Analysis of Long-Term Prestress Loss in Prestressed Concrete (PC) Structures Using Fiber Bragg Grating (FBG) Sensor-Embedded PC Strands

This study aims to develop a prestressed concrete steel (PC) strand with an embedded optical Fiber Bragg Grating (FBG) sensor, which has been developed by the Korea Institute of Civil Engineering and Building Technology since 2013. This new strand is manufactured by replacing the steel core of the normal PC strand with a carbon-fiber-reinforced polymer (CFRP) rod with excellent tensile strength and durability. Because this new strand is manufactured using the pultrusion method, which is a composite material manufacturing process, with an optical fiber sensor embedded in the inner center of the CFRP Rod, it ensures full composite action as well as proper function of the sensor. In this study, a creep test for maintaining a constant load and a relaxation test for maintaining a constant displacement were performed on the proposed sensor-type PC strand. Each of the two tests was conducted for more than 1000 h, and the long-term performance verification of the sensor-type PC strand was only completed by comparing the performance with that of a normal PC strand. The test specimens were fabricated by applying an optical fiber sensor-embedded PC strand, which had undergone long-term performance verification tests, to a reinforced concrete beam. Depending on whether grout was injected in the duct, the specimens were classified into composite and non-composite specimens. A hydraulic jack was used to prestress the fabricated beam specimens, and the long-term change in the prestress force was observed for more than 1600 days using the embedded optical fiber sensor. The experimental results were compared with the analytical results to determine the long-term prestress loss obtained through finite-element analysis based on various international standards.

Research on Prediction Model of Prestress Loss of Anchor Cable in Soil-Rock Dual-Structure Slope

The establishment of the prestressed cable loss prediction model is a difficult problem faced by the popularization and use. This article aims at the problem of the loss of anchor cable prestress over time in the soil-rock dual-structure slope. We relied on the soil-rock dual-structure slope treatment project of section K5 + 220-K5 + 770 of Jiangwen Expressway and monitored the prestress loss of the anchor cable in the slope through the anchor cable meter with built-in vibrating wire sensor. Using regression analysis and segmented modelling methods, we established a comprehensive mathematical improvement model, analyzed the applicability of the improved model, and obtained the error range, 0.04%–8.9%. This work offers a new approach for predicting anchor cable prestress loss, which has certain practical value for the use of prestressed anchor cables.

Determination of Bridge Prestress Loss under Fatigue Load Based on PSO-BP Neural Network

During the service period of a prestressed concrete bridge, as the number of cyclic loads increases, cumulative fatigue damage and prestress loss will occur inside the structure, which will affect the safety, durability, and service life of the structure. Based on this, this paper studies the loss of bridge prestress under fatigue load. First, the relationship between the prestress loss of the prestressed tendons and the residual deflection of the test beam is analyzed. Based on the test results and the main influencing factors of fatigue and creep, a concrete fatigue and creep calculation model is proposed; then, based on the static cracking check calculation method and POS-BP neural network algorithm, a prestressed concrete beam fatigue cracking check model under repeated loads is proposed. Finally, the mechanical performance of the prestressed concrete beam after fatigue loading is analyzed, and the influence of the fatigue load on the bearing capacity of the prestressed concrete beam is explored. The results show that the bridge prestress loss characterization model based on the POS-BP neural network algorithm has the advantages of high calculation efficiency and strong applicability.

Analysis of Re-Tensioning Time of Anchor Cable Based on New Prestress Loss Model

Considering the interaction among anchor cable, frame beam and rock mass, a new model of prestress loss of anchor cable was established. The accuracy and applicability of the new model were verified by comparing the field monitoring data and the calculation results of existing models. In addition, based on the new model, the effect of the re-tension of the anchor cable at different time nodes was analyzed, and the later compensation time of anchor cable prestress was discussed. The research shows that: the accuracy of the new model is higher after considering the effect of the frame beam, the new model can not only calculate the loss of prestress of anchor cable, but also accurately predict the time when the prestress of anchor cable reaches the stable stage. The ideal effect of prestress compensation can be achieved when the anchor cable is re-tensioned at each time point after 20 days of the construction completed. The original prestress loss of the anchor cable is different, and the re-tension effect is also different, the greater the loss of the original prestress of the anchor cable, the more obvious the prestress compensation effect during the re-tension.

Development of prestress-loss identification method in the cable-anchorage systemusing impedance responses and artificial neural networks

In this paper, a method for identifying the loss of prestressing force (prestress-loss) in the cable-anchorage system of prestressed concrete structures using the impedance responses and artificial neural networks (ANNs) is developed. First, theories of impedance responses and damage detection methods for diagnosing the occurrence and the severity of prestress-loss are presented. In which, the occurrence of prestress-loss is determined by MAPD (Mean Absolute Percentage Deviation) index. Then, the severity of the prestress-loss is determined by ANNs. The feasibility of the developed method is verified by numerical simulations for a real cable-anchorage system with different levels of prestress-loss. The reliability of the numerical simulations for impedance responses is evaluated by comparison to experimental results. Finally, the occurrence and severity of the prestress-loss are exactly identified by the proposed method. The results of this study show that the proposed method is highly effective in determining the prestress-loss in the cable-anchorage system