research to provide a sufficient background on the challenges and problems in optimizing design techniques and understanding infrastructure performance, behavior and current condition. It is observed that the most important factors determining the quality of sensors and systems and their reliability are the long-term sensing ability, data rate, types of processors, size, power consumption, operation frequency, etc. This review will hopefully lead to increased efforts toward the development of low-powered, highly efficient, high data rate, reliable sensors and systems for SHM.

This article presents an analysis into the nonlinear forced vibration of a micro cylindrical shell reinforced by carbon nanotubes (CNTs) with considering agglomeration effects. The structure is subjected to magnetic field and transverse harmonic mechanical load. Mindlin theory is employed to model the structure and the strain gradient theory (SGT) is also used to capture the size effect. Mori-Tanaka approach is used to estimate the equivalent material properties of the nanocomposite cylindrical shell and consider the CNTs agglomeration effect. The motion equations are derived using Hamilton's principle and the differential quadrature method (DQM) is employed to solve them for obtaining nonlinear frequency response of the cylindrical shells. The effect of different parameters including magnetic field, CNTs volume percent and agglomeration effect, boundary conditions, size effect and length to thickness ratio on the nonlinear forced vibrational characteristic of the of the system is studied. Numerical results indicate that by enhancing the CNTs volume percent, the amplitude of system decreases while considering the CNTs agglomeration effect has an inverse effect.

This paper investigates the operation of the $H_{\infty}$ static output-feedback controller to reduce dynamic responses under seismic excitation on the five-story and benchmark 20 story building with parametric uncertainties. Linear matrix inequality (LMI) control theory is applied in this system and then to achieve the desired LMI formulations, some transformations of the LMI variables is used. Conversely uncertainties due to material properties, environmental loads such as earthquake and wind hazards make the uncertain system. This problem and its effects are studied in this research. Also to decrease the transition of large amount of data between sensors and controller, avoiding the disruption of whole control system and economy problems, the operation of the decentralized controllers is investigated in this paper. For this purpose the comparison between the performance of the centralized, fully decentralized and partial decentralized controllers in uncoupled and coupled cases is performed. Also, the effect of the changing the number of stories in substructures is considered. Based on the numerical results, the used control algorithm is very robust against the parametric uncertainties and structural responses are decreased considerably in all the control cases but partial decentralized controller in coupled form gets the closest results to the centralized case. The results indicate the high applicability of the used control algorithm in the tall shear buildings to reduce the structural responses and its robustness against the uncertainties.

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

Computational Building Information Modeling (BIM) is an intelligent 3D model-based process that provides architecture, engineering, and construction professionals the insight to plan, design, construct, and manage buildings and infrastructure more efficiently. This paper aims at using BIM in Hospitals configurations protection. Infrastructure projects are classified as huge structural projects taking advantage of many resources such as finance, materials, human labor, facilities and time. Immense expenses in infrastructure programs should be allocated to estimating the expected results of these arrangements in domestic economy. Hence, the significance of feasibility studies is inevitable in project construction, in this way the necessity in promoting the strategies and using global contemporary technologies in the process of construction maintenance cannot be neglected. This paper aims at using the building information modeling in covering Imam Khomeini Hospital's equipment. First, the relationship between hospital constructions maintenance and repairing, using the building information modeling, is demonstrated. Then, using library studies, the effective factors of constructions' repairing and maintenance were collected. Finally, the possibilities of adding these factors in Revit software, as one of the most applicable software within BIM is investigated and have been identified in some items, where either this software can enter or the software for supporting the repairing and maintenance phase lacks them. The results clearly indicated that the required graphical factors in construction information modeling can be identified and applied successfully.

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

In this research the effect of bedding layer angle and bedding layer thickness on the shear failure mechanism of concrete has been investigated using PFC3D. For this purpose, firstly calibration of PFC3d was performed using Brazilian tensile strength. Secondly shear test was performed on the bedding layer. Thickness of layers were 5 mm, 10 mm and 20 mm. in each thickness layer, layer angles changes from $0^{\circ}$ to $90^{\circ}$ with increment of $25^{\circ}$. Totally 15 model were simulated and tested by loading rate of 0.016 mm/s. The results shows that when layer angle is less than $50^{\circ}$, tensile cracks initiates between the layers and propagate till coalesce with model boundary. Its trace is too high. With increasing the layer angle, less layer mobilize in failure process. Also the failure trace is very short. It's to be note that number of cracks decrease with increasing the layer thickness. The minimum shear test strength was occurred when layer angle is more than $50^{\circ}$. The maximum value occurred in $0^{\circ}$. Also, the shear test tensile strength was increased by increasing the layer thickness.

Boundary effect and the noise robustness are the two crucial aspects which affect the effectiveness of the damage localization based on the mode shape measurements. To overcome the boundary effect problem and enhance the noise robustness in damage detection, a simple damage localization method is proposed based on the Singular Value Decomposition (SVD) for the mode shape of composite plates. In the proposed method, the boundary effect problem is addressed by the decomposition and reconstruction of mode shape, and the noise robustness in enhanced by the noise filtering during the decomposition and reconstruction process. Numerical validations are performed on plate-like structures for various damage and boundary scenarios. Validations show that the proposed method is accurate and effective in the damage detection for the two-dimensional structures.

This paper outlines a computational procedure for the effective merging of diverse sensor measurements, displacement and acceleration signals in particular, in order to successfully monitor and simulate the current health condition of civil structures under dynamic loadings. In particular, it investigates a Kalman Filter implementation for the Heterogeneous Data Fusion of displacement and acceleration response signals of a structural system toward dynamic identification purposes. The procedure is perspectively aimed at enhancing extensive remote displacement measurements (commonly affected by high noise), by possibly integrating them with a few standard acceleration measurements (considered instead as noise-free or corrupted by slight noise only). Within the data fusion analysis, a Kalman Filter algorithm is implemented and its effectiveness in improving noise-corrupted displacement measurements is investigated. The performance of the filter is assessed based on the RMS error between the original (noise-free, numerically-determined) displacement signal and the Kalman Filter displacement estimate, and on the structural modal parameters (natural frequencies) that can be extracted from displacement signals, refined through the combined use of displacement and acceleration recordings, through inverse analysis algorithms for output-only modal dynamics identification, based on displacements.