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.     

Sheet metal forming simulation considering die deformation

Due to environmental concerns and safety regulations in the automotive industry, the development of strong and lightweight cars has been a hot issue in the last decade. One solution for this purpose would be to use high-strength steel (HSS) and advanced high-strength steel (AHSS). These materials can make the car lighter while maintaining the crash resistance of the vehicle. HSS and AHSS have more resistance force in the die structure compared with conventional steel due to their higher yield and tensile strength and thus, these materials have a greater effect on die deformation during the sheet metal forming process. As a result, die deformation can affect the blank sheet’s drawn pattern, strain, and stress as well as springback. This study presents a sheet metal forming simulation that considers die deformation. The simulation process was compared with conventional simulation methods. Our results indicate that the sheet metal forming simulation with die deformation consideration provides useful information on the die structure as well as formability and springback.     

Surveillance and Poaching on Inshore Reefs of the Great Barrier Reef Marine Park

The Great Barrier Reef (GBR), Australia, is managed under the GBR Marine Park Act (1975) and is seen as a shining example of marine resource management. The principle tool of management is zoning for multiple use. We examined surveillance and illegal fishing around two inshore islands (Magnetic and Orpheus) of the GBR Marine Park in 2000/2001. Both islands are near Townsville, the largest city adjacent to the GBR. Surveillance effort was low, with vessels present on only 16% of days of the year. Measurable but low levels of illegal recreational fishing occurred within no-take zones. Levels decreased with increasing surveillance effort. Thus zoning was not completely successful in protecting fish targeted by fisheries, even within the most highly enforced sections of the Park. The expansion of no-take zones in 2004 from 4.6% to 33.4% of the area of the 358,000 km2 Park represents a considerable challenge for future surveillance and enforcement.     

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.     

Climate change projections for variables affecting road networks in Europe

Global climate change will affect road networks during this century. The effects will be different in various parts of the world due to differences in local climate change and in the structure and properties of roads. In this paper, climate change projections are presented for climate variables that are most likely to affect the long-term performance of road networks in Europe. We apply four regional climate simulations up to the year 2100 using two plausible future emission scenarios. The results show that the changing climate will require significant adaptation measures in the near future in order to maintain the operability of the European road network.     

How tube strikes affect macroscopic and link travel times in London

Abstract

The purpose of this study was to investigate the impact of the five strikes on the London Underground (metro) rail system, which occurred in 2009 and 2010, on macroscopic and road link travel times. A consequence of these strikes was an increase in road traffic flows above usual levels. This provides an opportunity to observe the operation of the road network under unusually high flows. The first objective involves the examination of strike effects on inbound (IT) and outbound traffic (OT) within central, inner and outer London. Travel time data obtained from automatic number plate recognition cameras are used within the first part of the analysis. The second more detailed objective was to investigate in spatio-temporal effects on travel times on five road links. Correlation analyses and general linear models are developed using both traffic flow and travel time data. According to the results of the study, the morning IT had approximately twice as much delay as the OT. Central London experienced the highest delays, followed by inner and outer London. As would be expected, the unique full-day strike in 2009 yielded the worst impact on the network with the highest percentage increase in total travel time (60%) occurring during the morning peak in the IT in inner London. The results from the link-level analysis showed statistical significance amongst the examined links indicating heterogeneous effects from one link to another. It was also found that travel time changes may be more effectively captured through time-of-day terms compared to hourly traffic flows.     

Combined effect of boost pressure and injection timing on the performance and combustion of CNG in a DI spark ignition engine

