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Measuring Behavior of Long-Span Bridges during Erection: Case Study of the Governor Mario M. Cuomo Bridge
The design of long-span cable-stayed bridges is governed by dead and erection loads, as well as wind loading. Despite the importance of dead and erection loads, their impact on the behavior of built structures is unknown, owing to limitations in using conventional sensors (e.g., strain gauges) during construction. To address this knowledge gap, this paper introduces three-dimensional (3D) digital image correlation (DIC) as a method to measure the erection-induced and dead load behavior of bridges. DIC is a portable, noncontact photographic technique that relies on pattern recognition and photogrammetric triangulation principles to calculate strains. This method was demonstrated by measuring the behavior of the Governor Mario M. Cuomo Bridge—a twin-span, cable-stayed bridge—between two intermediate construction stages. The strains from the anchoring of six cables and the application of the tie-down force were measured in the two edge girders, the end floor beam, and the supplemental longitudinal truss. Results indicate that the strains in the girders were similar in magnitude and approximately symmetrical in direction. Shear behavior was observed in the end floor beam between the north edge girder and the tie-down. At the location of the shop weld of the end floor beam, an increase in strain was observed from the thicker side to the thinner side, with a change from flexure toward shear dominant behavior closer to the tie-down. Measured results are compared with predictions from a 3D finite-element model, further verifying this measurement technique. While this method is demonstrated for the Governor Mario M. Cuomo Bridge, DIC can be broadly used for the measurement of dead load and erection-induced strains, providing unprecedented information on behavior. Recommendations for implementing DIC for monitoring bridges during erection are provided.
This paper introduces a method to measure the behavior of long-span bridges during erection. Specifically, a photographic measurement technique, known as digital image correlation, can track the strains induced between different stages of construction. Hardware includes two cameras that are mounted on a rigid bar, a sensor controller, and a data acquisition laptop, as well as a power source (e.g., a portable generator). Photographs of bridge components, for which a pattern has been preapplied, are taken at different stages. Then a software package is used to calculate the strains based on pattern recognition. This technique overcomes the barriers of using conventional sensors (i.e., strain gauges) during erection, as the system does not need to remain onsite between erection stages and a constant power source is not required. This technique is demonstrated for the case study of the Governor Mario M. Cuomo Bridge, a twin-span cable-stayed bridge, but the technique could be used widely across the bridge industry.
Measuring Behavior of Long-Span Bridges during Erection: Case Study of the Governor Mario M. Cuomo Bridge
The design of long-span cable-stayed bridges is governed by dead and erection loads, as well as wind loading. Despite the importance of dead and erection loads, their impact on the behavior of built structures is unknown, owing to limitations in using conventional sensors (e.g., strain gauges) during construction. To address this knowledge gap, this paper introduces three-dimensional (3D) digital image correlation (DIC) as a method to measure the erection-induced and dead load behavior of bridges. DIC is a portable, noncontact photographic technique that relies on pattern recognition and photogrammetric triangulation principles to calculate strains. This method was demonstrated by measuring the behavior of the Governor Mario M. Cuomo Bridge—a twin-span, cable-stayed bridge—between two intermediate construction stages. The strains from the anchoring of six cables and the application of the tie-down force were measured in the two edge girders, the end floor beam, and the supplemental longitudinal truss. Results indicate that the strains in the girders were similar in magnitude and approximately symmetrical in direction. Shear behavior was observed in the end floor beam between the north edge girder and the tie-down. At the location of the shop weld of the end floor beam, an increase in strain was observed from the thicker side to the thinner side, with a change from flexure toward shear dominant behavior closer to the tie-down. Measured results are compared with predictions from a 3D finite-element model, further verifying this measurement technique. While this method is demonstrated for the Governor Mario M. Cuomo Bridge, DIC can be broadly used for the measurement of dead load and erection-induced strains, providing unprecedented information on behavior. Recommendations for implementing DIC for monitoring bridges during erection are provided.
This paper introduces a method to measure the behavior of long-span bridges during erection. Specifically, a photographic measurement technique, known as digital image correlation, can track the strains induced between different stages of construction. Hardware includes two cameras that are mounted on a rigid bar, a sensor controller, and a data acquisition laptop, as well as a power source (e.g., a portable generator). Photographs of bridge components, for which a pattern has been preapplied, are taken at different stages. Then a software package is used to calculate the strains based on pattern recognition. This technique overcomes the barriers of using conventional sensors (i.e., strain gauges) during erection, as the system does not need to remain onsite between erection stages and a constant power source is not required. This technique is demonstrated for the case study of the Governor Mario M. Cuomo Bridge, a twin-span cable-stayed bridge, but the technique could be used widely across the bridge industry.
Measuring Behavior of Long-Span Bridges during Erection: Case Study of the Governor Mario M. Cuomo Bridge
J. Bridge Eng.
Wang, Yao (Autor:in) / Thrall, Ashley P. (Autor:in) / Zoli, Theodore P. (Autor:in) / Sun, Shiyao (Autor:in)
01.12.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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