改进传统港包机提高散装物料灌包效率

随着生产跨越式的发展以及货类结构的变化,原有灌包设备暴露出明显缺陷,灌包效率低,严重影响了装卸生产,介绍了对原灌包设备的软件及硬件进行改进:灌包机由两种卸料控制方式,提升为六种卸料控制方式,同时增设了散装物料下料辅助搅拌装置,该装置有效地保障了物料流动下泻,大大提高了灌包效率。     

国内外钣金与涂装创新创业现状分析

钣金与涂装是汽车售后市场的重要组成部分,为了解国内外钣金与涂装创新创业现状,文章采用问卷调查、实地考察、文献研究等方法进行了研究,分析得出以下结论:钣金与涂装设备产品更加环保、便利,工艺更加安全、高效,生产管理更加智能化、数据化,生产三废处理更加绿色环保,从业人员在工作中自制设备工具使操作变得更简易。通过对钣金与涂装行业创业的调查,发现汽车钣喷快修连锁化发展迅速,用户忠诚度、满意度稳中有升;钣喷维修小店机遇与挑战并存,在售后维修市场夹缝中求生存;技工院校钣喷创新创业教育已逐步展开。     

城市货运交通政策体系研究

由于受行业及部门分割的影响,我国城市货运交通政策往往缺乏必要的系统性和统一性,不仅不利于城市货运交通规划的编制与实施,还给城市物流发展带来负面影响。论述了城市货运交通政策的概念、目标、实施范围、政策评估及其基本内容;并结合国内外货运交通发展的经验案例,说明规划或政策的制定者们必须重新调整和认识货物流通中心的发展观念,用城市货运交通大系统的视角去审视货物流通中心发展面临的政策问题,结尾对我国城市货运交通一体化和货物流通中心发展政策的思考,指出必须加强货物流通中心发展政策与城市货运交通的必要有效的互动,从更高层面加强货运交通政策领域的研究工作。     

铁路32 m混凝土简支箱梁结构噪声试验研究

以32 m单线和双线单室混凝土简支箱梁为对象,通过噪声试验、结构有限元和声学有限元分析,研究箱梁结构噪声的声辐射特性、峰值频率产生的原因及评价方法.结果表明:列车通过桥梁时,离箱梁表面较远处的噪声级起伏不大,可采用稳态算法简化分析;混凝土箱梁的结构噪声主要分布在250 Hz以下,且随频率的增加而迅速衰减,因此理论预测时可将250 Hz作为截止频率;单线和双线箱梁的2个噪声峰值频率分别为63和160 Hz,以及50和315 Hz,二者均在第1个峰值频率处达到最大声压级,且此峰值频率处的噪声具有明显的有调性;不同箱室尺寸箱梁的结构噪声声辐射差异较大,车速并不是噪声的第一决定因素;混凝土箱梁结构噪声的峰值频率出现在声辐射效率和振动响应均较大处,因此应避免结构振动模态和空腔声学模态重合而导致空腔共鸣引起的噪声被放大;建议修订铁路噪声相关规范时,考虑混凝土箱梁低频结构噪声的危害.     

A framework for user- and system-oriented optimisation of fuel efficiency and traffic flow in Adaptive Cruise Control

Fully automated vehicles could have a significant share of the road network traffic in the near future. Several commercial vehicles with full-range Adaptive Cruise Control (ACC) systems or semi-autonomous functionalities are already available on the market. Many research studies aim at leveraging the potential of automated driving in order to improve the fuel efficiency of vehicles. However, in the vast majority of those, fuel efficiency is isolated to the driving dynamics between a single follower-leader pair, hence overlooking the complex nature of traffic. Consequently fuel efficiency and the efficient use of the roadway capacity are framed as conflicting objectives, leading to fuel-economy control models that adopt highly conservative driving styles.This formulation of the problem could be seen as a user-optimal approach, where in spite of delivering savings for individual vehicles, there is the side-effect of the deterioration of traffic flow. An important point that is overlooked is that the inefficient use of roadway capacity gives rise to congested traffic and traffic breakdowns, which in return increases energy costs within the system. The optimisation methods used in these studies entail high computational costs and, therefore, impose a strict constraint on the scope of problem.In this study, the use of car-following models and the limitation of the search space of optimal strategies to the parameter space of these is proposed. The proposed framework enables performing much more comprehensive optimisations and conducting more extensive tests on the collective impacts of fuel-economy driving strategies. The results show that, as conjectured, a “short-sighted” user-optimal approach is unable to deliver overall fuel efficiency. Conversely, a system-optimal formulation for fuel efficient driving is presented, and it is shown that the objectives of fuel efficiency and traffic flow are in fact not only non-conflicting, but also that they could be viewed as one when the global benefits to the network are considered.     

