本文選題：隨機(jī)車流　切入點(diǎn)：荷載調(diào)查　出處：《長(zhǎng)沙理工大學(xué)》2014年碩士論文

【摘要】：車輛荷載作用在橋梁上具有一定的隨機(jī)性和變化性,特別是隨著現(xiàn)代社會(huì)的發(fā)展,交通量的增大,對(duì)高速公路橋梁進(jìn)行隨機(jī)車輛荷載譜研究很有必要。本文以吉茶高速公路矮寨大橋?yàn)楣こ瘫尘?對(duì)矮寨大橋進(jìn)行了為期48小時(shí)的隨機(jī)荷載調(diào)查與研究,主要工作和研究如下：1.進(jìn)行了連續(xù)48小時(shí)的隨機(jī)車輛荷載調(diào)查,并系統(tǒng)研究了車輛隨機(jī)荷載各參數(shù)的分布特點(diǎn),確定了荷載調(diào)查的方法與步驟并將矮寨大橋的車輛荷載分為七大類型,分別對(duì)各類車型進(jìn)行車型構(gòu)成比例、車流量構(gòu)成比例、車道參數(shù)、車速參數(shù)、車道橫向位置參數(shù)、車重參數(shù)等進(jìn)行一系列分析與研究。研究結(jié)果表明：矮寨大橋車輛荷載主要是以第二類小轎車和第七類大型貨車為主,其中小轎車占總車輛的49.5%,第七類大型貨車占總車輛的21.56%,其余類型車輛所占的比例均小于10%；第一類至第七類車型的典型車重分別為1646kg、1451kd、3572kg、 12395kg、6974kg、29104kg以及52832kg。2.采用正態(tài)分布、對(duì)數(shù)正態(tài)分布和威布爾分布三種分布類型函數(shù)對(duì)矮寨大橋車流量進(jìn)行參數(shù)分析和優(yōu)化擬合,通過(guò)K-S檢驗(yàn)方法來(lái)檢驗(yàn)是否通過(guò)要求,尋找出與實(shí)測(cè)分布最為接近的分布參數(shù)及分布類型。研究結(jié)果表明：最終選用正態(tài)分布函數(shù)來(lái)替代各車型車速分布函數(shù),威布爾分布函數(shù)來(lái)代替各車型車道橫向位置分布函數(shù),正態(tài)分布函數(shù)來(lái)代替各車型的車重分布函數(shù)。3.根據(jù)車輛對(duì)橋的損傷量對(duì)車輛進(jìn)行折算,研究車輛荷載的時(shí)間序列來(lái)獲得車輛荷載的功率譜密度函數(shù)和自相關(guān)函數(shù),得到調(diào)查車流數(shù)據(jù)的頻率和各種特性。結(jié)合前面的結(jié)論矮寨大橋隨機(jī)車流主要服從正態(tài)分布,得到折算后車流的均值和標(biāo)準(zhǔn)差,并利用Matlab編制出相關(guān)的程序,生成滿足此分布的矮寨大橋隨機(jī)車輛荷載譜。
[Abstract]:The effect of vehicle load on the bridge is random and changeable, especially with the development of modern society, the increase of traffic volume, It is necessary to study the random vehicle load spectrum of expressway bridge. In this paper, a 48-hour random load investigation and research on the Puizhai Bridge of Ji-cha Expressway is carried out. The main work and research are as follows: 1. A 48-hour random vehicle load survey has been carried out, and the distribution characteristics of the parameters of the vehicle random load have been systematically studied. The methods and steps of load investigation are determined, and the vehicle loads of Aizhai Bridge are divided into seven types, which are the proportion of vehicle types, the proportion of traffic flow, lane parameters, speed parameters, lane lateral position parameters. A series of analysis and research on the vehicle weight parameters are carried out. The results show that the second kind of cars and the seventh kind of large trucks are the main loads of the vehicles in the pai Zhai Bridge. The cars account for 49.5% of the total vehicles, the seventh type of large trucks account for 21.56% of the total vehicles, and the other types of vehicles account for less than 10% of the total vehicles. The typical vehicle weights of the first to seventh types of vehicles are 1646 kg / 1451 kg / d 3572 kg / kg, 12395kg / 694 kg / 29104 kg and 52832 kg / g / 2.The typical vehicle weights of the first and seventh types of vehicles are 1646 kg / kg / 1451 kg / d 3572 kg / kg, 12395kg / 1 974 kg / kg 29104kg and 52832kg.2. The logarithmic normal distribution and Weibull distribution are used to analyze and optimize the traffic flow of the pai Zhai Bridge. The K-S test method is used to test whether the traffic flow is required or not. The results show that the normal distribution function is used to replace the vehicle speed distribution function and the Weibull distribution function to replace the lateral position distribution function of each vehicle lane. The normal distribution function is used to replace the vehicle weight distribution function of each vehicle type. According to the damage amount of the vehicle to the bridge, the time series of vehicle load are studied to obtain the power spectrum density function and autocorrelation function of vehicle load. The frequency and characteristics of the investigated traffic flow data are obtained. Combined with the previous conclusion, the random traffic flow of the Aizhai Bridge is mainly from normal distribution, the mean value and standard deviation of the converted traffic flow are obtained, and the relevant programs are compiled by using Matlab. The random vehicle load spectrum of pai-zhai bridge satisfying this distribution is generated.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U441.2

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本文編號(hào)：1674796