State of the Art Review of Aerodynamic Effects on Bridges

Haldar, Puja; Karmakar, Somnath

doi:10.1007/s40030-022-00640-6

Cited by 3 publications

(1 citation statement)

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“…Presently, domestic and foreign codes and other related studies are being conducted from the perspectives of vortex vibration limit and the fatigue of structural components caused by vortex vibration [ 9 , 10 , 11 , 12 ]. However, less attention is being paid to driving safety.…”

Section: Introductionmentioning

confidence: 99%

Online Intelligent Perception of Front Blind Area of Vehicles on a Full Bridge Based on Dynamic Configuration Monitoring of Main Girders

Zeng

Dan

Guan

et al. 2022

Sensors

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Establishing an online perception mechanism for a driver’s front blind area on a full bridge under vertical vortex-induced vibration (VVIV) is essential for ensuring road safety and traffic control on bridge decks under specific conditions. Based on accelerations of vibration monitoring of the main girders, this paper uses a real-time acceleration integration algorithm to obtain real-time displacements of measurement points; realizes the real-time estimation of the dynamic configurations of a main girder through parametric function fitting; and then can perceive the front blind area for vehicles driving on bridges experiencing VVIV in real time. On this basis, taking a long-span suspension bridge suffering from VVIV as an engineering example, the influence of different driving conditions on the front blind area is examined. Then, the applicability of the intelligent perception technology framework of the front blind area is verified. The results indicate that, during VVIV, the driver’s front blind area changes periodically and the vehicle model has the most significant impact on the front blind area; in contrast, the vehicle’s speed and the times of the vehicle entering the bridge have minimal impact on it. Meanwhile, it is shown that the framework can accurately perceive front blind areas of vehicles driving on the bridge, and identify different vehicle models, speeds and times of vehicle bridge entries in real time.

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Section: Introductionmentioning

confidence: 99%