进气滚流强度对直喷发动机燃烧特性的影响

以光学单缸直喷汽油发动机作为试验平台,通过在进气法兰处安装不同的滚流导流板调节进气截面积来获得不同强度的滚流气流。利用Converge软件对缸内滚流强度和湍动能进行评估,采用高速彩色相机拍摄不同滚流强度下火焰状态随曲轴转角的变化,同时采用燃烧分析仪采集缸压数据。通过图像处理分离蓝色火焰和黄色火焰,其中,蓝光被认为主要来自火焰中CH释放的化学荧光,而黄光被认为主要来自炭烟颗粒的辐射。试验发现:随着滚流强度的提高,蓝色火焰面积增加,缸内燃烧速率得以提升,缸内平均指示有效压力增强,相关性分析表明,蓝色火焰面积和燃烧放热率有很好的正相关性。同时,黄色火焰随滚流强度增加而减少,表明炭烟生成量降低。此外,燃烧的循环波动也随滚流强度的增加而降低。     

排气温度、排气流量和海拔高度对SCR系统NOx转化率和NH3泄漏量的影响研究

为研究不同海拔下SCR系统性能,分别在80、90、100 k Pa大气压力下对一台满足国五排放标准的高压共轨柴油机进行性能与排放试验,以研究排气温度、排气流量和海拔变化对NO_x转化率和NH₃泄漏量的影响。结果表明:在排气流量为350 kg/h情况下,NO_x转化率随排气温度升高呈现先增后减的趋势,不同温度下NO_x转化率最大差值为43.4百分点;NH₃泄漏量随着温度的升高大体上呈下降趋势,不同温度下NH₃泄漏量最大差值为328×10^-6;NO_x转化率随排气流量升高呈现先增后减的趋势,在250℃时,不同排气流量下NO_x转化效率最大相差21.5百分点;NH₃泄漏量随排气流量的增大而增加,在250℃时,不同排气流量下NH₃泄漏量最大差值为90.8×10^-6。相同工况下,海拔越高,NO_x转化率越高,NH₃泄漏量越小,大气压力为80和100 k Pa下NO_x转化率最大相差20.1百分点,NH₃泄漏量最大相差54.6×10^-6。     

铁路集装箱混合货物平衡装载布局优化模型与算法

铁路集装箱装载布局逐步发展成为在不同规格和不同类型货物混合平衡装载制约下追求装载空间容积和载重量综合利用率最大化问题，其研究对货物高效安全运输尤为重要。本文针对铁路集装箱混合货物平衡装载布局问题，给出铁路集装箱装后重心平衡和集重容许弯矩约束量化方法，以集装箱综合利用率最大化为优化目标，构建铁路集装箱混合货物平衡装载布局优化模型；区别于直接将货物构造为货物块的方法，给出了一种基于混合货物分类方法和待装货物结构判断指标的货物块单元构造方法，并设计一组货物块单元选择和放置方法及剩余空间更新规则，提出铁路集装箱混合货物平衡装载布局优化算法。算例结果表明：所提方法在保证集装箱装载空间容积和载重量的平均综合利用率不低于87%的同时，有92.8%和97.87%以上的概率满足装载重心平衡和集重容许弯矩约束，可有效提高货物块与剩余空间适配度，客观反映装载空间利用情况，并达到平衡装载要求，为铁路集装箱货物装载布局提供决策支持。     

