• Wind and Structures
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• v.10 no.2
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• pp.121-133
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• 2007

To gain understanding of the applicability of carbon fiber reinforced polymer (CFRP) cable in cable-supported bridges, based on the Runyang Bridge and Jinsha Bridge, a suspension bridge using CFRP cables and a cable-stayed bridge using CFRP stay cables are schemed, in which the cable's cross-sectional area is determined by the principle of equivalent axial stiffness. Numerical investigations on the dynamic behavior, aerostatic and aerodynamic stability of the two bridges are conducted by 3D nonlinear analysis, and the effect of different cable materials on the wind resistance is discussed. The results show that as CFRP cables are used in cable-supported bridges, (1) structural natural frequencies are all increased, and particularly great increase of the torsional frequency occurs for suspension bridges; (2) under the static wind action, structural deformation is increased, however its aerostatic stability is basically remained the same as that of the case with steel cables; (3) for suspension bridge, its aerodynamic stability is superior to that of the case with steel cables, but for cable-stayed bridge, it is basically the same as that of the case with steel stay cables. Therefore as far as the wind resistance is considered, the use of CFRP cables in cable-supported bridges is feasible, and the cable's cross-sectional area should be determined by the principle of equivalent axial stiffness.

• Smart Structures and Systems
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• v.21 no.4
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• pp.421-433
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• 2018

Carbon fiber reinforced polymer (CFRP) cable has good mechanical properties and corrosion resistance. However, the anchorage of CFRP cable is a big issue due to the anisotropic property of CFRP material. In this article, a high-efficient bonding anchorage with novel configuration is developed for CFRP cables. The acoustic emission (AE) technique is employed to evaluate the performance of anchorage in the fatigue test and post-fatigue ultimate bearing capacity test. The obtained AE signals are analyzed by using a combination of unsupervised K-means clustering and supervised K-nearest neighbor classification (K-NN) for quantifying the performance of the anchorage and damage evolutions. An AE feature vector (including both frequency and energy characteristics of AE signal) for clustering analysis is proposed and the under-sampling approaches are employed to regress the influence of the imbalanced classes distribution in AE dataset for improving clustering quality. The results indicate that four classes exist in AE dataset, which correspond to the shear deformation of potting compound, matrix cracking, fiber-matrix debonding and fiber fracture in CFRP bars. The AE intensity released by the deformation of potting compound is very slight during the whole loading process and no obvious premature damage observed in CFRP bars aroused by anchorage effect at relative low stress level, indicating the anchorage configuration in this study is reliable.