需求响应的集装箱班列时刻表优化及 Benders分解算法

充分考虑集装箱货物与集装箱班列在时间和数量方面的匹配关系，以集装箱货物送达目的站的总延误最小为目标，构建集装箱班列时刻表优化的线性混合整数规划模型.采 用Benders分解算法将原问题分解为确定集装箱货物与班列匹配方案的主问题，以及优化班列时刻表的子问题，通过求解子问题的对偶模型不断产生主问题的割平面.为克服割平面有效性较低的缺点，设计改进策略，使每次迭代产生多个割平面同时添加至主问题中.最后，通过算例验证模型和算法的有效性.结果表明：改进策略的运用有效提高了算法的计算效率，利用模型及算法得到的班列时刻表与集装箱货物的数量、时间分布之间具有较好的匹配性，制定的班列时刻表很好地响应了用户需求.     

基于KENTRACK的铁路沥青混凝土底砟层疲劳特性评价

重复动载疲劳损伤是沥青混凝土底砟层的破坏形式之一。本文建立了沥青混凝土底砟层的三维有限元分析模型,分析其在列车荷载作用下的受力变形特性。采用KENTRACK设计方法分析了沥青混凝土底砟层的疲劳寿命。结果表明:沥青混凝土底砟层等厚度替代基床表层的路基结构形式在列车荷载作用下基床表层的竖向动变形和振动加速度明显减小;沥青混凝土底砟层的层底拉应变在10×10^-6~90×10^-6,处于较低水平;沥青混凝土底砟层具有良好的疲劳耐久性,可用于工程实践。     

双块式轨枕外形质量快速检测系统研制及应用

SK?2型双块式混凝土轨枕是高速铁路无砟轨道结构中的重要预制件,单一生产厂日均产量达到800~1400根,但目前的人工检测方式无法满足双块式轨枕的出厂检验要求。本文提出的双块式轨枕外形质量快速检测系统可满足TB/T 3397—2015《CRTS双块式无砟轨道混凝土轨枕》的出厂检验要求,与双块式轨枕生产线相匹配,大大提高了检测效率,实现了双块式轨枕全参数、自动化、智能化检测。检测数据自动上传至生产管理平台,可对双块式轨枕生产质量进行跟踪管理。     

Optimal development of alternative fuel station networks considering node capacity restrictions

A potential solution to reduce greenhouse gas (GHG) emissions in the transport sector is the use of alternative fuel vehicles (AFV). As global GHG emission standards have been in place for passenger cars for several years, infrastructure modelling for new AFV is an established topic. However, as the regulatory focus shifts towards heavy-duty vehicles (HDV), the market diffusion of AFV-HDV will increase as will planning the relevant AFV infrastructure for HDV. Existing modelling approaches need to be adapted, because the energy demand per individual refill increases significantly for HDV and there are regulatory as well as technical limitations for alternative fuel station (AFS) capacities at the same time. While the current research takes capacity restrictions for single stations into account, capacity limits for locations (i.e. nodes) – the places where refuelling stations are built such as highway entries, exits or intersections – are not yet considered. We extend existing models in this respect and introduce an optimal development for AFS considering (station) location capacity restrictions. The proposed method is applied to a case study of a potential fuel cell heavy-duty vehicle AFS network. We find that the location capacity limit has a major impact on the number of stations required, station utilization and station portfolio variety.     

运营高铁车站黄土路基沉降特征及原因分析

针对黄土地区某高铁车站路基沉降病害问题,选取典型区域,采用PS-InSRA技术对变形区域进行监测,获取2017年2月至2019年6月的Sentinel-1A卫星影像数据并与现场勘测结果相结合,分析形变特征和趋势,以指导后续病害治理。结果表明:研究区域路基沉降主要发生在2017年5月至9月和2018年4月至8月两个时间段,春夏季沉降速率较大,秋冬季相对平稳;地基土含水率在13%~26%之间,在地下2 m和4 m为含水率增加速率临界深度,0~2 m范围内的含水率增加较快,2~4 m范围内的含水率增加速率减缓,4~10 m范围内含水率基本稳定;路基部位地基处理影响范围有限,路基侧沟外侧地基土干密度偏小,渗透系数偏大,路基沉降的主要原因为车站场坪地表汇水渗入地基引起路基黄土层湿化变形。     