隧道内不同间距双火源火灾试验及模拟研究

为了给隧道双火源事故中的人员疏散和应急救援提供参考，研究隧道内部双火源火灾条件下的燃烧行为和火场环境，搭建1∶10缩尺寸模型隧道，开展不同火源间距下的双火源油池火试验，研究燃烧速率、火焰形态和隧道内纵向温度分布；同时，采用PyroSim数值模拟的方法分析隧道内部双火源之间距底面高度0.1、0.15 m处的温度分布。试验结果表明：对于隧道内双火源火灾，燃烧速率受火源间距影响较大，当间距从2D(D为油盘边长)增加到8D时，燃烧速率从20.43 g·m^-2·s^-1下降至15.61 g·m^-2·s^-1，并逐渐接近单火源燃烧速率；燃烧过程中火焰相互倾斜，倾角会随着间距增加逐渐减小，由18.3°减小至13.7°。由于两火源之间相互限制，火源之间区域内的热量不断积聚，双火源间近顶板温度明显偏高；双火源外侧远端近顶板处纵向温度呈指数衰减规律，与单火源远端顶板温度分布规律保持一致，但温度衰减因子会随着双火源间距的增加逐渐变大。数值模拟结果表明：双火源之间温度分布呈现出凹形分布规律，随着距火源距离的增加，温度迅速下降，后逐渐保持稳定，但稳定区间内的温度仍然较高，会对人员造成伤害。双火源间距对火源之间的温度分布影响较大，随着间距增加，双火源之间的稳定温度逐渐下降，对人员疏散影响逐渐变小。双火源之间温度分布规律研究结果可为火灾初期被困人员的施救提供参考。     

基于非均匀发车间隔的大小交路时刻表优化模型

基于客流时空分布规律，考虑列车平均发车间隔、运行时间、最大载客量等约束条件，将列车在车站的停站时间与上、下车客流量相关联，建立城市轨道交通高峰时段基于非均匀发车间隔的大小交路时刻表优化模型，对乘客平均旅行时间及列车发车间隔平均偏离值进行协同优化。以某城市轨道交通线路实际运营数据验证模型的有效性。结果表明，优化后乘客在各个车站平均等待时间较优化前减少幅度为0.4%~13.1%，其中全线客流量较大的第7、8、9站优化幅度较为明显，分别为 11.7%、13.1%、11.9%。优化后列车在各个车站最大满载率较优化前降低幅度为1.8%~8.5%，且所有车站站台均无滞留乘客，体现了优化后列车运输能力与客流需求的良好匹配。灵敏度分析讨论了目标函数权重系数及列车平均发车间隔值对模型的影响，表明本模型具有良好的可用性及稳定性，能够为城市轨道交通列车时刻表优化提供参考。     

城市轨道交通差异化票价和补贴优化

为研究不同群体，即一般群体和特殊群体(老年人、残疾人、学生)的票价方案和补贴问题，本文考虑不同群体的差异性，以各群体的票价折扣率和列车开行间隔为决策变量，构建基于群体差异化的运营补贴优化模型，以社会福利最大化为目标，优化各群体的票价折扣率、企业的服务水平及政府的补贴额度，确保各群体获得合适的补贴，实现公共交通出行的公平性。综合考虑城市轨道交通运输能力约束、政府财政约束及不同群体票价折扣率约束，设计了基于模拟退火算法的求解算法。以长沙地铁2号线为例，分析比较不同群体的票价折扣率，提出基于列车运行计划的福利票价方案。研究结果表明，一般群体不享受折扣，残疾人4折优惠，老年人2折优惠及学生6折优惠，交通特殊群体的出行比分别提升了1.06%，2.86%及1.94%。政府在实施补贴政策时，可以通过不同群体的票价福利措施和企业的服务水平确定补贴额度。     

Development of distress condition index of asphalt pavements using LTPP data through structural equation modeling

