Improvement in the estimation and back-extrapolation of CO2 emissions from the Irish road transport sector using a bottom-up data modelling approach

Road transport is a major source of CO₂ emissions in Ireland and accounts for almost 96% of the total CO₂ emissions from the transport sector. Following the recent adopted UNFCCC reporting guidelines on annual inventories [24/CP.19], this study applied the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2006 IPCC GLs) tier 3 approach to estimate CO₂ emissions from road transport at the vehicle category level, for the first time in Ireland. For this, disaggregated datasets were prepared based on year of vehicle registration and mileage since registration of the vehicle. Such an approach provided a more realistic national scenario in comparison to the use of average mileage degradation in emission calculations. This investigation comprised a recalculation of previous emissions estimates (1990–2012) and an estimation of CO₂ emissions in 2013 using a previously unavailable level of data disaggregation for vehicle mileage as well as using vehicle class specific data and an improved bottom-up estimation methodology in COPERT. Historic vehicle fleet data were restructured, annual mileage data were estimated in relation to the fleet data and back extrapolated using a regression approach.The results showed that the mileage degradation was not only subject to fuel technology, engine size, and age but also the emissions class and vehicle category. It was also observed that the disaggregated level of data provided a different CO₂ emissions split among the vehicle categories than that of previous estimations which were based on an aggregated level of data. Previous emissions inventories (1990–2012) were shown to have underestimated the share from diesel fuelled passenger cars by more than 56% in 2012. Diesel fuelled passenger cars were also found to account for the majority of CO₂ emissions from road transport activities in Ireland in 2013. The level and trend assessment showed that emissions from Euro-II and Euro-III classed vehicles especially for passenger cars, which have a significant contribution to the total emission in 2013 have caused an increase in fleet level emissions in Ireland. In addition, the results also showed that the emissions share from Light Duty Vehicles and Heavy Duty Vehicles were overestimated by previous investigations. This paper highlights the importance of the resolution of data used in emissions inventory preparation which may impact upon future projections and policy formulation. The findings of this investigation are also discussed in relation their implications for road transport policy, including carbon taxation and future policy options aimed at achieving EU emissions target in 2020.     

基于特征线的客车造型设计方法研究

以造型法则为基础,探讨一种以特征线为依托的设计方式,力求使客车的设计过程变得简单明了,使设计师的思路更加清晰。     

客车有限元建模方法概述

针对国内客车行业要求,在现有客车有限元建模技术的基础上,研究新的更切合客车产品特点的有限元建模方法,通过实际应用表明,这种方法是实用有效的。     

柔性神经网络及其在开关磁阻电机建模与仿真中的应用

作为一种新型的神经网络,创建了具有高度柔性特性的网络结构,给出了柔性神经网络(FNN)的基本原理,并将其应用于开关磁阻电机(SRM）的建模与仿真,展示了SRM新型建模方法的主要优点。FNN在实现系统功能的同时,需要较少的神经元和迭代循环,大大降低了网络的复杂性,加速了网络的学习与实时计算速度。     

矿产资源资产估价的动态收益现值法研究

应用随机时间序列理论和资产评估理论对矿产资源资产估价的收益现值法进行了研究,建立了待估矿产资源资产未来净收益的动态预测模型,提出了折现率历史数据的测算方法,据此,建立了与净收益预测模型相类似的未来折现率的动态预测模型。这些模型和方法为把现行的偏重于静态的收益现值法扩展为科学实用的动态收益现值法奠定了基础。     

分析工艺系统受力变形的有限元法

介绍了工艺系统受力分析有限元方法.在分析了工艺系统的受力特点后,建立 了有限元模型,并提出用等效刚度的虚拟结构作为机床结构模型,代替复杂的实际结构模 型.给出实例证明了该方法能够满足要求.     

带软时间窗的混合车队车辆路线问题的模型和算法研究

将典型的车辆路线问题扩展为综合考虑了客户具有间窗约束和中央仓库拥有多种类型配送车辆的情况。在构造了问题的数学模型后,着重阐述了求解本问题的TS算法设计过程。最后结合适应性记忆过程给出了TS算法的伪代码描述和一个算法。     

物流配送中心虚拟仿真设计方法

为了提高物流配送中心布局的客观性与运行效率,降低物流处理成本,分析了传统物流配送中心布局的缺点,研究了影响物流配送中心布局的各种随机因素,提出了物流配送中心布局的虚拟仿真设计方法.根据整理的物流配送中心布局实际参数,确定物流中心的规模、作业流程与平面布局,提出了配送中心布局方案,通过计算机仿真模拟了配送中心运行过程,计算了配送中心的空间利用率、作业能力、运行效率与运行成本,并评价了方案的优劣.实际应用结果表明:物流配送中心布局仿真虚拟设计方法精度高,对规划方案的模拟、优化与选择符合客观实际.     

PSPICE MODELLING OF LED

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Integrating parking behaviour in activity-based travel demand modelling: Investigation of the relationship between parking type choice and activity scheduling process

Traditionally, the parking choice/option is considered to be an important factor in only in the mode choice component of a four-stage travel demand modelling system. However, travel demand modelling has been undergoing a paradigm shift from the traditional trip-based approach to an activity-based approach. The activity-based approach is intended to capture the influences of different policy variables at various stages of activity-travel decision making processes. Parking is a key policy variable that captures land use and transportation interactions in urban areas. It is important that the influences of parking choice on activity scheduling behaviour be identified fully. This paper investigates this issue using a sample data set collected in Montreal, Canada. Parking type choice and activity scheduling decision (start time choice) are modelled jointly in order to identify the effects of parking type choice on activity scheduling behaviour. Empirical investigation gives strong evidence that parking type choice influences activity scheduling process. The empirical findings of this investigation challenge the validity of the traditional conception which considers parking choice as exogenous variable only in the mode choice component of travel demand models.