A full-scale experimental test was conducted to analyze the composite behavior of insulated concrete sandwich wall panels (ICSWPs) subjected to wind pressure and suction. The experimental program was composed of three groups of ICSWP specimens, each with a different type of insulation and number of glass-fiber-reinforced polymer (GFRP) shear grids. The degree of composite action of each specimen was analyzed according to the load direction, type of the insulation, and number of GFRP shear grids by comparing the theoretical and experimental values. The failure modes of the ICSWPs were compared to investigate the effect of bonds according to the load direction and type of insulation. Bonds based on insulation absorptiveness were effective to result in the composite behavior of ICSWP under positive loading tests only, while bonds based on insulation surface roughness were effective under both positive and negative loading tests. Therefore, the composite behavior based on surface roughness can be applied to the calculation of the design strength of ICSWPs with continuous GFRP shear connectors.

Existing vision-based displacement sensors (VDSs) extract displacement data through changes in the movement of a target that is identified within the image using natural or artificial structure markers. A target-less vision-based displacement sensor (hereafter called “TVDS”) is proposed. It can extract displacement data without targets, which then serve as feature points in the image of the structure. The TVDS can extract and track the feature points without the target in the image through image convex hull optimization, which is done to adjust the threshold values and to optimize them so that they can have the same convex hull in every image frame and so that the center of the convex hull is the feature point. In addition, the pixel coordinates of the feature point can be converted to physical coordinates through a scaling factor map calculated based on the distance, angle, and focal length between the camera and target. The accuracy of the proposed scaling factor map was verified through an experiment in which the diameter of a circular marker was estimated. A white-noise excitation test was conducted, and the reliability of the displacement data obtained from the TVDS was analyzed by comparing the displacement data of the structure measured with a laser displacement sensor (LDS). The dynamic characteristics of the structure, such as the mode shape and natural frequency, were extracted using the obtained displacement data, and were compared with the numerical analysis results. TVDS yielded highly reliable displacement data and highly accurate dynamic characteristics, such as the natural frequency and mode shape of the structure. As the proposed TVDS can easily extract the displacement data even without artificial or natural markers, it has the advantage of extracting displacement data from any portion of the structure in the image.