Dynamic charging infrastructure deployment for plug-in hybrid electric trucks

Inspired by the rapid development of charging-while-driving (CWD) technology, plans are ongoing in government agencies worldwide for the development of electrified road freight transportation systems through the deployment of dynamic charging lanes. This en route method for the charging of plug-in hybrid electric trucks is expected to supplement the more conventional charging technique, thus enabling significant reduction in fossil fuel consumption and pollutant emission from road freight transportation. In this study, we investigated the optimal deployment of dynamic charging lanes for plug-in hybrid electric trucks. First, we developed a multi-class multi-criteria user equilibrium model of the route choice behaviors of truck and passenger car drivers and the resultant equilibrium flow distributions. Considering that the developed user equilibrium model may have non-unique flow distributions, a robust deployment of dynamic charging lanes that optimizes the system performance under the worst-case flow distributions was targeted. The problem was formulated as a generalized semi-infinite min-max program, and a heuristic algorithm for solving it was proposed. This paper includes numerical examples that were used to demonstrate the application of the developed models and solution algorithms.     

Optimum routing of battery electric vehicles: Insights using empirical data and microsimulation

This study investigates the energy consumption impact of route selection on battery electric vehicles (BEVs) using empirical second-by-second Global Positioning System (GPS) commute data and traffic micro-simulation data. Drivers typically choose routes that reduce travel time and therefore travel cost. However, BEVs’ limited driving range makes energy efficient route selection of particular concern to BEV drivers. In addition, BEVs’ regenerative braking systems allow for the recovery of energy while braking, which is affected by route choices. State-of-the-art BEV energy consumption models consider a simplified constant regenerative braking energy efficiency or average speed dependent regenerative braking factors. To overcome these limitations, this study adopted a microscopic BEV energy consumption model, which captures the effect of transient behavior on BEV energy consumption and recovery while braking in a congested network. The study found that BEVs and conventional internal combustion engine vehicles (ICEVs) had different fuel/energy-optimized traffic assignments, suggesting that different routings be recommended for electric vehicles. For the specific case study, simulation results indicate that a faster route could actually increase BEV energy consumption, and that significant energy savings were observed when BEVs utilized a longer travel time route because energy is regenerated. Finally, the study found that regenerated energy was greatly affected by facility types and congestion levels and also BEVs’ energy efficiency could be significantly influenced by regenerated energy.     

Social and spatial effects of transforming the private vehicle fleet in Brisbane,Australia

Transformation of the motor vehicle fleet has been an important feature of the world’s peak car phenomenon. Very few urban transport studies have explored such important changes in large urban cities. Using an innovative green vehicle datasets constructed for 2009 and 2014, this paper investigates the ongoing change in urban private vehicle fleet efficiency (VFE) in Brisbane. The spatial patterns of VFE change were examined with social-spatial characteristics of the urban area. The results showed that the social and spatial effect of VFE changes remain uneven over urban space. The inner urban areas have experienced higher level of VFE change, whilst people in the outer and oil vulnerable areas showed a low tendency in shifting to more efficient vehicles. The implication of VFE change for future household vehicle adoption was also evaluated based on a cost-benefit analysis of new vehicle technology costs and expected fuel savings for households that choose a fuel efficient vehicle. The results show that imposing a stronger national fuel economy target in the long term would accelerate evolution of vehicle fleets and oil vulnerability reduction in Brisbane.     

Have Emission Control Areas (ECAs) harmed port efficiency in Europe?

Ports in the European Union and North America have enforced environmental regulations on controlling SO_x and NOx emissions from ships in their coastal areas known as Emission Control Areas (ECAs). This study uses two-stage approaches to examine whether ECA regulations impact the efficiency of ports operating in such areas. First, port efficiencies are estimated using non-radial slacks-based measure (SBM) Data Envelopment Analysis (DEA) models. The efficiency scores estimated by the SBM DEA models are then regressed on explanatory variables, including the ECA factor, and macroeconomic indicators using bootstrapped truncated regression (BTR) models. Panel data is collected on countries in EU ECAs and non-ECAs regarding such input variables as capital and labor, with cargo as an output variable. The results indicate that ECA regulations can harm port efficiency, reflecting concerns of policy-makers and industrial managers: the average efficiency loss from an ECA designation amounts to 0.058–0.066 on a scale of 0–1, accounting for a 15–18% loss from ECA ports’ average efficiency scores.     

An integrated framework for assessing service efficiency and stability of rail transit systems

A well-designed service plan efficiently utilizes its infrastructure and ensures an acceptable level of service stability with consideration of potential incidents that disturb or disrupt the rail transit services. To perform service evaluation, an integrated process combining capacity, resource usage, and system reliability is required to quantify service efficiency and stability in a consistent way. This study adopts capacity-based indices, “capacity utilization” and “expected recovery time”, as the attributes for service efficiency and stability, and develops a comprehensive evaluation framework with three corresponding modules to incorporate capacity, service plan, and system reliability and maintainability simultaneously. The capacity analysis module computes the rail transit capacities under normal and degraded operations. The reliability module classifies and fits the proper reliability and maintainability distributions to the historical interruption data. The service efficiency and stability module analyzes the results of the previous two modules and evaluates the service efficiency and stability of rail transit service plans. Empirical results show that the established evaluation framework can not only evaluate the service efficiency and stability but also identify critical sections and time slots. This tool can help rail transit operators rapidly assess their operational changes and investment strategies related to efficiency and stability so as to provide efficient and stable services to their customers.