Reaction characteristics of the diesel oxidation catalyst of particulate matters from the diffusion flame of a oiler burner

The objective of this experimental study is to investigate the characteristics of the size distribution and the number concentration of PM (particulate matters) emitted from the diffusion flame of a boiler burner, which has the same type of combustion as a diesel engine. This study is performed to investigate the emission characteristics of nanoparticles generated from diffusion combustion in diesel fuel, and it considered fuel factors and the reaction characteristics of the nanoparticles on the DOC (Diesel oxidation catalyst). The factors examined in this experiment included the sulfur content in the fuel, the blend of the diesel fuel containing biodiesel and bio-ethanol, and the concentration of engine oil (0.1% and 1.0%) blended with diesel fuel. The particle size distribution of the nanoparticles exhausted from the boiler burner was measured by an SMPS (scanning mobility particle sizer). The number concentration of PM that were smaller than 70 nm in diameter greatly increased in the rear of the DOC when fuel containing 250 ppm of sulfur was used. The experiment also suggested that the particle number concentration in both the front and rear of the DOC was lower when ULSD (ultra low sulfur diesel) fuel blended with biodiesel and bio-ethanol, which are oxygenated fuels, was used than when only ULSD fuel was used. The higher the content of engine oil in the fuel, the higher the particle number concentration was in the front and rear of the catalyst. When the first dilution air temperature is increased from 30°C to 180°C, the nanoparticle number concentration dramatically dropped in the rear of the catalyst when fuel containing 250 ppm of sulfur was used, while the particle size distribution remained almost the same when the fuel with engine oil was used.     

PSO algorithm-based parameter optimization for HEV powertrain and its control strategy

The coordination between the powertrain and control strategy has significant impacts on the operating performance of hybrid electric vehicles (HEVs). A comprehensive methodology based on Particle Swarm Optimization (PSO) is presented in this paper to achieve parameter optimization for both the powertrain and the control strategy, with the aim of reducing fuel consumption, exhaust emissions, and manufacturing costs of the HEV. The original multi-objective optimization problem is converted into a single-objective problem with a goal-attainment method, and the principal parameters of powertrain and control strategy are set as the optimized variables by PSO, with the dynamic performance index of HEVs being defined as the constraint condition. Computer simulations were carried out, which showed that the PSO scheme gives preferable results in comparison to the ADVISOR method. Therefore, fuel consumption and exhaust emissions of HEVs can be effectively reduced without sacrificing dynamic performance of HEVs.     

Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.     

Analysis of the evolvement of contact wire wear irregularity in railway catenary based on historical data

This paper studies the evolvement of the wear irregularity of contact wire using wire thickness data measured yearly from a section of railway catenary. The power spectral density and time–frequency representation based on the wavelet transform are employed for data analysis, with an emphasis on local wear irregularities that are crucial for contact wire condition assessment. To investigate the cause of wear irregularity evolvement and the mutual influence with the pantograph–catenary dynamic interaction, simulations considering the influence of wear irregularity are carried out based on the finite element method. Analyses of the actual wear irregularities and the dynamic contact force under singular and complex wear irregularities are performed. Although the wear irregularity has limited impact on the pantograph–catenary interaction, it can induce the vibration of pantograph and contact wire that will lead to a notable increase of contact force standard deviation. The evolvement of wear irregularity is closely associated with the span length and dropper distribution of catenary structure and the running direction of pantograph. In addition, it is found feasible to detect the wear irregularity based on contact force, on condition that the sampling frequency is high enough to reflect the indicative frequencies.     

Swimming for survival: A role of phytoplankton motility in a stratified turbulent environment

We investigate a role for vertical migration in stratified coastal water, where the swimming speed is generally significantly less than the typical turbulent fluctuations in a tidally-mixed bottom layer. In our modelling approach we use a k- turbulence model to describe the physical forcing, a Lagrangian random walk model to describe the vertical displacement of individual cells in response to turbulence and due to cell motility, and a phytoplankton growth model to direct the swimming behaviour of the phytoplankton according to their light and nutrient requirements. The model results show how the cells form a stable subsurface chlorophyll maximum (SCM) at the base of the thermocline where episodic tidal turbulence causes erosion of part of the SCM biomass into the bottom mixed layer (BML). We then focus on the question of whether an ability to swim (weakly, compared to typical bottom layer turbulent intensities) provides any advantage by allowing return to the SCM. Our results show that tidal turbulence in the BML helps both motile and neutrally-buoyant cells by periodically pushing them into the base of the thermocline. Motile cells then have the advantage that they can swim further into the thermocline towards higher light which also reduces the likelihood of being re-mixed back into the BML.     

