Experimental investigation of B20 combustion and emissions under various intake conditions for low-temperature combustion

Recently, biodiesel has emerged as an alternative fuel for achieving low-temperature combustion (LTC). Several articles in the literature have showed that oxygenated biofuels, including biodiesel, can improve combustion stability under high exhaust gas recirculation (EGR) operation, which is considered to be necessary for the removal of nitric oxides (NOx). The objective of this study was to investigate the performance and emissions of 20% biodiesel blended diesel fuel (B20) at various intake pressures and oxygen concentration levels to characterize the fuel for LTC application. The experimental investigation of B20 was carried out using a single-cylinder engine (SCE) at 1400 rpm and 50% load condition. A set of critical flow orifices with synthetic EGR was employed to simulate various intake pressures and EGR levels. The behavior of the B20 was first characterized under various intake conditions. The results showed that with high oxygen intake, B20 exhibited combustion and emission levels that were very similar to conventional diesel. However, B20 reduced combustion deterioration while exhibiting lower carbon monoxide (CO) and hydrocarbon (HC) emissions than diesel under low oxygen intake conditions.     

Design of 2-speed transmission for electric commercial vehicle

As environmental and economic interests increase, the need for eco-friendly vehicle such as an electric vehicle (EV) has increased rapidly. Various research of enhancing EV powertrain efficiency and relibility have been studied. In this study, 2-speed shift gears mechanism is designed by using simpson type planetary gear train. This transmission has two planetary gear unit. Gear position is determinded by which ring gear is fixed. Internal components of the transmission are designed for satisfying the required specification of EV. We analyze gear strength, gear mesh efficiency, and transmission efficiency. By manufacturing the transmission prototype and performing some experiments, we verify the application suitability of this transmission.     

A simulation optimization approach for solving the dual-cycling problem in container terminals

Dual cycling is an operation technique whereby quay cranes perform loading and unloading operations simultaneously in the same ship bay. In this article, a mixed-integer programming model for quay crane dual-cycling scheduling is developed. The model considers the stowage plan of outbound containers and the operation sequence of quay cranes. To solve the model, a heuristic method, called bi-level genetic algorithm, is designed. Meanwhile, a simulation optimization method integrating the intelligent decision mechanism of the optimization algorithm and evaluation function of simulation model is proposed. Numerical experiments indicate that dual cycling can reduce the operation time of quay cranes compared to the method of scheduling loading and unloading separately. Moreover, the model and algorithms developed in this article can tackle quay crane dual-cycling problem efficiently.     

Relationship between phytoplankton bloom and wind stress in the sub-polar frontal area of the Japan/East Sea

The seasonal dynamics of phytoplankton blooms in the central Japan/East Sea (JES) show pronounced year-to-year variability based on Sea-viewing Wide Field-of-view Sensor (SeaWiFS; 19972003) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra (20002003) observations. Wind seems to strongly influence this variability. To study the relationship between wind and bloom initiation, we analyzed daily, remotely sensed wind stress data (Active Microwave Instrument–wind [AMI–wind], NASA Scatterometer [NSCAT], and Quick Scatterometer [QuickSCAT]: 19972003) and daily chlorophyll concentrations based on ocean color data (SeaWiFS and MODIS). The results agreed well with the hypotheses; in spring, blooms began 615 days after wind stress weakened. Fall blooms started 39 days after wind strengthened. We also simulated seasonal changes using a simple light–nutrient model using two values for the respiration ratio: 10% and 20%. The use of 20% seemed to reproduce the timing of the spring bloom quite well but underestimated the absolute level of chlorophyll concentration. On the other hand, using 10% produced a better estimation of the chlorophyll concentration but failed to match the timing. Neither of the model runs reproduced the timing of the fall bloom well.     

Evaluation of a brake assistance system (BAS) using an injury severity prediction model for pedestrians

Through the years, traffic engineers and researchers have developed a variety of countermeasures to enhance pedestrian safety. Pedestrian-vehicle collisions are regarded as the most serious type of accident since they incur high fatality rates. A fundamental concept in developing effective countermeasures is to analyze pedestrian-vehicle collisions scientifically, which can identify the causes of accidents and accident severity. The objective of this study was to investigate the pedestrian safety benefit of the brake assistance system (BAS) and a functional requirement associated with BAS, namely the time needed to safely detect a pedestrian ahead. An injury severity prediction model for pedestrians was developed to systematically evaluate the BAS in this study. Ordered multinomial logistic regression analysis was used to establish a statistical model capable of predicting pedestrian injury severity. In addition to vehicle characteristics, collision speed and pedestrian characteristics were used as independent predictor variables. The outcomes of this study would be useful in directing the development of safety policies and technologies associated with pedestrian safety.     

Pedestrian crowd tactical‐level decision making during emergency evacuations

This paper investigates pedestrian crowd tactical‐level decision making during emergency evacuations. Of particular interest is crowd exit‐choice behaviour. Two sources of stated choice data are collected and combined. One data set is derived from an experiment linked to a real‐life exit choice experience of participants (in a non‐evacuation setting). We examine aspects that have often been taken for granted in the literature in connection with egress behaviour of crowds during emergencies. We quantify evacuees' trade‐off between “distance”, “density”, “exit visibility” and “directional density” as well as the interactive effect between exit visibility and tendency to follow others. A comprehensive random‐utility analysis is conducted ranging from traditionally practiced models to the state‐of‐the‐practice methods such as random‐coefficient nested logit. Our findings suggest that (i) unless evacuees face certain levels of uncertainty in the escape environment; flows of crowd are unlikely to be followed. Otherwise, most evacuees perceive other individuals as potential sources of congestion and extra delay (generalisation to situations where crowd is completely unfamiliar with the egress geometry, however, may require careful scrutiny). (ii) Evacuees mostly prefer visible exits over the exits whose congestion level is unknown to them (i.e. the tendency to minimise ambiguity). (iii) The presence of attribute uncertainty (e.g. exit visibility) significantly changes the impact of observing decisions of others on each individual choice maker. We also found out that (iv) spatial distribution of exits has a significant influence on evacuees' decisions (presenting itself in the form of violating the IIA assumption). (v) The marginal weights that different individuals place upon attributes of exits are significantly heterogeneous. (vi) There is meaningful correlation between certain utility weights of individual evacuees. These behavioural findings can provide significant behavioural insight essential for safe evacuation planning and accurate forecast of evacuees' behaviour. Copyright © 2016 John Wiley & Sons, Ltd.     

