Real-Time Aeroelastic Hybrid Simulation Method for Bridge Deck Section Models
Publication: Journal of Structural Engineering
Volume 149, Issue 5
Abstract
A section model test effectively assesses the aeroelastic behavior of long-span bridges in a wind-resistant design. The conventional approach uses springs to support a mass-calibrated physical section model scaled to the similarity principle. Modal damping can also be modeled using sticks soaked in oils. Although this procedure has been successfully applied to most bridges, it involves physical limitations in selecting the model scale and vibration frequencies. Also, certain degrees of time and effort are required for the calibration and modification of dynamic properties in order to achieve precision. This study proposes a new real-time aeroelastic hybrid simulation (RTAHS) approach that eliminates the potential drawbacks of the conventional spring-supported section model test. With this new approach, the aeroelastic force on the physical section model is directly measured using supporting load cells. The equation of motion is solved numerically, and linear electric motors impose the expected movement of the model in a real-time fashion. The hardware of the RTAHS consists of linear electric motors, motor drivers, sensors, and an Ethernet for Control Automation Technology (EtherCAT) based real-time motion controller. The hardware is controlled with three control loops, i.e., numerical integration, time-delay compensation, and PID control of the position. For this study, a series of comparative wind tunnel tests was used to demonstrate the validity of the proposed RTAHS concept.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was supported by a Grant (20SCIP-B119964-06) from the Ministry of Land, Infrastructure and Transport of the Korean Government through the Korea Bridge Design and Engineering Research Center at the Seoul National University. The third author acknowledges the support by Brain Pool Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Grant No. NRF-2020H1D3A2A01063648) and Natural Sciences and Engineering Research Council of Canada (Grant No. ALLRP 549582–19).
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© 2023 American Society of Civil Engineers.
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Received: Jan 16, 2022
Accepted: Nov 29, 2022
Published online: Feb 16, 2023
Published in print: May 1, 2023
Discussion open until: Jul 16, 2023
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