连续配筋混凝土路面(CRCP)的施工实践

通过张(家口)石(家庄)高速公路连续配筋混凝土路面(CRCP)试验路的修筑,总结连续配筋混凝土路面(CRCP)在施工准备、钢筋安装、混凝土摊铺、端部处理等方面的施工技术要点,其结果可为其在我国高速公路中的应用提供参考.     

车辆动力学仿真中评判脱轨的直接方法

根据轮轨空间动态耦合关系 ,提出了一种根据轮轨接触点位置进行脱轨评定的直接方法 ,可用于对机车车辆动力学安全性分析评价。阐述了通过轮轨接触点进行脱轨评判的原理和采用此方法的优点。作为例子 ,运用货车 -轨道空间耦合模型 ,对 C62 A货车曲线通过进行了脱轨仿真计算。仿真结果表明 ,在仿真计算时采用此方法非常行之有效 ,评判直观、可靠     

轿车座椅R点及体压分布仿真计算

该文利用MADYMO进行座椅参考点R点坐标的预测,并分析了不同百分位假人模型的体压分布情况;针对50百分位的多体假人模型,通过调整座椅泡沫的刚度,探寻50百分位多体假人模型最理想的体压分布图,研究结果可作为轿车座椅设计、座椅舒适性评价的参考和依据。     

我国公路快速货运发展的切入点

本文首先对公路快速货运系统的定义做了必要的补充并对公路快速货运的产业特点进行了阐述,之后从宏观与微观的角度对目前我国公路快速货运业发展中出现的货运需求不足的问题进行了分析,得出是由于集散运输发展滞后、服务交易成本过高导致了行业发展缓慢的结论。最后,提出我国公路快速货运发展应以大、中城市工商企业的快运需求为切入点,从市内快运向城间区域快运方向发展。     

环境法律制度的经济分析

依靠政府干预和市场机制是两种基本环境法律制度,都能在一定程度上起到使环境污染的外部不经济性内部化作用,但两者各有利弊,且实施途径与经济效果不尽相同,选择适宜的环境法律制度对防治环境污染至关重要。     

形状记忆合金梁动力稳定性

基于形状记忆合金材料的热：力学行为和拟弹性行为本构关系及梁的动力学平衡方程，建立了该类梁横向振动非线性动力学模型．用平衡态定性分析法讨论了形状记忆合金梁的稳定性与材料相变的关系．研究表明，梁的横向振动平衡态的稳定性与材料相的稳定性有对应关系．在马氏体相稳定的低温状态，系统有3个不动点，1个为稳定中心，另外2个为不稳定鞍点；在马氏体与奥氏体共存的中间温度状态，系统有5个不动点，3个为稳定的中心，2个为不稳定的鞍点；在奥氏体相稳定的高温度状态，系统有唯一稳定不动点。     

基于手机GPS定位数据的交通方式换乘点识别方法研究

交通方式换乘点识别长期以来是手机大数据交通调查领域的一大技术难点,既有研究大多通过设置出行时间、距离阈值进行识别,算法经验性强,普适性不佳,且易将起讫点、信号控制、交通拥堵等停留误识别为换乘停留。为此,提出了一种基于手机GPS定位数据的交通方式换乘点识别新方法：首先,构建模糊时空聚类算法识别个体运动-静止状态,算法同步实现了定位点时空密度双重聚类约束与聚类边界弹性需求,对个体运动状态识别效果更佳;其次,建立支持向量机模型进行交通方式换乘点识别,有效解决了起讫点、信号控制、交通拥堵等停留对换乘停留造成的干扰;最后,从出行链视角出发,提出了基于序列相似度算法的误差回溯自检与优化模型,能够有效修复换乘点漏识别与错误识别问题。此外,在成都市开展了大范围实测试验,由150名志愿者采集了近2 160 h得到的777.6万条数据被用于技术实证评估。试验结果表明：所述方法对交通方式换乘点平均识别准确率达89.3%,换乘时间平均识别误差控制在20 s以内;与既有空间聚类、小波分析算法相比,换乘点识别精度提升近10%,换乘时间误差最大可降低20 s以上,算法适用性与效果更佳。研究成果可为基于活动的交通需求模型演进提供数据支撑,为交通规划与管理部门决策提供技术支持。     

汽车控制器输入信号采集接口设计

本文介绍了几种常用的汽车控制器输入信号采集接口设计方案,并对比分析了这几种方案优缺点。     

The cost of convenience; Air pollution and noise on freeway and arterial light rail station platforms in Los Angeles

Light rail transit (LRT) systems constitute one of the most sustainable public transportation modes and transit agencies have increasingly constructed LRT lines along the median of roadways to reduce land acquisition costs and traffic conflicts. Despite these conveniences, few studies have examined the air pollution and noise exposures for passengers on LRT station platforms within freeway or arterial medians. In response, we monitored particle number count (PNC) concentrations and noise levels on 17 station platforms in the Los Angeles metro system in summer 2012 and assessed differences between freeway and arterial platforms. We visited each station on average 7 times for approximately 19 min with two teams carrying a full set of instruments. As expected, impacts were higher on green line platforms in the center of a grade-separated freeway compared to blue line platforms in the center of an arterial due to being in close proximity to greater traffic volumes. Overall, freeway-arterial platform differences were 35,100 versus 20,000 particles/cm³ for PNC and 83 versus 62 dBA for noise. This average noise intensity on green line platforms was four times that on blue line stations. We also found that PNC concentrations were significantly higher at open air monitoring platform positions compared to standing under a shade canopy (about 2000 particles/cm³ higher), but that noise levels were significantly lower at open air positions compared to under canopy positions (about 3.2 dBA lower). Results identify important factors for transport planners to consider when locating and designing in-roadway LRT platforms.     

Integrated data-driven modeling to estimate PM2.5 pollution from heavy-duty truck transportation activity over metropolitan area

Based on the national emission inventory data from different countries, heavy-duty trucks are the highest on-road PM_2.5 emitters and their representation is estimated disproportionately using current modeling methods. This study expands current understanding of the impact of heavy-duty truck movement on the overall PM_2.5 pollution in urban areas through an integrated data-driven modeling methodology that could more closely represent the truck transportation activities. A detailed integrated modeling methodology is presented in the paper to estimate urban truck related PM_2.5 pollution by using a robust spatial regression-based truck activity model, the mobile source emission and Gaussian dispersion models. In this research, finely resolved spatial–temporal emissions were calculated using bottom-up approach, where hourly truck activity and detailed truck-class specific emissions rates are used as inputs. To validate the proposed methodology, the Cincinnati urban area was selected as a case study site and the proposed truck model was used with U.S. EPA’s MOVES and AERMOD models. The heavy-duty truck released PM_2.5 pollution is estimated using observed concentrations at the urban air quality monitoring stations. The monthly air quality trend estimated using our methodology matches very well with the observed trend at two different continuous monitoring stations with Spearman’s rank correlation coefficient of 0.885. Based on emission model results, it is found that 71 percent of the urban mobile-source PM_2.5 emissions are caused by trucks and also 21 percent of the urban overall ambient PM_2.5 concentrations can be attributed to trucks in Cincinnati urban area.