轨道复合不平顺对无缝线路横向变形的影响分析

轨道复合不平顺会对行车的安全及稳定性产生较大影响,也是影响无缝线路横向变形的一个重要因素。为研究轨道复合不平顺对无缝线路的具体影响,通过构建三维轨道框架非线性有限元模型,采用轨道框架单点(或多点)位置发生横向及竖向位移来模拟复合不平顺状态,通过计算获取节点位移变化规律,进而分析轨道复合不平顺对无缝线路横向变形的影响作用。研究结果表明,轨道的复合不平顺会对无缝线路的横向变形产生显著的影响;当线路出现三角坑等类似病害时,其节点位移变化更为显著,在无缝线路的日常养护维修中应尤为注意。     

复杂城市环境泥水盾构泥浆绿色处理技术分析

泥水平衡盾构法修建隧道,在施工阶段会产生大量的废浆,如果废浆没有得到科学、妥善的处理,对环境的污染是无法估计的。本文以新建京张高铁清华园隧道工程为依托,结合在城市复杂繁华地区施工场地狭小、泥浆处理难度大等工程难题,对盾构掘进产生的废弃泥浆绿色处理技术进行了适应性研究,分析了综合处理之后泥浆循环利用的应用效果。泥水处理设备、压滤设备及离心设备相结合的泥浆综合处理技术,有效地实现了盾构施工"零排放",为今后类似施工条件的工程提供了技术参考。     

Data dependent input control for origin–destination demand estimation using observability analysis

In this paper, we address the observability issue of static O–D estimation based on link counts. Unlike most classic observability analyses that relied only on network topological relationships, our analysis incorporates the actual values of input parameters, thus including network operational relations as well. We first analyze possible mathematical properties of an O–D estimation problem with different data input. We then propose a modeling approach based on mixed-integer program for selecting model input that ensures observability and estimation quality. Through establishing a stronger connection between observability analysis and the corresponding estimation problem, the proposed method aims to improve estimation quality while reducing reliance on erroneous data.     

基于前轮转角约束自适应模型预测控制的路径跟踪研究

针对在车辆行驶中较小的前轮转角无法充分利用路面附着能力,较大的前轮转角使得车辆的行驶稳定性差的问题,文章提出了一种前轮转角约束自适应模型预测方法。首先建立车辆的动力学模型,然后通过计算得到轮胎纵向力,最终得到车辆的前轮转角。将车辆的状态量与前轮转角自适应约束条件输入给模型预测控制器,输出车辆的前轮转角,实现对参考路径的跟踪。在Carsim和MATLAB平台上联合仿真,仿真结果表明前轮转角约束自适应模型预测控制的车辆相比固定转角约束的车辆具有较好的跟踪能力和稳定性。     

A real-time adaptive signal control in a connected vehicle environment

The state of the practice traffic signal control strategies mainly rely on infrastructure based vehicle detector data as the input for the control logic. The infrastructure based detectors are generally point detectors which cannot directly provide measurement of vehicle location and speed. With the advances in wireless communication technology, vehicles are able to communicate with each other and with the infrastructure in the emerging connected vehicle system. Data collected from connected vehicles provides a much more complete picture of the traffic states near an intersection and can be utilized for signal control. This paper presents a real-time adaptive signal phase allocation algorithm using connected vehicle data. The proposed algorithm optimizes the phase sequence and duration by solving a two-level optimization problem. Two objective functions are considered: minimization of total vehicle delay and minimization of queue length. Due to the low penetration rate of the connected vehicles, an algorithm that estimates the states of unequipped vehicle based on connected vehicle data is developed to construct a complete arrival table for the phase allocation algorithm. A real-world intersection is modeled in VISSIM to validate the algorithms. Results with a variety of connected vehicle market penetration rates and demand levels are compared to well-tuned fully actuated control. In general, the proposed control algorithm outperforms actuated control by reducing total delay by as much as 16.33% in a high penetration rate case and similar delay in a low penetration rate case. Different objective functions result in different behaviors of signal timing. The minimization of total vehicle delay usually generates lower total vehicle delay, while minimization of queue length serves all phases in a more balanced way.     

