To further improve the precision and efficiency of structural health monitoring technology and the theory of large-scale structures, full-field non-contact structural geometry morphology monitoring is expected to be a breakthrough technology in structural safety state monitoring and digital twins, owing to its economic, credible, high frequency, and holographic advantages. This study validates a proposed holographic visual sensor and algorithms in a computer-vision-based full-field non-contact displacement and vibration measurement. Using an automatic camera patrol experimental device, original segmental dynamic and static video monitoring data of a model bridge under various damage/activities were collected. According to the temporal and spatial characteristics of the series data, the holographic geometric morphology tracking algorithm was introduced. Additionally, the feature points set of the structural holography geometry and the holography feature contours were established. Experimental results show that the holographic visual sensor and the proposed algorithms can extract an accurate holographic full-field displacement signal, and factually and sensitively accomplish vibration measurement, while accurately reflecting the real change in structural properties under various damage/action conditions. The proposed method can serve as a foundation for further research on digital twins for large-scale structures, structural condition assessment, and intelligent damage identification.

Computer vision is becoming one of the most popular remote-sensing techniques and has been used widely in displacement monitoring and damage identification of in-service bridges. Nevertheless, several obstacles, including limited sampling rate, insufficient resolution for remote measurement, and error induced by camera tilting, restrict the application of vision-based approaches in structural health monitoring (SHM). The combination of a traditional SHM system and a modern remote-sensing technique can significantly improve the accuracy and reliability of the monitoring system. To make full use of data collected in the traditional SHM system and computer vision technique and overcome their shortcomings, we presented an improved bridge displacement estimation approach for SHM purposes by fusing camera-based and acceleration measurements. First, we estimated the scaling factor, which transfers pixel displacement to real displacement under tilt photogrammetry, by the acceleration reconstructed and camera-based displacements in the same frequency band without the actual size of the structure or the measurement parameters. Then, we extracted the low-frequency displacement from the vision-based measurement, and we fused the high-frequency displacement that was reconstructed from the acceleration measurement to achieve high-accuracy displacement estimation. The efficiency of this method was validated through dynamic load tests on a suspension model bridge in the laboratory and field tests on a highway and subway cable-stayed bridge.

For the numerical simulation of flow systems with various complex components, the traditional one-dimensional (1D) network method has its comparative advantage in time consuming and the CFD method has its absolute advantage in the detailed flow capturing. The proper coupling of the advantages of different dimensional methods can strike balance well between time cost and accuracy and then significantly decrease the whole design cycle for the flow systems in modern machines. A novel multi-fidelity coupled simulation method with numerical zooming is developed for flow systems. This method focuses on the integration of one-, two- and three-dimensional codes for various components. Coupled iterative process for the different dimensional simulation cycles of sub-systems is performed until the concerned flow variables of the whole system achieve convergence. Numerical zooming is employed to update boundary data of components with different dimensionalities. Based on this method, a highly automatic, multi-discipline computing environment with integrated zooming is developed. The numerical results of Y-Junction and the air system of a jet engine are presented to verify the solution method. They indicate that this type of multi-fidelity simulation method can greatly improve the prediction capability for the flow systems

Bridge displacement is an important part of safety evaluations. Currently, bridge displacement monitoring uses only a few measurement points, making it difficult to evaluate safety. To address this problem, we propose a multi-point displacement synchronous monitoring method. The structural surface has abundant natural texture features, so we use the feature points of the structural surface as the displacement measurement points and propose a feature point displacement calculation method. Furthermore, we conduct experiments on a beam in the laboratory and obtain the beam’s multi-point displacement monitoring results. The monitoring results show that the displacement of some feature points is mismatched. We propose the use of the structural deflection curve to eliminate the feature point displacement mismatches. This method uses the maximum rotation angle of the deflection curve to eliminate displacement mismatches. The results indicate that it is effective to eliminate displacement mismatches in simple structures, such as simply supported beams. Finally, we obtain the test beam’s multi-point displacement synchronous monitoring results. Compared with the 3D laser scanning measurement method, the maximum error of the monitoring results is 8.70%. Research shows that the main reason for the monitoring error is image noise, and the noise interference problem due to its application in practical bridges requires further investigation. Compared with traditional displacement monitoring, this method has significant economic, efficiency, and data integrity advantages. The method has application prospects for multi-point displacement monitoring of simple structures, such as simply supported beams.

A precast concrete deck-steel beam-connection concrete (PCSC) connector using ultra-high-performance concrete (UHPC) as post-cast concrete has been proposed to enable rapid on-site construction of assembled composite bridges. This paper aims to optimize the structure of PCSC connectors using the finite element (FE) model to maximize material utilization and economic efficiency. A refined FE model comprising the bond degradation at the steel–UHPC interface was developed based on the push-out experimental results of PCSC connectors. The shear mechanism of the PCSC connectors was analyzed. Subsequently, parametric analyses were performed to investigate the effects of stud diameter, height, spacing, and concrete strength on the mechanical properties of PCSC connectors. The results indicate that the bond at the steel–connection concrete interface positively affects the shear bearing capacity and stiffness of the PCSC connectors. When UHPC was used as connection concrete, it improved the bearing capacity by about 20% and the shear stiffness of the stud by about 16% compared with normal concrete, but the ductility was 38% lower. It was also found that increasing the compressive strength of the connection concrete increased the shear strength of specimens. However, when the compressive strength of UHPC exceeded 130 MPa, the additional UHPC strength did not significantly enhance the shear performance of specimens. In order to ensure the effective restraint of the connection concrete to studs, it is recommended that the minimum width and height of the connection concrete (UHPC) be determined based on the minimum horizontal spacing and height of the studs. Specifically, the length-to-diameter ratio of studs is greater than or equal to 3.18, the horizontal spacing of studs can be at least 2.82 d, and the clear distance between the outer stud shank and the edge of the UHPC cannot be less than 30 mm. The results are expected to provide a reference for the engineering design of PCSC connectors and a reference for conventional stud connectors with UHPC.