Continuous rotating SMA actuators require motion conversion mechanisms, so their structure is relatively complex and difficult to realize the miniaturization. Here, a new type of continuous rotating actuator driven by SMA is proposed. It combines the movable tooth drive with SMA drive. The structure and working principle of the integrated movable tooth drive system is introduced. The equations of temperature, stress and strain of memory alloy wires, and the output torque of drive system are given. Using these equations, the temperature, the output forces of the SMA wires, and output torque of the drive system are studied. Results show that the compact drive system could give large output torque. To obtain large output torque plus small fluctuation, large eccentricity and small diameter of the SMA wire should be taken. Combined application of ventilation cooling and high current can increase the rotary speed of the drive system.

Structural fuses are made up from oriented steel plates to be used to resist seismic force with shear loading resistance capabilities. The damage and excessive inelastic deformations are concentrated in structural fuses to avoid any issues for the rest of the surrounding elements. Recently developed fuse plates are designed with engineered cutouts leaving flexural or shear links with controlled yielding features. A promising type of link is proposed to align better bending strength along the length of the link with the demand moment diagram is a butterfly-shaped link. Previously, the design methodologies are purely based on the flexural stresses, or shear stresses only, which overestimate the dampers capability for resisting against the applied loadings. This study is specifically focused on the optimized design methodologies for commonly used butterfly-shaped dampers. Numerous studies have shown that the stresses are not uniformly distributed along the length of the dampers; hence, the design methodology and the effective implementation of the steel need revisions and improvements. In this study, the effect of shear and flexural stresses on the behavior of butterfly-shaped links are computationally investigated. The mathematical models based on von-Mises yielding criteria are initially developed and the optimized design methodology is proposed based on the yielding criterion. The optimized design is refined and investigated with the aid of computational investigations in the next step. The proposed design methodology meets the needs of optimized design concepts for butterfly-shaped dampers considering the uniform stress distribution and efficient use of steel.

This work resumes a research that proposes the use of the technique based on the dissipation energy of the shape memory alloy (SMA) ties. It focuses principally on the assessment of the effectiveness of the use of these smart materials on displacements, accelerations and the stresses of the minaret of the great mosque of Ajloun in Jordan. The 3-D finite element model of the minaret is performed by the ANSYS software. First of all, the proposed model is calibrated and validated according to the experimental results gathered from ambient vibration testing results. Then, a nonlinear transient analysis is considered, when the El-Centro earthquake is used as the input signal. Different simulating cases concerning the location, number and type of SMA devices are proposed in order to see their influence on the seismic response of the minaret. Hence, the results confirm the effectiveness of the proposed SMA device.

A new methodology for mitigation of the wheel squealing is proposed and investigated based on the dithering control. The idea can be applied in railway lines particularly in urban areas. The idea is clearly presented, and applied to a validated model. A full-scale model including the vehicle, curved track and wheel/rail contact is developed in the time domain to analyze the possibility and level of wheel squeal noise. Comparing the numerical results with a field test, the model is validated in different levels namely i) occurrence, ii) squealing frequency and iii) noise level. Two different approaches are proposed a) dithering of the wheel with piezoelectric patches and b) dithering of the rail with piezoelectric stacks. The noise level as well as the wheel responses is compared after applying the control strategy. A parametric study is carried out and effect of the dithering voltage and frequency on the squealing noise is investigated. It is found that both the strategies perform quite effectively within the saturating threshold of piezoelectric actuators.

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

A study concerning the strength of brittle materials is presented in this paper. The failure behavior was investigated examining the plane of the crack after the failure and comparing the results obtained with those deriving from the fracture mechanics theory. Although the proposed methods are valid in general for brittle materials, the experiment was performed on glass because the results are more significant for this. Glass elements of various sizes and different edge finishes were subjected to bending tests until collapsing. The bending results were studied in terms of failure load and energy dissipation, and the fracture surfaces were examined by means of microscopic analysis, in which the depth of the flaw and the mirror radius of the fracture were measured and the strength was calculated. These results agreed with those obtained from the fracture mechanics analysis.

This research deals with the vibration analysis of embedded smart concrete plate reinforced by zinc oxide (ZnO). The effective material properties of structure are considered based on mixture rule. The elastic medium is simulated by orthotropic visco-Pasternak medium. The motion equations are derived applying Sinusoidal shear deformation theory (SSDT). The differential quadrature (DQ) method is applied for calculating frequency of structure. The effects of different parameters such as volume percent of ZnO, boundary conditions and geometrical parameters on the frequency of system are shown. The results are compared with other published works in the literature. Results indicate that the ZnO have an important role in frequency of structure.

Applying more features gives us better accuracy in modeling; however, increasing the inputs causes the curse of dimensions. In this paper, a new structure has been proposed for fault detecting and identifying (FDI) of high-dimensional systems. This structure consist of two structure. The first part includes Auto-Encoders (AE) as Deep Neural Networks (DNNs) to produce feature engineering process and summarize the features. The second part consists of the Local Model Networks (LMNs) with LOcally LInear MOdel Tree (LOLIMOT) algorithm to model outputs (multiple models). The fault detection is based on these multiple models. Hence the residuals generated by comparing the system output and multiple models have been used to alarm the faults. To show the effectiveness of the proposed structure, it is tested on single-shaft industrial gas turbine prototype model. Finally, a brief comparison between the simulated results and several related works is presented and the well performance of the proposed structure has been illustrated.