Innovative detector layout for automated traffic turning volume counting

Because of many advantages, loop detectors are the most common practice for obtaining data to control intersections. However, they have some drawbacks, including the fact that multiple detectors are usually required to monitor a location. The current practice in many cities is to install four consecutive loop detectors per lane, or two at the stop bar and one as an advanced detector. In some cities, there are also departure detectors. All these configurations have some practical problems and do not produce accurate counts especially in shared lanes. In this paper, a new placement configuration for departure detectors is proposed and named the mid‐intersection detector (MID). In this configuration, departure detectors are moved back to the middle of the intersection in such a way that they can be activated by more than one movement at different times. In some cases, departure detectors lack equations for calculating turning movements, a problem solved by MIDs because each movement passes more detectors along its path (without increasing the number of loops), and therefore they can produce more accurate and reliable data for obtaining turning movement counts. Copyright © 2017 John Wiley & Sons, Ltd.     

Precise estimation of connections of metro passengers from Smart Card data

The aim of this study is to estimate both the physical and schedule-based connections of metro passengers from their entry and exit times at the gates and the stations, a data set available from Smart Card transactions in a majority of train networks. By examining the Smart Card data, we will observe a set of transit behaviors of metro passengers, which is manifested by the time intervals that identifies the boarding, transferring, or alighting train at a station. The authenticity of the time intervals is ensured by separating a set of passengers whose trip has a unique connection that is predominantly better by all respects than any alternative connection. Since the connections of such passengers, known as reference passengers, can be readily determined and hence their gate times and stations can be used to derive reliable time intervals. To detect an unknown path of a passenger, the proposed method checks, for each alternative connection, if it admits a sequence of boarding, middle train(s), and alighting trains, whose time intervals are all consistent with the gate times and stations of the passenger, a necessary condition of a true connection. Tested on weekly 32 million trips, the proposed method detected unique connections satisfying the necessary condition, which are, therefore, most likely true physical and schedule-based connections in 92.6 and 83.4 %, respectively, of the cases.     

Development of an integrated system based vehicle tracking algorithm with shadow removal and occlusion handling methods

Video image processing system (VIPS) is more efficient than other detecting systems. However, VIPS involves outdoor images and is very sensitive to the external environment, which could greatly decrease its accuracy according to rapid environmental changes. To obtain accurate traffic data accordingly, VIPS must address the problems such as growing shadows in transition; distortion of images due to the headlights at night; noises caused by the rain, snow or fog; and occlusions. This study intends to accurately calculate traffic data while addressing the shadow and occlusion problems, which are the most difficult tasks for the image‐detector‐based traffic data system. In this study, an algorithm for the individual vehicle tracking collection was developed to address the occlusion problem and to eliminate the noises or shadows caused by external environmental factors. A traffic data collection system was also proposed in order to accurately track individual vehicles that pass through the detection region. In addition, establishing an integrated system with shadow removal and occlusion handling using an image processing was also proposed. Copyright © 2010 John Wiley & Sons, Ltd.     

Analysis of thirty years evolution of urban growth,transport demand and supply,energy consumption,greenhouse and pollutants emissions in Greater Cairo

The objective of the paper is to analyze evolution of urbanization, transport demand and supply in Greater Cairo (GC) over the last three decades of the 20th century. This is in addition to investigating the impact of city growth on energy consumption and emissions from transport. It utilizes results of 1971, 1978, 1987, 1998 and 2001 travel demand surveys, undertaken during the corresponding GC transport studies; each was published a year or two later. No further transport studies have been carried out in GC over the past decade and in view of the current political situation, it is not envisaged that similar studies will be undertaken in the near future. The analysis includes the evolution of daily trips, trip purpose share, modal share and number of cars. More recent trends for 2006/2007 vehicle registration by type and size are given. The evolution of transport supply covers projects until early 2012. In parallel estimates of the evolution of energy consumption and cost, emissions of greenhouse gases (CO₂) and pollutants (CO, HC and NO_x) are given for 1971/2001. The adopted estimation methodology is summarized. Comparative analysis of relevant evolution indexes and trends of growth between 1971 and 2001, taking the former as base year, is given. Land use and transport policies and projects that in some cases helped, directly or indirectly, to reduce traffic congestion, or at least prevented an increase, are addressed, commenting on their outcomes. Thus, transferable experience are useful to sister cities benefiting from successes and avoiding drawbacks. The evolution of the impact of GC metro on energy consumption and cost, and GHG emissions is given for 1987/2001, assuming the scenario “metro did not exist”. More recent impact analysis is given for 2007/2008, as the data allowed estimating traffic volumes that would have been added to the congested metro corridors under the above scenario; and the related fuel consumption and cost and GHGs. The paper ends with conclusions on GC evolution, learned lessons and suggests repeating similar work in other mega cities of the developing countries. Further research is emphasized, e.g., modeling the relationship between land use, transport, energy and emissions; modeling emission factors by vehicle type; and studying fuel-subsidy-reduction scenarios and their socio-economic effects.