An analysis of children’s leisure activity engagement: examining the day of week, location, physical activity level, and fixity dimensions

This paper presents a detailed analysis of discretionary leisure activity engagement by children. Children’s leisure activity engagement is of much interest to transportation professionals from an activity-based travel demand modeling perspective, to child development professionals from a sociological perspective, and to health professionals from an active lifestyle perspective that can help prevent obesity and other medical ailments from an early age. Using data from the 2002 Child Development Supplement of the Panel Study of Income Dynamics, this paper presents a detailed analysis of children’s discretionary activity engagement by day of week (weekend versus weekday), location (in-home versus out-of-home), type of activity (physically active versus passive), and nature of activity (structured versus unstructured). A mixed multiple discrete-continuous extreme value model formulation is adopted to account for the fact that children may participate in multiple activities and allocate positive time duration to each of the activities chosen. It is found that children participate at the highest rate and for the longest duration in passive unstructured leisure activities inside the home. Children in households with parents who are employed, higher income, or higher education were found to participate in structured outdoor activities at higher rates. The child activity modeling framework and methodology presented in this paper lends itself for incorporation into larger activity-based travel model systems where it is imperative that children’s activity-travel patterns be explicitly modeled—both from a child health and well-being policy perspective and from a travel forecasting perspective.

A reverse causal-effect modeling approach for signal control of an oversaturated intersection

A novel approach is presented in which signalized intersections are treated as normal highway bottlenecks for improved computational efficiency. It is unique in two ways. First, it treats the signalized intersections as common freeway bottlenecks by a reversed cause and effect modeling approach. Both traffic arrivals and departures are modeled by smooth continuous functions of time as if there were no interruptions to traffic flows from signals. The use of smooth continuous functions for departure curves instead of commonly used step functions makes it easy to apply differential calculus in optimization and future extension to a system of intersections. Second, a dynamic linear programming (LP) model is then developed to maximize the total vehicular output from the intersection during the entire period of congestion subject to prevailing capacity and other operational constraints. The continuous optimal departure flow rate (the effect) is then converted to signal timing parameters (the cause) that can be readily implemented. Two numerical examples are presented to demonstrate the properties of the proposed algorithm and examine its performance.     

Carbon dioxide emissions from diesel and compressed natural gas buses during acceleration

Motor vehicle emission factors are generally derived from driving tests mimicking steady state conditions or transient drive cycles. Neither of these test conditions, however, completely represents real world driving conditions. In particular, they fail to determine emissions generated during the accelerating phase – a condition in which urban buses spend much of their time. We analyse and compare the results of time-dependant emission measurements conducted on diesel and compressed natural gas buses during an urban driving cycle on a chassis dynamometer and we derive power-law expressions relating carbon dioxide emission factors to the instantaneous speed while accelerating from rest. Emissions during acceleration are compared with that during steady speed operation.     

Improved theoretical modeling of a cyclone separator as a diesel soot particulate emission arrester

Particulate matter is considered to be the most harmful pollutant emitted into air from diesel engine exhaust, and its reduction is one of the most challenging problems in modern society. Several after-treatment retrofit programs have been proposed to control such emission, but to date, they suffer from high engineering complexity, high cost, thermal cracking, and increased back pressure, which in turn deteriorates diesel engine combustion performance. This paper proposes a solution for controlling diesel soot particulate emissions by an improved theoretical model for calculating the overall collection efficiency of a cyclone. The model considers the combined effect of collection efficiencies of both outer and inner vortices by introducing a particle distribution function to account for the non-uniform distribution of soot particles across the turbulent vortex section and by including the Cunningham correction factor for molecular slip of the particles. The cut size diameter model has also been modified and proposed by introducing the Cunningham correction factor for molecular slip of the separated soot particles under investigation. The results show good agreements with the existing theoretical and experimental studies of cyclones and diesel particulate filter flow characteristics of other applications.     

Low cost design of parallel parking assist system based on an ultrasonic sensor

This paper presents a low cost design and implementation of a parallel parking assist system (PPAS) based on ultrasonic sensors. Generally, a PPAS requires several types of sensors, such as an ultrasonic sensor, camera sensor, radar sensor and laser sensor for parking space detection. However, our proposed PPAS only requires two ultrasonic sensors on the front and lateral sides for parking space detection. Moreover, a steering angle sensor and wheel speed sensor installed in the vehicle are used to obtain vehicle position information for localization in ultrasonic range data. The hardware architecture of the PPAS based on an electronic control unit (ECU) module, sensor modules and a human machine interface (HMI) module was proposed. Moreover, the software architecture of the PPAS is based on system initialization, scheduling, recognition and a control algorithm. In particular, a novel sensor algorithm was proposed to minimize the vehicle corner error of the ultrasonic sensor. A prototype of the PPAS based on the proposed architecture was constructed. The experimental results demonstrate that the implemented prototype is robust and successfully performs parking space detection and automatic steering control. Finally, the low cost design and implementation of the PPAS was possible due to the cheap ultrasonic sensors, simple hardware design and low computational complexity of the proposed algorithm.