Validating and improving public transport origin–destination estimation algorithm using smart card fare data

Smart card data are increasingly used for transit network planning, passengers’ behaviour analysis and network demand forecasting. Public transport origin–destination (O–D) estimation is a significant product of processing smart card data. In recent years, various O–D estimation methods using the trip-chaining approach have attracted much attention from both researchers and practitioners. However, the validity of these estimation methods has not been extensively investigated. This is mainly because these datasets usually lack data about passengers’ alighting, as passengers are often required to tap their smart cards only when boarding a public transport service. Thus, this paper has two main objectives. First, the paper reports on the implementation and validation of the existing O–D estimation method using the unique smart card dataset of the South-East Queensland public transport network which includes data on both boarding stops and alighting stops. Second, the paper improves the O–D estimation algorithm and empirically examines these improvements, relying on this unique dataset. The evaluation of the last destination assumption of the trip-chaining method shows a significant negative impact on the matching results of the differences between actual boarding/alighting times and the public transport schedules. The proposed changes to the algorithm improve the average distance between the actual and estimated alighting stops, as this distance is reduced from 806 m using the original algorithm to 530 m after applying the suggested improvements.     

Fractional-order-based ACC/CACC algorithm for improving string stability

Traffic flow optimization and driver comfort enhancement are the main contributions of an Adaptive Cruise Control (ACC) system. If communication links are added, more safety and shorter gaps can be reached performing a Cooperative-ACC (CACC). Although shortening the inter-vehicular distances directly improves traffic flow, it can cause string unstable behavior. This paper presents fractional-order-based control algorithms to enhance the car-following and string stability performance for both ACC and CACC vehicle strings, including communication temporal delay effects. The proposed controller is compared with state-of-the-art implementations, exhibiting better performance. Simulation and real experiments have been conducted for validating the approach.     

浅埋顶管沉井周边土体的三维破坏形状及沉降研究

为研究顶管沉井及周边土体在顶进力作用下的形变范围与大小，以加固旋喷桩作为沉井周围加固体建立ABAQUS软件计算模型，并将模拟结果与工程实例、PLAXIS 3D软件所得结果进行对比分析。同时，采用广州地区花岗岩残积土进行室内沉井模型试验，并通过试验结果对数值模拟结论进行验证，得出结论如下： 1）在开挖基坑前达到设计强度的旋喷桩能有效减小基坑周边土体塌陷变形、坑底隆起。2）在施加工作顶推力下，前侧主动区首先出现贯通裂缝，竖向位移斜率增大出现明显拐点；继续增大顶推力，土体位移会急剧增大导致地表沉降严重。3）对于后背土体，在顶推力作用下，地表破裂线的切线角度从0°逐渐增大至45°+φ/2，导致破裂范围也不断扩大；达到45°+φ/2处后，继续施加顶推力会导致短轴方向破坏范围扩大的速度较长轴方向的速度更快；三维空间中被动区破坏土体在地表处产生形状为椭圆的破坏面，椭圆长轴方向为顶推轴线方向，被动破坏体呈现为牛角状椭圆楔体。     

Caterham Seven 420R v Porsche 911 GT3 RS

在赛道作为一条经验法则,除非420R在打滑,否则其实它根本没用尽全力。它会转向不足——其实有时还挺有用的,如果你非要找到它的极限并再用力推过头一点点的话;但如果你就是入弯时对前胎要求过高那它就那么有帮助了。Seven之妙处在于驾驶者可以立刻知道当前的情况。你完全可以在入弯到     

VEGF-C、VEGFR-3和podoplanin在食管癌中的表达及其意义

目的观察血管内皮生长因子C(VEGF-C)及其受体3(VEGFR-3)和肾小球上皮细胞整合膜蛋白(podoplanin)在食管癌组织中的表达,分析其与肿瘤淋巴结转移的关系。方法免疫组织化学SP法检测76例食管癌组织中VEGF-C、VEGFR-3和podoplanin的表达及淋巴管密度(LVD)。结果食管癌VEGF-C表达阳性率为63.1%,VEGF-C的表达与食管癌的淋巴结转移、TNM分期有统计学意义(P<0.01,P<0.05),但与患者年龄、肿瘤大小及分化程度无关;癌旁组织淋巴管密度同淋巴结转移、VEGF-C阳性表达间有统计学意义(P<0.01,P<0.05),podo-planin LVD值与VEGFR-3 LVD值相比,具有统计学意义(P<0.01)。结论食管癌组织中VEGF-C表达与肿瘤TNM分期、淋巴管密度和淋巴结转移有关,VEGF-C表达越高,淋巴管密度越大,淋巴结转移可能性越高。癌旁组织LVD同VEGF-C的高表达及淋巴结转移密切相关,食管癌组织中podoplanin标记的淋巴管密度较VEGFR-3标记的淋巴管密度更为精确,是一种更为满意的淋巴管内皮特异性标志物。