基于南京长江三桥的车辆荷载模型  

Traffic load model based on the third Nanjing Yangtze river bridge

作　　者：林诗枫[1] 黄侨[1] 任远[1] 樊叶华 杨娟 

机构地区：[1]东南大学交通学院,南京210096 [2]南京长江第三大桥有限公司,南京211808

出　　处：《东南大学学报（自然科学版）》2016年第2期365-370,共6页Journal of Southeast University：Natural Science Edition

基　　金：国家自然科学基金资助项目(51208096);江苏省交通运输科技项目重大专项资助项目(2014Y02);江苏省交通运输科技资助项目(2012Y25)

摘　　要：为了满足南京长江三桥的技术状态评估和预测的需求,基于该桥收费站7年的称重数据库和桥面监控视频资料,根据不同的轴组类型对日常运营的主要车辆进行了车型划分.采用参数估计和非参数估计方法,建立了车辆质量、轴距、车型、轴重等车辆荷载模型中相关参数的数学模型.然后,基于泊松过程理论、Markov过程理论和车辆跟驰模型,对车辆荷载模型中的车速、车辆到达时刻等时变参数进行随机模拟.研究结果表明:多数车型质量分布为多峰分布,宜采用核密度估计法确定其统计模型;生成随机车辆时,需考虑车辆质量与车速、轴重等参数的相关性;采用M CM C法模拟得到的随机车辆车型分布近似于桥梁实际运营中的车型分布.To meet the demands of the structure assessment and prediction of the third Nanjing Yangtze river bridge,the major vehicles in daily operation are categorized according to different types of vehicle axes based on the 7-year weighing database of the toll station and video surveillance of this bridge. The mathematical models of the vehicle weight,the wheelbase,the vehicle type,and the wheel weight are set up by parameter estimation and nonparametric estimation methods. Then,the time-dependent parameters,such as the vehicle velocity and the vehicle arrival time,are stochastically stimulated based on the Poisson process theory,the Markov process theory and the vehicle follow-ing model. The research results showthat the weight distributions of most classified vehicles are subject to the multi-peak distributions,so the statistical model should be built by the kernel density estimation method. The correlation between the vehicle weight and the velocity and that between the vehicle weight and the wheel weight should be considered when the random vehicles are generated. The distribution of the random vehicle types simulated by the MCMC（ Markov chain Monte Carlo） method is approximate to the distribution of the vehicle types during the actual bridge operational period.

关 键 词：桥梁工程 车辆荷载模型 荷载流模拟 养护管理 

分 类 号：TU312[建筑科学—结构工程]