公路桥梁车辆荷载随机过程模型  

Vehicles load stochastic process model of highway bridges

作　　者：余志武[1] 朱红兵[1,2] 蒋丽忠[1] 黄星浩[1] 唐斌[1] 

机构地区：[1]中南大学土木工程学院,湖南长沙410075 [2]武汉科技大学城市建设学院,湖北武汉430070

出　　处：《中南大学学报（自然科学版）》2011年第10期3131-3135,共5页Journal of Central South University:Science and Technology

基　　金：国家自然科学基金资助项目(50878216);国家西部交通建设科技项目(200631800019)

摘　　要：以多年交通量统计数据为基础,利用灰色系统建立交通量增长的灰色GM(1,1)预测模型,进一步利用马尔科夫链对模型进行处理,得到公路交通量增长随机过程预测模型;利用贵新公路(贵州贵阳—新寨)2 a内连续的车辆总质量,将车质量分布函数与交通量预测模型相结合,得到车辆荷载随机过程模型。研究结果表明:该随机过程预测模型精度较高,车辆总质量符合双指数分布规律;由车辆荷载随机过程模型可计算出一定年限内通过桥梁的某车辆荷载总质量范围内的车辆数,从而较好地解决了桥梁疲劳分析和验算时桥梁运营期内荷载疲劳累积计算问题。Based on the traffic statistical data of many years,a traffic increasing prediction model was established by using grey system theory,then it is treated with Markov chain,and highway＇s traffic increasing stochastic process prediction model was achieved.Utilizing 2 years continual vehicles masses measured at Guixin highway（Guiyang—Xinzai）,combined with vehicle＇s mass distribution function and traffic prediction model,vehicles load stochastic process model of highway bridges was obtained.The results show that the model has a high precision and vehicle＇s mass corresponds with two exponential distributions.The model can figure out vehicle numbers which across the bridge in a certain load mass scope during a certain period,so the model can resolve loads cumulate fatigue calculation problem during fatigue analysis or fatigue checking.

关 键 词：桥梁 疲劳 车辆荷载 灰色系统 马尔科夫链 

分 类 号：U441.4[建筑科学—桥梁与隧道工程]