Dynamic Performance Simulation of Long-Span Bridge under Combined Loads of Stochastic Traffic and Wind

桥(图论) 气动弹性 跨度(工程) 结构工程 风力工程 卡车 流量(计算机网络) 工程类 风速 细胞自动机 空气动力学 计算机科学 汽车工程 气象学 航空航天工程 内科学 物理 医学 计算机安全 算法
作者
Suren Chen,Jun Wu
出处
期刊:Journal of Bridge Engineering [American Society of Civil Engineers]
卷期号:15 (3): 219-230 被引量:97
标识
DOI:10.1061/(asce)be.1943-5592.0000078
摘要

Slender long-span bridges exhibit unique features which are not present in short and medium-span bridges such as higher traffic volume, simultaneous presence of multiple vehicles, and sensitivity to wind load. For typical buffeting studies of long-span bridges under wind turbulence, no traffic load was typically considered simultaneously with wind. Recent bridge/vehicle/wind interaction studies highlighted the importance of predicting the bridge dynamic behavior by considering the bridge, the actual traffic load, and wind as a whole coupled system. Existent studies of bridge/vehicle/wind interaction analysis, however, considered only one or several vehicles distributed in an assumed (usually uniform) pattern on the bridge. For long-span bridges which have a high probability of the presence of multiple vehicles including several heavy trucks at a time, such an assumption differs significantly from reality. A new “semideterministic” bridge dynamic analytical model is proposed which considers dynamic interactions between the bridge, wind, and stochastic “real” traffic by integrating the equivalent dynamic wheel load (EDWL) approach and the cellular automaton (CA) traffic flow simulation. As a result of adopting the new analytical model, the long-span bridge dynamic behavior can be statistically predicted with a more realistic and adaptive consideration of combined loads of traffic and wind. A prototype slender cable-stayed bridge is numerically studied with the proposed model. In addition to slender long-span bridges which are sensitive to wind, the proposed model also offers a general approach for other conventional long-span bridges as well as roadway pavements to achieve a more realistic understanding of the structural performance under probabilistic traffic and dynamic interactions.

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