齿轨铁路基础设施综合维修体系研究

根据齿轨铁路的工程特点,分析齿轨铁路基础设施综合维修的相关需求。借鉴国内既有铁路的综合维修模式,提出适合齿轨铁路的综合维修模式。进而对综合维修体系的组织机构设置及具体机构布点提出了建。     

汉巴南铁路兰渝联络线电分相设置方案研究

联络线电分相设置方案影响因素众多,且其设置与否对工程和运营的影响也较大。本文对汉巴南铁路兰渝联络线电分相设置方案进行研究,提出高速铁路设置关节式电分相联络线最短长度;对联络线电分相不同设置方案进行比选研究,并结合各方案的土建工程、信号系统、供电系统及限制因素提出布局优化措施,以期为联络线电分相合理设置与优化布局提供新思路。     

成昆铁路矮塔斜拉桥索梁锚固区模型试验研究北大核心

为研究铁路矮塔斜拉桥索梁锚固区的受力形式,以成昆铁路金沙江大桥为工程背景,针对该桥采用的新型梁顶混凝土锚固构造,通过缩尺模型试验研究其在不同荷载下的应力分布和开裂特征。结果表明:在斜拉桥成桥恒载索力作用以及最不利荷载组合索力作用下,C7锚固块更容易发生破坏,将其作为试验构件开展缩尺模型试验,发现锚固块在不同张拉荷载作用下张拉至设计索力的过程中,应变增幅基本上线性增加,卸载后同样呈线性减小,说明混凝土受力处在线弹性阶段,且应力在规范要求范围内。在试验荷载加载至140%设计索力时,锚固块前端倒角位置开始出现细小裂纹且随荷载的增加不断开展。当荷载卸载至0时,之前出现的裂缝随荷载的减小逐渐闭合,宽度肉眼不可见,表明该构造能够满足正常使用要求且具备足够的安全储备。     

大坡道米轨道床阻力及轨排稳定性研究

为研究大坡道米轨(齿轨)有砟轨道结构稳定性,通过建立米轨离散元和有限元轨排模型,分析该结构在不同坡度条件下道床阻力变化及在荷载作用下轨排纵、横向稳定性。研究表明:(1)受轨枕与道床之间正压力减小和道砟颗粒之间接触减弱的共同作用,随着坡度增大,轨枕道床纵、横向阻力逐渐降低,且降低幅度明显高于轨枕与道床间正压力的降低幅度;(2)随着坡度的不断增大,在纵向制动荷载作用下轨枕位移显著增大,且有砟道床整体稳定性逐渐降低;(3)综合考虑轨枕位移及有砟道床整体稳定性,建议米轨有砟轨道最大坡度不超过500‰;(4)在温度荷载及制动荷载作用下,为保证米轨铁路曲线段的横向稳定性,在坡度为250‰时,无齿轨段曲线半径≮700 m,有齿轨段曲线半径≮600 m。     

Prioritizing road extension projects with interdependent benefits under time constraint

Since transportation projects are costly and resources are limited, prioritizing or sequencing the projects is imperative. This study was inspired by a client who asked: “I have tens of approved road extension projects, but my financial resources are limited. I cannot construct all the projects simultaneously, so can you help me prioritize my projects?” To address this question, the benefits and costs of all the possible scenarios must be known. However, the impacts (or benefit) of road extension projects are highly interdependent, and in sizable cases cannot be specified thoroughly. We demonstrate that the problem is analogous to the Traveling Salesman Problem (TSP). Dynamic change in travel demand during construction is another aspect of the complexity of the problem. The literature is yet to provide efficient methods for large cases. To this end, we developed a heuristic methodology in which the variation of travel demand during the construction period is considered. We introduce a geometrical objective function for which a solution-finding policy based on “gradient maximization” is developed. To address the projects’ interdependency, a special neural network (NN) model was devised. We developed a search engine hybridized of Ant Colony and Genetic Algorithm to seek a solution to the TSP-like problem on the NN based on gradient maximization. The algorithm was calibrated and applied to real data from the city of Winnipeg, Canada, as well as two cases based on Sioux-Falls. The results were reliable and identification of the optimum solution was achievable within acceptable computational time.