故障救援情形下的地铁列车调度调整模型

基于给定的救援组织方案,以列车运行时间、备用列车加开位置和方向、客流量等为约束条件,以备用列车加开方案和列车到发时间为决策变量,以站台滞留人数与加开备用列车数的加权和最小为目标,构建故障救援情形下的地铁列车调度调整混合整数规划模型.对模型线性化后,采用商业软件CPLEX求解.以某地铁运营线路为例,以不固定和固定备用列车...     

组合方法加固璧山人民桥的设计与实践

重庆璧山县人民大桥加固过程中的两种加固方法的组合使用,既有新方法新技术的应用,又有传统加固方法的体现,能大幅度提高原桥承载能力,将原桥的荷载提高2个等级,技术及经济效益也相当好,说明在桥梁加固设计中几种加固方法的联合使用具有较好的实际应用前景.     

东茭嘴疏浚工程中的环保问题探讨

该文通过对东茭嘴疏浚工程可能产生的环境影响进行分析,介绍了在工程中采取的减少工程对环境造成影响的措施,并指出了仍然存在的问题及解决问题的方法。     

绿色集装箱港口节能减排策略综述

综述了绿色集装箱港口节能减排策略,总结了国内外针对在港船舶、场桥、集卡与岸桥节能减排的措施与减排效果量化方面的研究成果,提出了未来的研究方向。研究结果表明:船用替代燃料(包括液化天然气、生物燃料、新能源)减排效果明显,针对替代燃料动力船应用困难问题,未来可重点研究替代燃料配套设施建设时序、补贴政策确定等问题;船舶采用岸电技术依据各地区碳排放系数不同可减少48.0%~70.0%的船舶在泊CO₂排放,考虑岸电设施使用率低等问题,港口岸电定价、船舶与码头配套设施改造时序等问题成为未来研究重点;降低船速可减少8.0%~20.0%的船舶在港CO₂排放;降低船舶非生产等待时间及辅助作业时间,并不能显著降低船舶在港CO₂排放,后续还可进一步研究如何通过港口资源合理调度等方式减少船舶在港等待时间;设立硫排放控制区可减少33.0%~34.6%的SO₂排放,还可继续研究排放控制区对船舶运营与港口运营的影响;场桥、集卡与岸桥节能减排措施主要为设备改造及优化调度,未来可继续研究既有设施设备节能改造时序,并分析在港船舶与装卸设备各减排措施集成下的综合减排效果;新能源供电系统在港口中的应用尚处于起步阶段,未来可研究港口新能源电力系统设计方法,构建清洁低碳的港口能源体系。      

基于LM算法神经网络的PMSM转子位置估算

针对永磁同步电机控制中传统机械传感器容易故障或失效,常规无传感器转子位置估计方法实现复杂、计算量大、易受干扰等问题,提出了基于LM算法神经网络的永磁同步电机转子位置估算器.通过采集两相静止坐标系下电压、电流以及与转子位置相关联的数据集来创建估算器模型,针对标准BP神经网络算法收敛速度慢、效率低的问题,将采用LM算法对数...     

城市道路交通事故特征分析——以乌鲁木齐市为例

中国正处于快速城镇化进程中,交通事故呈现频发的趋势,并时常伴随着重大恶性事故,因此,对事故的分析与研究十分迫切而有必要.以乌鲁木齐市为例,对该市2007～2010年的交通事故作了分析与研究,得到了时间、空间等方面的分布特征,将有助于减少并预防城市道路交通事故.     

大功率空冷自增湿PEMFC温度控制方法

为研究大功率空冷自增湿质子交换膜燃料电池(PEMFC)温度控制对电堆输出性能的影响,分别采用模糊控制、PID控制、模糊-PID切换控制、自适应模糊PID控制对电堆进行试验测试.实验结果表明,不同控制方法在负载变化时的动态响应特性存在较大差异:模糊控制对电堆输出性能影响较大,在大电流输出时会造成明显的浓差极化;模糊控制、PID控制、模糊-PID切换控制在负载变化时动态响应存在较大的超调量,调节时间长;模糊自适应PID控制超调量小,调节时间短.与PID温度控制相比,自适应模糊PID温度控制超调量降低了75%,调节时间加快了20%.综合考虑调节时间、超调量、稳态误差、电堆输出性能等因素,自适应模糊PID温度控制有利于提高大功率空冷自增湿PEMFC输出特性.      

CFD Analysis of Ship-to-Ship Hydrodynamic Interaction

A numerical study of ship-to-ship interaction forces is performed using a commercial CFD code, and the results are compared with experimental data and with the results of a panel method analysis. Two ship models have been used in the interaction forces analysis: a tug and a tanker, advancing parallel to each other with different lateral distances and two different values of the fluid depth. Computations are carried out with four different flow models: inviscid and viscous flow with the free surface modeled as a rigid wall and inviscid and viscous flow with the deformable free surface. A fair agreement was obtained with available experimental data and results obtained by panel method. The influence of viscosity in the computations is found to be comparatively weak, while the wavemaking effects may be important, at small magnitude of the horizontal clearance.     

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.     

How household transportation expenditures have evolved in Canada: a long term perspective

In recent years, increasing recognition of the challenges associated with global climate change and inequity in developed countries have revived researcher’s interest towards analyzing transportation related expenditure of households. The current research contributes to travel behaviour literature by developing an econometric model of household budgetary allocations with a particular focus on transportation expenditure. Towards this end, we employ the public-use micro-data extracted from the Survey of Household Spending (SHS) for the years 1997–2009. The proposed econometric modeling approach is built on the multiple discrete continuous extreme value model (MDCEV) framework. Specifically, in our analysis, the scaled version of the MDCEV model outperformed its other counterparts. Broadly, the model results indicated that a host of household socio-economic and demographic attributes along with the residential location characteristics affect the apportioning of income to various expenditure categories and savings. We also observed a relatively stable transportation spending behaviour over time. Additionally, a policy analysis exercise is conducted where we observed that with increase in health expenses and reduction in savings results in adjustments in all expenditure categories.