Signs of functional loss due to the deterioration of structures are primarily identified from cracks occurring on the surface of structures, and continuous monitoring of structural cracks is essential for socially important structures. Recently, many structural crack monitoring technologies have been developed with the development of deep-learning artificial intelligence (AI). In this study, stacking ensemble learning was applied to predict the structural cracks more precisely. A semantic segmentation model was primarily used for crack detection using a deep learning AI model. We studied the crack-detection performance by training UNet, DeepLabV3, DeepLabV3+, DANet, and FCN-8s. Owing to the unsuitable crack segmentation performance of the FCN-8s, stacking ensemble learning was conducted with the remaining four models. Individual models yielded an intersection over union (IoU) score ranging from approximately 0.4 to 0.6 for the test dataset. However, when the metamodel completed with stacking ensemble learning was used, the IoU score was 0.74, indicating a high-performance improvement. A total of 1235 test images was acquired with drones on the sea bridge, and the stacking ensemble model showed an IoU of 0.5 or higher for 64.4% of the images.

Carbon-fiber-reinforced polymer (CFRP) cables have emerged as promising alternatives to conventional prestressing tendons because of their high tensile strength, excellent corrosion resistance, and low self-weight. Their use is particularly advantageous in infrastructure exposed to aggressive environments, such as chloride-induced corrosion, where improved durability and reduced maintenance are critically required. In this study, a 10 mm diameter round-bar-type CFRP cable was developed using a pultrusion process, and its applicability to structural systems was comprehensively evaluated through material testing and field implementation. Mechanical performance was assessed through tensile, relaxation, and fatigue tests. The developed CFRP cable exhibited an average tensile strength of 3019 MPa and an elastic modulus of 176.9 GPa, demonstrating mechanical properties comparable to or better than those of conventional prestressing tendons. The final relaxation ratio was measured as 2.25%, satisfying the low-relaxation criterion specified in KS D 7002. In the fatigue test, the cable sustained 2,000,000 loading cycles under a stress range corresponding to 60–66% of the ultimate tensile strength without fracture or significant stiffness degradation, confirming its excellent fatigue durability. In addition, the developed CFRP cable was implemented in a cable-net structure to verify its constructability and structural applicability in practice. The field application confirmed that the lightweight CFRP cable enabled convenient transportation and installation, while stable prestress introduction was achieved using the same tensioning procedure as that for conventional steel cable systems. The results demonstrate the integrated feasibility of the developed CFRP cable in terms of both material performance and practical structural application. This study provides experimental evidence supporting the structural use of CFRP tendons and offers a technical basis for the future development of design provisions and broader infrastructure applications.

Carbon-fiber reinforced polymer (CFRP) tendons have attracted increasing attention as corrosion-resistant prestressing elements for prestressed concrete and cable-supported structures; however, their practical implementation requires reliable verification of long-term mechanical performance and anchorage reliability. In this study, a 9.5 mm pultruded CFRP tendon and compression-type anchorage system were developed and experimentally evaluated through relaxation, creep rupture, and fatigue tests. The tendon exhibited a tensile strength of 2501 MPa and an elastic modulus of 132.5 GPa. Relaxation tests were conducted at an initial load corresponding to 70% of the ultimate tensile capacity, and the measured relaxation loss after 1000 h was 1.02%. Based on logarithmic regression of the measured data, the relaxation loss at 1,000,000 h was estimated to be 2.11%; however, this value should be interpreted as an extrapolated long-term estimate rather than a directly verified result. Creep rupture tests performed at load ratios of 82.4–100.0% yielded an estimated 1,000,000 h creep rupture load ratio of approximately 80%, although the prediction is subject to uncertainty because of the limited number of specimens and scatter in rupture times. Fatigue tests indicated that the CFRP tendon–anchorage assembly maintained stable performance up to 2,000,000 cycles without measurable degradation in elastic stiffness under the adopted loading conditions. These results suggest that the developed CFRP tendon–anchorage system has promising potential for prestressing applications, while further long-term tests with a larger number of specimens are required to improve the statistical reliability of the extrapolated relaxation and creep rupture predictions.