Influence of oxygenate content on particulate matter emission in gasoline direct injection engine

The relationship between the oxygen content in gasoline and the particulate emission (particle number and weight) was investigated. In order to study the influence of the engine configuration on the particulate emission, four vehicles were tested in which the following systems were installed: Vehicle 1 was equipped with direct injection system which uses central mounted outwardly opening injectors. Vehicle 2 and 3 used direct injection with a side mounted multihole injectors and Vehicle 4 had port fuel injection system. Methyl tert-butyl ether (MTBE) was used as the oxygen booster. The oxygen content in the gasoline was varied from 1 to 3 wt%, which corresponds with an MTBE dosage from 3.55% to 16.11%. This study used fuel that contained the same octane number with a 2% oxygen content without oxygen components, and it was used as the reference fuel in order to distinguish the effect of the oxygen content increases and the octane boosts that result from the MTBE. All vehicle tests were performed on a roller type chassis dynamometer using the New European Driving Cycle (NEDC) and Federal Test Procedure-75 (FTP-75) cycle. The experiment results demonstrate that the oxygen content increases in the gasoline reduced the particulate emission in vehicles with direct injection engines. An equivalent phenomenon was observed in a vehicle with a port fuel injection engine, but its absolute particle number was much smaller than that of the gasoline direct injection engine. The amount of reduction of the particle number in the start (cold) phase of the test cycle was significant compared with the later (hot) phase engine operation. However, particulates were emitted even though the engine was fully warmed up, especially when the engine was highly loaded. Other factors such as fuel economy or other exhaust emissions were not significantly affected by the oxygen content.     

In-vehicle display HMI safety evaluation using a driving simulator

Recently, telematics services and in-vehicle display devices such as the CNS (Car Navigation System) have become new causes of traffic accidents. These accidents are caused by ‘Inattention’ from the increase of the driver’s mental workload while he/she is driving. The driver of a vehicle (except for emergency or police vehicles) must not use a hand-held mobile phone while the vehicle is moving. To address this problem, Australia, England, Italy, Brazil and some states in the US have banned the use of hand-held mobile devices during driving. However, there are no restrictions on the use of in-vehicle displays or on the display’s positions. The position of a navigation system in a vehicle should be assessed objectively, and the effect of the position on the driver’s attention should be studied. Some existing research reports that in-vehicle distraction not only leads to reduced speeds and more frequent lane switching, but also more gazing by the driver to the centre of the road. In this study, to develop an assessment method and to propose the proper position of a CNS, an experiment is carried out in a driving simulator environment. Different methods to track the gaze and physical parameters of the driver are used for HMI (Human-Machine Interface) assessment. The experiment is carried out in a driving simulator to observe the glancing distribution during driving according to the position of the navigation system. Fourteen subjects participated in this experiment. Changes in subjects’ physiological signals and glancing distribution rates were collected.     

Predicting auto-ignition characteristics of RCCI combustion using a multi-zone model

The objective of new combustion concepts is to meet emission standards by improving fuel air mixing prior to ignition. Since there is no overlap between injection and ignition, combustion is governed mainly by chemical kinetics and it is challenging to control the phasing of ignition. Reactivity Controlled Compression Ignition (RCCI) combustion aims to control combustion phasing by altering the fuel ratios of the high- and low octane fuel and injection timings. In this study the dual fuel blend is prepared with gasoline and diesel fuels. The applied injection timings of the diesel are very early (90 to 60° CA bTDC). In the detailed reaction mechanism, n-heptane and iso-octane represent diesel and gasoline fuel, respectively. A multi-zone model approach is implemented to perform RCCI combustion simulation. Ignition characteristics are analyzed by using CA50 as the main parameter. In the experiments for the early direct injection (DI) timing advancing the injection time results in a later ignition. Qualitatively, the trend effect of the diesel injection timing and the effect of the ratio gasoline/diesel are captured accurately by the multi-zone model.     

Three-speed transmission system for purely electric vehicles

This paper discusses the necessity of using a transmission system to improve the energy efficiency of purely electric vehicles (EVs). The energy efficiency of an electric motor varies at different operating points to meet the output power demand. The three gear ratios of a transmission system can maintain the motor speed within a stable region with relatively high energy efficiency, while various vehicle speeds are needed. This work is based on a light EV prototype. The optimized gear ratios of this transmission result in a considerably reduced energy consumption of 9.3% compared with conventional EVs with single-speed reducers under the condition of the Urban Dynamometer Driving Schedule driving cycle. Thus, the transmission system is necessary to improve the energy efficiency of EVs.     

