An inter‐Urban freight mode choice model

The Australian Railway Research and Development Organisation is conducting a study with one of its objectives being to determine factors affecting freight mode use. Part of this has included the development and calibration of freight mode choice models. This paper outlines the results obtained from the application of an Elimination‐by‐Aspects (EBA) model to this task. The paper describes the theoretical background to the EBA model, within the context of a general choice process, and then describes the results of the model when applied to three samples of shippers involved in regional freight transport.     

Sea space capacity and operation strategy analysis system

Sea space planning and congestion management is receiving more attention. However, little work on sea space capacity and strategy analyses can be found in the literature. Compared to other transportation systems, a sea space system has some special features that require consideration. The system capacity also depends on the pattern of traffic using the system. In this paper, we model a sea space as a directional network and capacity models for berthing areas, anchorage areas, fairways and their intersections, as well as the entire sea space system are developed. These models can be used to compute capacity for any given traffic pattern which can be extracted from vessel trip records or from traffic forecasts. To implement these models, a software system called Sea Space Capacity and Strategy Analysis System (SCSAS) has been developed in Visual C + + and is now being used in Singapore.     

A planning model for multiple‐mode transportation system operations

The problem of generating a set of “good” transportation alternatives during the early and intermediate stages of transportation planning is addressed in this paper. A linear programming model of a multi‐modal transportation system is developed. The model is run interactively to determine optimal operating levels for all modes for various transport policy decisions. The model described is a component of a composite network generation model incorporating dynamic changes. The linear programming component determines optimal operating policies for given points in time. The composite model incorporates these in a dynamic programming framework to determine optimal staged investment policies over several time periods.     

Estimating origin‐destination matrices from link volume counts: a simple intercity auto travel demand model for Sri Lanka

The cost of nation wide travel surveys is high. Hence in many developing countries, planners have found it difficult to develop intercity transportation plans due to the non availability of origin‐destination trip matrices. This paper will describe a method for the intercity auto travel estimation for Sri Lanka with link traffic volume data.

The paper outlines the rationale of selecting the district capitals of Sri Lanka as its “cities,” the methodology for selecting the intercity road network, determination of link travel times from express bus schedules and the location of link volume counting positions.

Initially, the total auto travel demand model is formulated with various trip purpose sub‐models. This model is finally modified to a simple demand model with district urban population and travel times between city pairs as the exogenous variables, to overcome statistical estimation difficulties. The final demand model has statistics within the acceptable regions.

The advantages of a simple model are discussed and possible extensions are proposed.     

“I can do perfectly well without a car!”

This article presents the results of a study exploring travellers’ preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travellers, (3) choice travellers with car as dominant alternative, and (4) car-dependent travellers. These preference segments differ in terms of the levels of involvement and cognitive effort in travel decision making, the travel consideration-set and underlying motivations. The study showed that for most people there is more to travel than getting from point A to point B, and that there is considerable heterogeneity in middle-distance travel preferences. Policy implications for reducing the need for travel and promoting a modal shift from car to other travel modes are discussed.     

Thermal Model for Square Lithium-ion Battery Pack

首先通过最小二乘法对方形锂离子电池组中单体电池的比热容、流道材料的导热系数和自然冷却条件下的综合换热系数进行了估计;然后根据热边界层理论确定了强制冷却条件下电池冷却流道表面局部综合换热系数的计算式;最后根据电池组的结构特点和冷却方式,建立了电池组的一维瞬态传热模型.该模型能根据电池组当前的环境温度、运行负荷、冷却强度和初始荷电状态实时预测电池组中各单体电池的运行温度.在Arbin试验台架上测量了144V/8A·h方形锂离子电池组在不同运行工况下单体电池的温度分布,并与模型仿真结果进行了对比,结果表明模型仿真的最大误差不超过1℃,满足混合动力系统性能仿真和电池组管理策略优化的精度要求.     

燃料电池发动机空气过滤器的实验与仿真

基于FLUENT软件,通过用户自定义函数(UDF)给定滤芯吸附SO2的约束条件,对过滤器的流体力学及化学吸附特性进行了仿真;仿真得到的SO2穿透曲线与实验结果吻合较好,所建模型能可靠地预测滤芯使用寿命.在此基础上对过滤器结构进行改进,结果表明,通过在化学滤芯上增加导流板可改善吸附层出现“死区”、“短路”的现象,从而提高滤芯的性能和使用寿命.     

基于组合预测模型的世界海运周转量预测分析

世界海运周转量是衡量未来航运市场运力需求的直接体现,在确定航运市场和船舶市场的发展趋势方面具有关键作用。针对世界海运周转量受到众多复杂因素影响的现实,基于传统的单个预测方法,分别采用时间序列、灰色系统、神经网络方法对世界海运周转量进行预测,然后再对单个预测方法进行加权组合,建立组合预测模型进行海运周转量的预测,预测结果表明:组合预测模型能够得到更加可靠的结果。     

基于广义回归神经网络与遗传算法的玻璃钢渔船船型要素优化研究

利用神经网络的非线性拟合能力,建立了基于广义回归神经网络的"船型要素-船体阻力"数学模型,提高了模型的拟合精度。同时结合遗传算法的非线性寻优能力,利用改进的遗传算法完成了船型要素的优化设计。优化结果可以作为玻璃钢渔船初步设计的技术参考。     

浅析地铁盾构隧道的施工测量

以南京地铁南北线一期工程许府巷-玄武门区间隧道的盾构施工为例，介绍了地铁盾构隧道的施工测量的特点以及测量的内容及方法。