Traditional pavement distress index such as the Pavement Condition Index (PCI) developed by U.S. Army Corps of Engineers determines coefficients of distresses based on subjective ratings. This study proposed an asphalt pavement distress condition index based on various types of distress data collected from the Long-Term Pavement Performance (LTPP) database through Structural Equation Modeling (SEM). The SEM method treated the overall distress index as a latent variable while various distresses were treated as endogenous and other influence factors such as age, layer thickness, material type, weather, environment and traffic, were exogenous observed variables. The SEM method modeled the contributions of various distresses as well as the influence of other factors on the overall pavement distress condition. Influences of age, layer thickness, material type, environment and traffic on the latent distress condition were in accordance with previous studies. Compared with previous attempts to model latent pavement condition index utilizing SEM method, more pavement condition measurements and influencing factors were included. Specifically, this study adopted the robust maximum likelihood estimator (MLR) to estimate parameters for non-normally distributed data and derived the explicit expression of latent variables with intercepts. A multiple regression prediction model was built to calculate an overall condition index utilizing those measured distress data. The established pavement distress index prediction model provided a rational estimation of weighting coefficients for each distress type. The prediction model showed that alligator cracking, longitudinal cracking in wheel path, non-wheel path longitudinal cracking, transverse cracking, block cracking, edge cracking, patch and bleeding were significant for the latent pavement distress index.     

Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications

Traffic signals, even though crucial for safe operations of busy intersections, are one of the leading causes of travel delays in urban settings, as well as the reason why billions of gallons of fuel are burned, and tons of toxic pollutants released to the atmosphere each year by idling engines. Recent advances in cellular networks and dedicated short-range communications make Vehicle-to-Infrastructure (V2I) communications a reality, as individual cars and traffic signals can now be equipped with communication and computing devices. In this paper, we first presented an integrated simulator with V2I, a car-following model and an emission model to simulate the behavior of vehicles at signalized intersections and calculate travel delays in queues, vehicle emissions, and fuel consumption. We then present a hierarchical green driving strategy based on feedback control to smooth stop-and-go traffic in signalized networks, where signals can disseminate traffic signal information and loop detector data to connected vehicles through V2I communications. In this strategy, the control variable is an individual advisory speed limit for each equipped vehicle, which is calculated from its location, signal settings, and traffic conditions. Finally, we quantify the mobility and environment improvements of the green driving strategy with respect to market penetration rates of equipped vehicles, traffic conditions, communication characteristics, location accuracy, and the car-following model itself, both in isolated and non-isolated intersections. In particular, we demonstrate savings of around 15% in travel delays and around 8% in fuel consumption and greenhouse gas emissions. Different from many existing ecodriving strategies in signalized road networks, where vehicles’ speed profiles are totally controlled, our strategy is hierarchical, since only the speed limit is provided, and vehicles still have to follow their leaders. Such a strategy is crucial for maintaining safety with mixed vehicles.     

Connected vehicle penetration rate for estimation of arterial measures of effectiveness

The Connected Vehicle (CV) technology is a mobile platform that enables a new dimension of data exchange among vehicles and between vehicles and infrastructure. This data source could improve the estimation of Measures of Effectiveness (MOEs) for traffic operations in real-time, allowing to perfectly monitor traffic states after being fully adopted. However, as with any novel technology, the CV adoption will be a gradual process. This research focuses on determining minimum CV technology penetration rates that would guarantee accurate MOE estimates on signalized arterials. First, we present estimation methods for various MOEs such as average speed, number of stops, acceleration noise, and delay, followed by an initial assessment of the penetration rates required to accurately estimate them in undersaturated and oversaturated conditions. Next, we propose a methodology to determine the minimum CV market penetration rates to guarantee accurate MOE estimates as a function of traffic conditions, signal settings, sampling duration, and the MOE variability. A correction factor is also provided to account for small vehicle populations where sampling is done without replacement. The methodology is tested in a simulated segment of the San Pablo Avenue arterial in Berkeley, CA. The outcomes show that the minimum penetration rate required can be estimated within 1% for most MOEs under a wide range of traffic conditions. The proposed methodology can be used to determine if MOE estimates obtained with a portion of CV equipped vehicles can yield accurate enough results. The methodology could also be used to develop and assess control strategies towards improved arterial traffic operations.     

集装箱堆场减少倒箱率方法研究

从集装箱堆场常见的倒箱原因进行分析，辅以实例利用搜索技术理论提出了出口箱箱位的合理分配以及减少倒箱率的措施。重点对集装箱堆场系统的优化进行了研究。