摘要
This paper focuses on understanding and evaluating the dynamic effect of the heavy-haul train system on the seismic performance of a long-span railway bridge. A systematic study on the effect of heavy-haul trains on bridge seismic response has been conducted, considering the influence of vehicle modeling strategies and dynamic characteristics of the seismic waves. For this purpose, the performance of a long-span cable-stayed railway bridge is assessed with stationary trains atop it, where the heavy-haul vehicles are modeled in two different ways: the multi-rigid body model with suspension system and additional mass model. Comparison of the bridge response in the presence or absence of the train system has been conducted, and the vehicle loading situation, which includes full-load and no-load, is also discussed. The result shows that during the earthquake, the peak moment of the main girder and peak stress of stay cables increase by 80% and by 40% in the presence of fully loaded heavy-haul trains, respectively. At the same time, a considerable decrease appears in the peak acceleration of the main girder. This proves the existence of the damping effect of the heavy-haul train system, and this effect is more obvious for the fully loaded vehicles. Finally, this paper proposes an efficient vehicle modeling method with 2 degrees of freedom(DOF) for simplifying the treatment of the train system in bridge seismic checking.
本文为了评估重载列车系统的动力效应对大跨度铁路桥梁地震响应的影响,研究了重载列车静止在铁路斜拉桥上时的动力特性以及地震响应,采用了基于多刚体力学的空间车辆模型与附加质量模型两种不同的方式对车辆进行建模。计算中考虑了桥梁的几何非线性,并采用了三类地震波进行数值模拟。在对比有无车辆情况下的桥梁响应时,考虑了重载货车满载以及空载的因素。结果表明,在地震发生时,满载的列车会使得主梁弯矩以及拉索的索力峰值分别增加80%与40%,但是主梁的加速度峰值则会显著下降。证明了重载列车存在一定阻尼效应,且该阻尼效应对于满载列车来说更为显著。在此基础上,提出了一种用于桥梁抗震验算的简化2自由度车辆模型,并证明了其可靠性。
作者
ZHU Zhi-hui
GONG Wei
WANG Kun
LIU Yu
DAVIDSON Michael T
JIANG Li-zhong
朱志辉;龚威;王琨;刘宇;DAVIDSON Michael T;蒋丽忠(School of Civil Engineering,Central South University,Changsha 410075,China;Key Laboratory of Engineering Structure of Heavy Railway of Ministry of Education,Changsha 410075,China;Bridge Software Institute,Engineering School of Sustainable Infrastructure and Environment,University of Florida,Gainesville,USA)
基金
Project(51678576) supported by the National Natural Science Foundation of China
Project(2017YFB1201204) supported by the National Key R&D Program of China。