In recent years, the number of tall buildings being constructed has been rapidly increasing worldwide. Some buildings have been constructed with triangular exterior structural members, known as diagrid systems, which have been developed for structural effectiveness and architectural aesthetics. Although more buildings with diagrid systems have been proposed and have been entered in design competitions, few studies have been carried out on the behavior of diagrid systems or diagrid nodes. Most important, the fabrication of diagrid nodes has been very difficult due to the relatively complex geometry and costly connections of the diagrid system. In this study, a new type of diagrid structural system node was proposed and tested cyclically for lateral loads such as earthquake and wind. Based on the test results, the cyclic performance for diagrid nodes is discussed with an emphasis on the hysteresis characteristics, welding methods, and failure modes.

In the Fourth Industrial Revolution, research and development of application technologies that combine high-tech technologies have been actively conducted. Building information modeling (BIM) technology using advanced equipment is considered promising for future construction projects. In particular, using a 3D laser scanner, LIDAR is expected to be a solution for future building safety inspections. This work proposes a new method for evaluating building stability using a 3D laser scanner. In this study, an underground parking lot was analyzed using a 3D laser scanner. Further, structural analysis was performed using the finite element method (FEM) by applying the figure and geometry data acquired from the laser scan. This process includes surveying the modeled point cloud data of the scanned building, such as identifying the relative deflection of the floor slab, and the sectional shape and inclination of the column. Consequently, safety diagnosis was performed using the original evaluation criteria. This confirms that it is precise and efficient to use a 3D laser scanner for building stability assessment. This paper presents a digital point cloud-based approach using a 3D laser scanner to evaluate the stability of buildings.

Concrete cracks can threaten the usability of structures and degrade the aesthetics of buildings. Furthermore, minor cracks can develop into large-scale cracks that may lead to structural failure when exposed to excessive external loads. In addition, the concrete crack width and depth should be precisely measured to investigate the effects of concrete cracks on the stability of structures. Thus, a nondestructive and noncontact testing method was introduced for detecting concrete crack depth using thermal images and machine learning. The thermal images of the cracked specimens were obtained using a constant test setup for several months under daylight conditions, which provided sufficient heat for measuring the temperature distributions of the specimens, with recording parameters such as air temperature, humidity, and illuminance. From the thermal images, the crack and surface temperatures were obtained depending on the crack widths and depths using the parameters. Four machine-learning algorithms (decision tree, extremely randomized tree, gradient boosting, and AdaBoost) were selected, and the results of crack depth prediction were compared to identify the best algorithm. In addition, data bias analysis using principal component analysis, singular value decomposition, and independent component analysis were conducted to evaluate the efficiency of machine learning.

The development of unmanned aerial vehicles (UAVs) is expected to become one of the most commercialized research areas in the world over the next decade. Globally, unmanned aircraft have been increasingly used for safety surveillance in the construction industry and civil engineering fields. This paper presents an aerial image-based approach using UAVs to inspect cracks and deformations in buildings. A state-of-the-art safety evaluation method termed SMART SKY EYE (Smart building safety assessment system using UAV) is introduced; this system utilizes an unmanned airplane equipped with a thermal camera and programmed with various surveying efficiency improvement methods, such as thermography, machine-learning algorithms, and 3D point cloud modeling. Using this method, crack maps, crack depths, and the deformations of structures can be obtained. Error rates are compared between the proposed and conventional methods.

Compared to concrete or mortar-filled Buckling-Restrained Braces (BRBs), all-steel BRBs provide weight and fabrication time reductions. In particular, all-steel buckling braces with H-section cores are gaining attention in cases where large axial strength is required. In this paper, an all-steel BRB, called NOVEL (Noise, CO₂ emission, Vibration, Energy dissipation and Labor), is presented. It comprises an H-section core encased in a square casing, and its behavior was studied through full-scale subassembly and brace tests, followed by a finite element parametric study. Two failure modes were observed: global buckling and flange buckling of the H-section core, which occurred in test specimens with P_cr/P_y ratios of 1.68 and 4.91, respectively. Global buckling occurred when the maximum moment in the casing reached its yielding moment, although the test specimens had sufficient stiffness to prevent global buckling. Failure by core flange buckling occurred at a core strain of 1.2%. The finite element parametric study indicated that adjusting the width-to-thickness ratio of the core flange is more feasible than stiffening the flange or adjusting the unconstrained-length end stiffeners. The value of 5.06 was the minimum flange slenderness ratio that provided a stable hysteresis to the end of the loading protocol of the American Institute of Steel Construction standard.