Development of simulated driving cycles for light,medium, and heavy duty trucks: Case of the Toronto Waterfront Area

Driving cycles are an important input for state-of-the-art vehicle emission models. Development of a driving cycle requires second-by-second vehicle speed for a representative set of vehicles. Current standard driving cycles cannot reflect or forecast changes in traffic conditions. This paper introduces a method to develop representative driving cycles using simulated data from a calibrated microscopic traffic simulation model of the Toronto Waterfront Area. The simulation model is calibrated to reflect road counts, link speeds, and accelerations using a multi-objective genetic algorithm. The simulation is validated by comparing simulated vs. observed passenger freeway cycles. The simulation method is applied to develop AM peak hour driving cycles for light, medium and heavy duty trucks. The demonstration reveals differences in speed, acceleration, and driver aggressiveness between driving cycles for different vehicle types. These driving cycles are compared against a range of available driving cycles, showing different traffic conditions and driving behaviors, and suggesting a need for city-specific driving cycles. Emissions from the simulated driving cycles are also compared with EPA’s Heavy Duty Urban Dynamometer Driving Schedule showing higher emission factors for the Toronto Waterfront cycles.     

中日韩运营铁路隧道检测技术现状及发展趋势

我国运营铁路隧道总体规模巨大，传统隧道检测方式难以满足大规模运营隧道检测及时、高效的需求，融合隧道检测新技术、优化运营铁路隧道既有检测方式是运营铁路隧道检测降本增效的关键。基于以上问题，对中国、日本及韩国隧道检测技术进行调研，从图像类、探测类以及集成综合类3个方面梳理中日韩隧道检测技术发展现状。提出运营铁路隧道检测技术以快速综合检测、数据智能化判释、隧道状态协同评估为主的发展趋势，分析适用于我国运营铁路隧道实际情况的隧道检测模式，提出应重视铺轨前的隧道检测，确保隧道初始状态信息的全面和真实性，加快建设隧道状态信息库，基于快速、综合、智能化的隧道检测技术体系，实现运营期铁路隧道的动态周期检测，以实现运营隧道降本增效。     

Development of driving cycles for electric vehicles in the context of the city of Florence

Strong efforts are spent in automotive engineering for the creation of so called Driving Cycles (DCs). Vehicle DC development has been a topic under research over the last thirty years, since it is a key activity both from an authority and from an industrial research point of view. Considering the innovative characteristics of Electric Vehicles (EVs) and their diffusion on certain contexts (e.g. city centers), the demand for tailored cycles arises. A proposal for driving data analysis and synthesis has been developed through the review and the selection of known literature experiences, having as a goal the application on a EVs focused case study. The measurement campaign has been conducted in the city of Florence, which includes limited traffic areas accessible to EVs. A fleet of EVs has been monitored through a non-invasive data logging system. After data acquisition, time-speed data series have been processed for filtering and grouping. The main product of the activity is a set of DCs obtained by pseudo-randomized selection of original data. The similarity of synthetic DCs to acquired data has been verified through the validation of cycle parameters. Finally, the new DCs and a selection of existing ones are compared on the basis of relevant kinematic parameters and expected energy consumption. The method followed for the creation of DCs has been implemented in a software package. It can be used to generate cycles and, under certain boundary conditions, to get a filtered access to the measured data and provide integration within simulation environment.     

Lightweighting shipping containers: Life cycle impacts on multimodal freight transportation

Freight transportation by truck, train, and ship accounts for 5% of the United States’ annual energy consumption (U.S. Energy Information Administration, 2017a). Much of this freight is transported in shipping containers. Lightweighting containers is an unexplored strategy to decrease energy and GHG emissions. We evaluate life cycle fuel savings and environmental performance of lightweighting scenarios applied to a forty-foot (12.2 meters) container transported by ship, train, and truck. Use phase burdens for both conventional and lightweighted containers (steel reduction, substitution with aluminum, or substitution with high tensile steel) were compared to life cycle burdens. The study scope ranged from the transportation of one container 100 km to the lifetime movement of the global container fleet on ships. Case studies demonstrated the impact of lightweighting on typical multimodal freight deliveries to the United States. GREET 1 and 2 (Argonne National Laboratory, 2016a,b) were used to estimate the total fuel cycle burdens associated with use phase fuel consumption. Fuel consumption was determined using modal Fuel Reduction Values (FRV), which relate mass reduction to fuel reduction. A lifetime reduction of 21% in the fuel required to transport a container, and 1.4% in the total fuel required to move the vehicles, cargo, and containers can be achieved. It was determined that a 10% reduction in mass of the system will result in a fuel reduction ranging from 2% to 8.4%, depending on the mode. Globally, container lightweighting can reduce energy demand by 3.6 EJ and GHG emissions by 300 million tonnes CO₂e over a 15-year lifetime.     