Real-time vision-based blind spot warning system: Experiments with motorcycles in daytime/nighttime conditions

This paper describes a real-time vision-based blind spot warning system that has been specially designed for motorcycles detection in both daytime and nighttime conditions. Motorcycles are fast moving and small vehicles that frequently remain unseen to other drivers, mainly in the blind-spot area. In fact, although in recent years the number of fatal accidents has decreased overall, motorcycle accidents have increased by 20%. The risks are primarily linked to the inner characteristics of this mode of travel: motorcycles are fast moving vehicles, light, unstable and fragile. These features make the motorcycle detection problem a difficult but challenging task to be solved from the computer vision point of view. In this paper we present a daytime and nighttime vision-based motorcycle and car detection system in the blind spot area using a single camera installed on the side mirror. On the one hand, daytime vehicle detection is carried out using optical flow features and Support Vector Machine-based (SVM) classification. On the other hand, nighttime vehicle detection is based on head lights detection. The proposed system warns the driver about the presence of vehicles in the blind area, including information about the position and the type of vehicle. Extensive experiments have been carried out in 172 minutes of sequences recorded in real traffic scenarios in both daytime and nighttime conditions, in the context of the Valencia MotoGP Grand Prix 2009.     

Factors Affecting Disaster Preparedness,Response, and Recovery Using the Community Capitals Framework

Abstract

Disaster research often focuses on how and why communities are affected by a discrete extreme event. We used the community capitals framework to understand how community characteristics influence their preparedness, response to, and recovery from successive or multiple disasters using the 1964 Good Friday Earthquake and the 1989 Exxon Valdez Oil Spill as case studies. This study assesses community response to these disasters by reviewing published literature on impacts to create profiles for six communities and by identifying community capitals before and during these disasters, and throughout the long-term recovery. While the presence of rich natural capitals commonly contributed resources to pre-disaster planning and long-term recovery, restriction of resource access immediately following the disasters was detrimental to many communities. Communities with strong political, social, and financial capitals tended to fare better immediately following disasters, enabling longer-term processes of transformation or recovery. However, in some communities the oil spill undermined these capitals more than the earthquake and resulting tsunami. In understanding how use and reliance on community capitals can lead to varied recovery success from different kinds of disasters, these findings can help coastal managers and planners prepare for future disasters.     

Operational performance evaluation of major container ports in the Asia-Pacific region

If international container ports are to gain a proper appreciation of their various advantages, disadvantages and potential opportunities in a globally competitive environment, it is essential that they conduct effective evaluation of their operational performance. The present study applies five models of data envelopment analysis (DEA) to acquire a variety of complementary information about the operational efficiency of major container ports in the Asia-Pacific region and to identify trends in port efficiency. The study first establishes the causes of inefficiency on the basis of efficiency value analysis. Slack variable analysis is then used to identify potential areas of improvement for inefficient ports. This is followed by the utilization of return to scale analysis to assess whether each port is in a state of increasing, decreasing, or constant return to scale. Finally, a sensitivity analysis is conducted to identify which input or output variables have larger weights in terms of efficiency. The results provide valuable information for port managements in their attempts to establish competitive strategies for the future and to improve their resource utilization for ongoing improvements in operational efficiency.     

The polarization of global container flows by interoceanic canals: geographic coverage and network vulnerability

It is widely acknowledged that the two major interoceanic canals of Suez and Panama play a central role in global shipping flows. However, this role has rarely been measured with precision both in terms of the geographic coverage and network topological properties of canal-dependent flows. Based on vessel movement data for containerships, this research clarifies the weight and share of canal-dependent flows globally and at the level of world regions, routes, and ports. It also estimates and maps the effects of removing canal-dependent flows from the network by means of graph-theoretical methods. While main results converge in showing a decreasing importance of canal shipping in the context of growing south-south trade exchanges, certain areas remain more dependent than others, such as Asia, Europe, and North America. The research also underlines factors of port vulnerability across the globe in relation with the two canals.     

Constructing Time‐Scaled Maps: Switzerland from 1950 to 2000†

Abstract

The article discusses the construction of a time‐scaled maps series for Switzerland documenting the shrinking of the country since 1950. It describes underlying network models and the mathematical approach employed for the necessary rescaling. In conclusion, it presents the maps and discusses how the country was shrunk by half.