电务安全维修与大综合分散管理适应性探讨

针对电务专用管理要求,紧密围绕路局扩大再生产的攻关项点和任务目标,稳步推进电务劳动组织和维修体制改革,做到修程修制与劳动组织合理衔接,提出破解安全维修与分散管理的措施。     

通信设备用阀控式密封铅酸蓄电池的维护和管理

从维护和管理的角度出发,对影响蓄电池寿命的因素进行了分析,对如何提高电池的使用寿命进行了探讨,并根据日常的一些维护经验,对蓄电池的维护提出了建议。     

大跨径梁桥非连续施工对成桥影响效应分析

内蒙古某(85+6×150+85)m PC黄河特大桥冬季休工期(长达6个月),恰逢主梁施工至最大悬臂状态,需验算非连续施工阶段受力状态以保证安全合龙成桥。采用计算土弹簧刚度来模拟桩—土摩阻效应,以Maxwell模型模拟墩顶新型阻尼器的墩梁位移效应,建立连续成桥和非连续成桥的线性和非线性数值模型。结果表明,与连续施工成桥相比,长悬臂施工状态休工使梁端上挠增大,主梁位移变化明显;主梁纵向最大弯矩增大,箱梁混凝土上下缘应力累积减小。     

富水蚀变岩大断面高速铁路隧道开挖大变形控制技术

以富水花岗岩侵入蚀变带区域高速铁路隧道建设为背景,对隧道开挖围岩变形控制技术进行研究。运用隧道工程理论、数值模拟和现场监测等技术与方法,提出了从全断面开挖法、台阶法、CD法到CRD法的安全度逐渐增加的隧道开挖方法,确定了避免富水花岗蚀变岩进一步应变软化和力学参数弱化的隧道开挖支护结构形式及其参数,得出了适当加大预留变形量结合衬砌紧跟的施工工艺。实践表明,按研究出的开挖方法和支护方案进行施工,可以有效控制隧道围岩大变形而使变形快速收敛,能够减少侵限处理工作量,并确保富水花岗蚀变岩隧道开挖时围岩稳定和地下工程结构安全。     

大跨度连续梁桥施工新方法研究

基于大跨度连续梁桥的特点及某大桥施工时需要调整施工方法的实际情况,运用有限元分析软件,计算并比较了两种施工方法下结构受力情况及主梁线形变化状况。通过施工、设计及监控解决相关技术难点后,桥梁顺利合龙,并缩短了近1个月的工期,表明悬臂浇筑与支架现浇相接合这种施工方法是可行的。     

中心城区大跨度大断面隧道爆破施工技术

广深港客运专线深港隧道位于深圳市中心城区,由单洞双线过渡到双洞单线,采用矿山法施工。结合深港隧道工程实践,介绍在中心城区大跨度、大断面爆破施工技术。     

我国道路客运业的现状及发展对客车制造业的影响

本文对我国道路客运业的现状和特点进行了分析介绍,指出道路客运业向集约化、规模化发展,客运经营主体的资质、经营管理水平等需要进一步的提高。道路客运业的发展对客车制造企业提出了更多要求,但二者又是相互融合、共同发展的。     

大断面地铁车站隧道软弱围岩渐进破坏规律模型试验研究

以贵阳市地铁2号线阳明祠车站为背景,采用室内模型试验模拟大断面地铁车站施工过程中隧道塌方破坏过程,明确施工期间大断面隧道塌方破坏过程机制,对比分析围岩和路面的变形。结果表明:通过围岩重力作用模拟隧道施工过程中塌方过程,与实际塌方过程基本吻合,弥补了常规加载破坏的不足;围岩渐进破坏过程表现为裂隙出现-裂隙发展-裂隙贯通-围岩塌方,支护渐进破坏过程表现为变形缓慢增加-变形快速增加-裂缝快速发展-支护破坏;围岩渐进破坏与支护渐进破坏相互作用,共同发展;在实际施工过程中,当支护变形大幅增加时,应增加支护强度,同时还应及时注浆、打设长锚杆,以减缓围岩裂隙发展,阻断围岩渐进破坏过程。     

Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach

Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.