A high-performance electrochromic-energy storage device (EESD) is developed, which successfully realizes the multifunctional combination of electrochromism and energy storage by constructing tungsten trioxide monohydrate (WO·HO) nanosheets and Prussian white (PW) film as asymmetric electrodes. The EESD presents excellent electrochromic properties of broad optical modulation (61.7%), ultrafast response speed (1.84/1.95 s), and great coloration efficiency (139.4 cm C). In particular, remarkable cyclic stability (sustaining 82.5% of its initial optical modulation after 2500 cycles as an electrochromic device, almost fully maintaining its capacitance after 1000 cycles as an energy storage device) is achieved. The EESD is also able to visually detect the energy storage level via reversible and fast color changes. Moreover, the EESD can be combined with commercial solar cells to constitute an intelligent operating system in the architectures, which would realize the adjustment of indoor sunlight and the improvement of physical comfort totally by the rational utilization of solar energy without additional electricity. Besides, a scaled-up EESD (10 × 11 cm) is further fabricated as a prototype. Such promising EESD shows huge potential in practically serving as electrochromic smart windows and energy storage devices.

The intelligent crack detection method is an important guarantee for the realization of intelligent operation and maintenance, and it is of great significance to traffic safety. In recent years, the recognition of road pavement cracks based on computer vision has attracted increasing attention. With the technological breakthroughs of general deep learning algorithms in recent years, detection algorithms based on deep learning and convolutional neural networks have achieved better results in the field of crack recognition. In this paper, deep learning is investigated to intelligently detect road cracks, and Faster R-CNN and Mask R-CNN are compared and analyzed. The results show that the joint training strategy is very effective, and we are able to ensure that both Faster R-CNN and Mask R-CNN complete the crack detection task when trained with only 130+ images and can outperform YOLOv3. However, the joint training strategy causes a degradation in the effectiveness of the bounding box detected by Mask R-CNN.

No abstract

No abstract

Terrestrial laser scanning technology (TLS) is a new technique for quickly getting three-dimensional information. In this paper we research the health assessment of concrete structures with a Finite Element Method (FEM) model based on TLS. The goal focuses on the benefits of 3D TLS in the generation and calibration of FEM models, in order to build a convenient, efficient and intelligent model which can be widely used for the detection and assessment of bridges, buildings, subways and other objects. After comparing the finite element simulation with surface-based measurement data from TLS, the FEM model is determined to be acceptable with an error of less than 5%. The benefit of TLS lies mainly in the possibility of a surface-based validation of results predicted by the FEM model.

No abstract

The technique of digital image correlation (DIC), which has been widely used for noncontact deformation measurements in both the scientific and engineering fields, is greatly affected by the quality of speckle patterns in terms of its performance. This study was concerned with the optimization of the digital speckle pattern (DSP) for DIC in consideration of both the accuracy and efficiency. The root-mean-square error of the inverse compositional Gauss-Newton algorithm and the average number of iterations were used as quality metrics. Moreover, the influence of subset sizes and the noise level of images, which are the basic parameters in the quality assessment formulations, were also considered. The simulated binary speckle patterns were first compared with the Gaussian speckle patterns and captured DSPs. Both the single-radius and multi-radius DSPs were optimized. Experimental tests and analyses were conducted to obtain the optimized and recommended DSP. The vector diagram of the optimized speckle pattern was also uploaded as reference.

No abstract