The economics of double-hulled tankers

A cost-benefit analysis is conducted on the double-hull requirements for oil tankers in United States' waters contained in the U.S. Oil Pollution Act of 1990. The benefits of reduced spillage are compared with the increased construction and operations costs of double-hulled vessels. In the most probable scanario, the expected benefits are only 20% of the expected costs. Double-hulls do not even show a positive net present value with the most favorable assumptions. Even if double-hulls prevent all of the spillage that occurs due to collisions and groundings, and that the damage per gallon spilled is as extensive as in the ‘Exxon Valdez’ incident, the benefits are under half of the costs.     

Efficiency and ecological characteristics of a VCR diesel engine

Compression ratio (CR) is a design parameter with highest influence on efficiency, emission and engine characteristics. In conventional internal combustion (IC) engines, the compression ratio is fixed and their performance is, therefore, a compromise between conflicting requirements. One fundamental problem is that drive units in the vehicles must successfully operate at variable speed and loads and in different ambient conditions. If a diesel engine has a fixed CR, a minimal value must be chosen that can achieve a reliable self-ignition when starting the engine in cold start conditions. In diesel engines, variable compression ratio (VCR) provides control of peak cylinder pressure, improves cold start ability and low load operation, enabling the multi-fuel capability, increase of fuel economy and reduction of emissions. By application of VCR and other mechanisms, the optimal regime fields are extended to the prime requirements: consumption, power, emission, noise, etc., and/or the possibility of the engine to operate with different fuels is extended. An experimental Diesel engine has been developed at the Faculty of Engineering, University of Kragujevac. The changes of CR are realized by changing the piston chamber diameter. Detailed engine tests were performed at the Laboratory for IC engines. Special attention has been given to decrease of fuel consumption and exhaust emissions. An optimal field of CR variation has been determined depending on the given objectives: minimal fuel consumption, minimal nitric oxides, and particulate matter emissions, etc.     

机械电子技术在未来铁道车辆中的应用与发展(续完)

倾摆方式的引入显现出冰山的一角,一旦主动控制系统被铁道车辆所采用,那么引进其他主动控制系统从技术方面讲将变得越来越简单。在转向架和车体之间的倾摆系统是一种特殊的二系主动悬挂系统。因此本文接下去将探讨如何将二系主动悬挂系统进行推广,基本目的在于改善由于轨道不平顺带来的干扰,也     

Windows CE操作系统在机车显示器上的应用研究

介绍Windows CE操作系统的特点,阐述了将嵌入式操作系统Windows CE应用在机车显示器上的整个开发过程,并对其应川结果进行了总结。     

用Morlet小波变换研究舰船横摇垂荡耦合特性

本文探索了用小波变换方法对舰船横摇垂荡非线性耦合动力学特性的研究.对于考虑与垂荡二次耦合的舰船横摇方程,用Morlet小波变换分析其摇摆响应动力学特性,研究分析了船舶在几种典型波浪中的状况:稳定区域中的横摇回复和稳态横摇;非稳定区域的横摇发散;以及混沌现象.研究表明,通过小波变换所特有的时频窗,对横摇响应小波变换系数的模和相等信息进行分析,可以获得船舶横摇-垂荡耦合非线性动力学幅值和频率的各种典型特征.     

A new approach for improving the performance of freight train timetabling of a single-track railway system

A new approach for improving the performance of freight train timetabling for single-track railways is proposed. Using the idea of a fixed-block signaling system, we develop a matrix representation to express the occupation of inter- and intra-station tracks by trains illustrating the train blocking time diagram in its entirety. Train departure times, dwell times, and unnecessary stopping are adjusted to reduce average train travel time and single train travel time. Conflicts between successive stations and within stations are identified and solved. A fuzzy logic system is further used to adjust the range of train departure times and checks are made to determine whether dwell times and time intervals can be adjusted for passenger and freight trains at congested stations to minimize train waiting times. By combining manual scheduling expertise with the fuzzy inference method, timetable efficiency is significantly improved and becomes more flexible.     

VMT, energy consumption, and GHG emissions forecasting for passenger transportation

Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998-2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.     

Physical environments influencing bicyclists’ perception of comfort on separated and on-street bicycle facilities

This study investigates the impacts of physical environments on bicyclists’ perceptions of comfort on separated and on-street bicycle facilities. Based on a field investigation conducted in Nanjing, China, we find that physical environmental factors significantly influencing bicyclists’ perception of comfort on the two types of facility. Cyclists’ comfort is mainly influenced by the road geometry and surrounding conditions on physically separated paths while they pay attention to the effective riding space and traffic situations on on-street bicycle lanes.     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.