热源变化影响下S-CO2布雷顿循环动态分析

文章基于能量守恒微分方程建立了改进的S-CO₂再压缩布雷顿循环动态模型,分析了船舶烟气温度和流量的变化对循环系统的动态响应。研究结果表明,热源温度和流量的降低导致循环系统的输出功以及循环效率降低;相对于热源流量,热源温度对循环系统的影响较大。     

基于BIM标准体系的铁路协同设计体系研究

随着物联网、云计算、大数据等前沿技术的不断进步,铁路行业正在迎来新的发展机遇。数字孪生铁路是以智能建造、智能装备、智能运营为核心的智能高铁技术应用数字环境,也是铁路工程全生命周期应用的数据基础。传统的设计方式中各专业内和专业间数据相对离散、逻辑关联性不高、成果不易维护且信息存在大量冗余,无法满足铁路智能化应用的要求。以京张客运专线BIM项目为载体,研究能够集中管理各专业设计资源、定制各专业设计参数交互流程、构建专业间数据层面逻辑关联、具有统一数据框架的协同设计体系。该体系强化了各专业间的联系,提升了设计质量,为工程数字化建设提供了数据结构组织有序、易于维护、动态可感知的数字孪生工程,同时也为勘察设计企业拓展工程全生命周期业务提供了可靠的技术保障。     

Modal analysis of real-time,real world vehicular exhaust emissions under heterogeneous traffic conditions

This study presents the characteristics of real world, real time, on-road vehicular exhaust emission namely, carbon monoxide (CO), nitric oxide (NO), hydrocarbons (HC), and carbon dioxide (CO₂) emitted under heterogeneous traffic conditions. Field experiments were performed on major category of vehicles in developing countries, i.e. two-wheelers, auto-rickshaws, cars and buses. The on-board monitoring was carried out on different corridors with varying road geometry. Results revealed that the driving cycle was dependent on the road geometry, with two lane mixed flow corridor having lot of short term events compared to that of arterial road. Vehicular emissions during idling and cruising were generally low compared to emissions during acceleration. It was also found that emissions were significantly dependent on short term events such as rapid acceleration and braking during a trip. Also, the standard emission models like COPERT and CMEM under predicted the real world emissions by 30–200% depending upon different driving modes. The on-road emissions measurements were able to capture the emission characteristics during the micro events of real world driving scenarios which were not represented by standard vehicle emission measured at laboratory conditions.     

Using a chassis dynamometer to determine the influencing factors for the emissions of Euro VI vehicles

In order to explore the influence of different factors on the emissions of heavy diesel vehicles, a chassis dynamometer was used to test and analyze a Euro VI standard heavy-duty diesel vehicle under different load, fuel, driving conditions, and resistance conditions. The full load condition was found to increase NOx emissions by about 0.107 g/km (30%) and the particulate matter (PM) by 0.003 g/km (18%) compared to the empty load condition. Compared with the China V diesel, the NOx emissions of the Beijing VI diesel were reduced by 0.065 g/km (18%), and PM decreased by 0.004 g/km (25%). The HC, CO, PM, and NOx emissions measured during the Chinese World Harmonized Transient Cycle (C-WHTC) were 0.002 g/km (27%), 0.0005 g/km (14%), 0.0024 g/km (15%), and 0.092 g/km (25%) higher, respectively, than those measured during the European Transient Cycle (ETC). The HC, CO, PM, and NOx emissions measured by using the test resistance were 0.002 g/km (28%), 0.001 g/km (25%), 0.003 g/km (18.7%), and 0.09 g/km (25.7%) higher, respectively, than those calculated with the recommended formula.     

圆钢管混凝土柱低周反复加载试验研究

为了研究钢管混凝土柱在低周反复荷载作用下组合材料横截面刚度对其性能的影响,以果园港二期工程上的钢管混凝土柱为原型,对3根钢管混凝土柱进行低周反复加载试验。通过控制试件钢管厚度进行物理模型试验,研究钢管厚度对钢管混凝土柱耗能性能、承载性能、强度退化、刚度退化、延性和变形能力的影响。试验结果表明:随着试件钢管厚度的增加,试件的能量耗散系数与等效黏滞阻尼系数均随之减小,试件的耗能能力随之变弱;钢管厚度越小,钢管混凝土柱试件的耗能性能越好。钢管越厚,对核心混凝土的约束作用就越强,强度退化就越弱,试件塑性变形能力就越好。钢管越厚,外包钢管对核心混凝土约束作用就越强,水平承载能力越高。     

优化造船流程,缩短船台周期

介绍了上船澄西船舶有限公司在推行分段总组造船法,发展预舾装技术、精度造船技术,提高分段、总组进坞(台)及下水前的安装完整性,从而最大限度发挥船坞(台)核心生产资源的作用方面取得的新进展.