基于多元胞模型的桥梁车流合成及荷载模拟

发布时间：2018-08-26 09:19

【摘要】：随机车辆荷载模拟是桥梁荷载评定和性能评估的基础和关键,目前基于Monte Carlo的车流模拟较难呈现长加载跨径内车流的微观动态演化特性,而基于元胞自动机(CA)的单元胞模拟方法在加载精度方面仍需改进.单元胞模拟法中,将每个车辆用一个元胞模拟,难以体现轴重影响,限制了模拟精度的提高.在此基础上,提出了每个元胞模拟一个车轴,多个元胞模拟一辆车的多元胞自动机(MCA)模型,并利用实测车流及其荷载数据进行模型校核.研究表明:多元胞车轴模拟方法能够准确地还原车流量、车头时距、车速、车重等系列车流以及荷载参数.以1 000m虚拟加载跨径的荷载集度、支点剪力、跨中弯矩为指标,统计模拟车流和实测数据的荷载响应特性.结果显示,MCA模型的模拟结果与实际车流误差均在5%以内,相较于传统单元胞模型17%的误差,精度显著提高.
[Abstract]:Stochastic vehicle load simulation is the basis and key of bridge load assessment and performance evaluation. At present, the simulation of vehicle flow based on Monte Carlo is difficult to present microscopic dynamic evolution characteristics of vehicle flow in long span. The cell simulation method based on cellular automata (CA) still needs to be improved in loading accuracy. In the unit cell simulation method, one cell is used for each vehicle, so it is difficult to reflect the influence of axle load, which limits the improvement of simulation accuracy. On this basis, a multivariate cellular automaton (MCA) model is proposed for each cell to simulate one axle and several cells to simulate a vehicle. The model is verified by the measured vehicle flow and its load data. The results show that the multiple cell axle simulation method can accurately restore the traffic flow, head-time distance, speed, vehicle weight and other series of vehicle flow as well as load parameters. The load-set degree, fulcrum shear force and mid-span bending moment of 1 000 m virtual loading span are taken as the indexes to simulate the load response characteristics of the vehicle flow and the measured data. The results show that the simulation results of MCA model and the actual traffic flow error are within 5%, compared with the traditional cell model error of 17%, the accuracy is significantly improved.
【作者单位】：同济大学土木工程学院;同济大学交通运输工程学院;
【基金】：国家自然科学基金(51478337,51678435) 中央高校基本科研业务费专项资金(2016J012302) “交通运输工程”高峰学科开放基金(2016J012302)
【分类号】：U441.2

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