There is an increasing interest in supercharging spark ignition engines operating on CNG (compressed natural gas) mainly due to its superior knock resisting properties. However, there is a penalty in volumetric efficiency when directly injecting the gaseous fuel at early and partial injection timings. The present work reports the combined effects of a small boost pressure and injection timing on performance and combustion of CNG fueled DI (direct injection) engine. The experimental tests were carried out on a 4-stroke DI spark ignition engine with a compression ratio of 14. Early injection timing, when inlet valves are still open (at 300°BTDC), and partial injection timing, in which part of the injection occurs after the inlet valves are closed (at 180°BTDC), were varied at each operating speed with variation of the boost pressure from 2.5 to 10 kPa. A narrow angle injector (NAI) was used to increase the mixing rate at engine speeds between 2000 and 5000 rpm. Similar experiments were conducted on a naturally aspirated engine and the results were then compared with that of the boosting system to examine the combined effects of boost pressure and injection timing. It was observed that boost pressure above 7.5 kPa resulted in an improvement of performance and combustion of CNG DI engine at all operating speeds. This was manifested in the faster heat release rates and mass fraction burned that in turn improved combustion efficiency of the boosting system. An increased in cylinder pressure and temperature was also observed with boost pressure compared to naturally aspirated engine. Moreover, the combustion duration was reduced due to concentration of the heat release near to the top dead center as the result of the boost pressure. Supercharging was also found to reduce the penalty of volumetric efficiency at both the simulated port and partial injection timings.     

Cooperative control for friction and regenerative braking systems considering dynamic characteristic and temperature condition

The braking system of hybrid electric vehicle (HEV) is composed of friction and regenerative braking system, meaning that braking torque is generated by the collaboration of the friction and regenerative braking system. With the attributes, there are two problems in the HEV braking system. First, rapid deceleration occurs due to dynamic characteristic difference when shifting the friction and regenerative braking systems. Second, the friction braking torque alters with temperature because the friction coefficient changes with the temperature. These problems cause the vehicle to be unstable. In this paper, the concurrence control and compensation control were proposed to solve these problems. And also, the concurrence control and compensation control were combined for the stability of the braking system. In order to confirm the effect of these control algorithms, the experiment and simulation were conducted. Consequently, it was confirmed that the control algorithm of this study improved the vehicle safety and stability.     

Safety benefits of integrated pedestrian protection systems

This study developed a methodology for evaluating the effectiveness of an integrated pedestrian protection system (IPPS) based on simulations. The proposed IPPS consists of active and passive vehicular systems for protecting pedestrians, including a pedestrian warning information system (PWIS), an active hood lift system (AHLS), and pedestrian airbag system (PAS). Two simulation methods were applied in the proposed methodology: a driving simulation and a finite element simulation. A driving simulator was used to obtain the change in collision speed, which is a key parameter for evaluating driving behavior when a PWIS is applied. In addition, a well-known simulator for finite element analysis, LSDYNA was used to simulate the impact of a pedestrian on a vehicle hood in a pedestrian-vehicle collision. The head injury criterion (HIC), which is an outcome of LS-DYNA simulations, is a major parameter for evaluating passive safety systems. The probability of pedestrian fatalities by collision speeds and HICs were estimated to quantify the safety benefits of an IPPS based on the statistical analyses. The results showed that an IPPS is capable of reducing pedestrian fatalities by approximately 90 % associated with jaywalking in the midblock and walking on the roadside. The findings of this study can be used to boost the development of various vehicular technologies for pedestrians. The results can be effectively used for policy making and deriving legislative requirements associated with advanced vehicular technologies for enhancing pedestrian safety.     

Activity space estimation with longitudinal observations of social media data

In this paper, we demonstrate the use of an inexpensive and easy-to-collect long-term dataset to address the problems caused by basing activity space studies off short-term data. In total, we use 63,114 geo-tagged tweets from 116 unique users to create individuals’ activity spaces based on minimum bounding geometry (convex hull). By using polygon density maps of activity space, we found clear differences between weekday and weekend activity spaces, and were able to observe the growth trajectory of activity space over 17 weeks. In order to reflect the heterogeneous nature of spatial behavior and tweeting habits, we used Latent Class Analysis twice. First, to identify five unique patterns of location-based activity spaces that are different in shape and anchoring. Second, we identify three unique growth trajectories. The comparison among these latent growth trajectories shows that in order to capture the extent of activity spaces we need long time periods for some individuals and shorter periods of observation for others. We also show that past studies using a single digit number of weeks may not be sufficient to capture individuals’ activity space. The major activity locations identified using a multilevel latent class model, do not appear to be statistically related to the growth patterns of Twitter users activity spaces. The evidence here shows Twitter data can be a valuable complementary source of information for heterogeneity analysis in activity-based modeling and simulation.