Nanoparticle emission characteristics and reduction strategies by boost pressure control and injection strategies in a passenger diesel engine

This research attempted to analyze nanoparticles and other harmful exhaust emissions in accordance with injection strategies and air-fuel ratio (AFR) changes for small diesel engines. The emission characteristics were analyzed in the medium-speed condition, which is the main driving range of a diesel engine. In the case of particulate matter (PM), the number of particles was measured, analyzed, and compared to identify the correlation and emission characteristics of nanoparticles by using a dilution device and condensation particle counter (CPC), which are international standards for particle measurement recommended by the Particulate Measurement Programme (PMP). The engine torque tended to be reduced as pilot injections were added, and the torque was increased by the increased boost pressure, but reduced by the exhaust pressure increase in a part of the low-load range. The number of nanoparticles was not influenced greatly by the change in AFR, but the reduction effect on the PM weight was great depending on the boost pressure increase. In addition, the number of nanoparticles tended to increase as the fuel injection timing became closer to TDC in all conditions, and its difference became larger with an increase in AFR. In addition, in the case of the pilot injection, nanoparticle emission showed similar characteristics depending on the main injection timing, but it was increased by advanced injection timing when performing the main injection only, and the number of the nanoparticles increased as pilot injections were added. Last, the optimal conditions for EMS calibration were analyzed by selecting the conditions of torque reduction and NOx increase within 5 % from all of the engine operating conditions; optimized conditions are presented.     

Vibration reduction of H/Shaft using an electromagnetic damper with mode change

The objective of this study is to develop a damper that can reduce the amplitude of vibration in various frequency ranges. Previous H/Shaft vibration reduction methods work in a passive way. A dynamic damper reduces the amplitude of vibration at its first mode, but vibration still appears at the second mode. A mass damper or hollow shaft can shift the natural frequency to a lower or higher region. The fixed operating frequency prevents vibration from being reduced outside the operating frequency range. The proposed damper uses electromagnets as either masses or actuators to change the damper mode between dynamic damper mode and mass damper mode. The electromagnetic damper (EMD) can change its mode to respond to the vibration excitation at both low and high frequencies. The vibration reduction performance was evaluated by FRF tests in laboratory and vehicle conditions. The results were compared with those of a dynamic damper and indicate that the amplitude of vibration is reduced by 95.6 % when the EMD is implemented on an H/Shaft, whereas only 61.9 % vibration reduction is achieved by the dynamic damper.     

Effect of ABCA1-V771M polymorphism on plasma lipid levels and its relationship with coronary atherosclerotic heart disease

Objective To explore the risk association of ABCA1-V771M polymorphism with coronary heart disease (CHD) in Hart nationality in Northwest of China. Methods With case-control study, ABCA1-V771M polymorphism was detected in 204 unrelated Hart nationality people in Northwest of China, and all the subjects by coronary angiography were grouped into 106 cases and 98 controls. The genotypes and alleles frequency distribution of ABCA1-V771M polymorphisms were analyzed by PCR-RFLP analysis, and the clinical statistics of serum lipids were compared and its effects of ABCA1-V771M polymorphism on the plasma lipid levels and coronary atherosclerotic heart disease were analyzed. Results The genotypic frequencies of ABCA1-V771M polymorphism matched well under Hardy-Weinberg equilibrium (P>0.05), V and M allelic frequencies were 33.3% and 66.7%. In comparison with VV VM genotype carriers, MM genotypes carriers had much lower plasma levels of HDL-C (P<0. 001) and much higher plasma levels of TG (P<0. 05). M allelic frequency in CHD group was significantly higher than V allelic frequency (P<0. 05). M allele was related with more severity of atherosclerosis in the coronary artery than V allele (P<0.05). However, there was no obvious difference in the incidence of AMI among carriers with three genotypes of ABCA1-V771M polymorphism (P>0.05). Conclusion ABCA1-V771M polymorphism was not only associated with the plasma levels of HDL-C and TG, but also related to the susceptibility and severity of coronary atheroselerotic heart disease. Moreover, M771 allele appeared to be atherogenie among Han population in Northwest of China.     

CFD Analysis of Ship-to-Ship Hydrodynamic Interaction

A numerical study of ship-to-ship interaction forces is performed using a commercial CFD code, and the results are compared with experimental data and with the results of a panel method analysis. Two ship models have been used in the interaction forces analysis: a tug and a tanker, advancing parallel to each other with different lateral distances and two different values of the fluid depth. Computations are carried out with four different flow models: inviscid and viscous flow with the free surface modeled as a rigid wall and inviscid and viscous flow with the deformable free surface. A fair agreement was obtained with available experimental data and results obtained by panel method. The influence of viscosity in the computations is found to be comparatively weak, while the wavemaking effects may be important, at small magnitude of the horizontal clearance.     

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.     

How household transportation expenditures have evolved in Canada: a long term perspective

In recent years, increasing recognition of the challenges associated with global climate change and inequity in developed countries have revived researcher’s interest towards analyzing transportation related expenditure of households. The current research contributes to travel behaviour literature by developing an econometric model of household budgetary allocations with a particular focus on transportation expenditure. Towards this end, we employ the public-use micro-data extracted from the Survey of Household Spending (SHS) for the years 1997–2009. The proposed econometric modeling approach is built on the multiple discrete continuous extreme value model (MDCEV) framework. Specifically, in our analysis, the scaled version of the MDCEV model outperformed its other counterparts. Broadly, the model results indicated that a host of household socio-economic and demographic attributes along with the residential location characteristics affect the apportioning of income to various expenditure categories and savings. We also observed a relatively stable transportation spending behaviour over time. Additionally, a policy analysis exercise is conducted where we observed that with increase in health expenses and reduction in savings results in adjustments in all expenditure categories.     

Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand

Network pricing serves as an instrument for congestion management, however, agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand, which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context, but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly, interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear, and the set of equilibrium paths is constant. These assumptions are restrictive, so three larger networks are considered numerically, and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases, optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.     

Factors associated with home-based e-working and e-shopping in Nanjing,China

The widespread adoption of information and communication technology has facilitated frequent e-activities in people’s daily life. From the perspective of individual’s time use on e-working and e-shopping at home, this paper aims to enhance our understanding of the function of home beyond a living space for family life. Using a household survey of 608 full-time paid employees who conducted e-activities at home in Nanjing, China, we investigated the characteristics and patterns of home-based e-working and e-shopping. Only 7.9% of the respondents neither e-shopped nor e-worked at home. We find that the socio-demographic context, Internet use habits, attitudes towards e-working/e-shopping, and geographical accessibility have influenced the patterns of home-based e-working and e-shopping. The results indicate that the rich e-activities taking place at home have changed the time use at home and reinforced the function of home as a multifunctional hub.     

Relationship between well-being and daily time use of elderly: evidence from the disabilities and use of time survey

According to US Census Bureau, the number of individuals in the age group above 65 years is expected to increase by more than 100% from the year 2000 to 2030. It is anticipated that increasing elderly population will put unforeseen demands on the transportation infrastructure due to the atypical mobility and travel needs of the elderly. Consequently, transportation professionals have attempted to understand the travel behavior of the elderly including the trip frequency, trip distance and mode choice decisions. Majority of the research on elderly travel behavior have focused on the mobility outcomes with limited research into understanding the tradeoffs made by this population segment in terms of their in-home and out-of-home activity engagement choices. The goal of the current research is to contribute to this line of inquiry by simultaneously exploring the daily activity engagement choices of the elderly Americans including their in-home and out-of-home activity participation (what activities to pursue) and time alloocation (duration of each activity) decisions while accounting for the temporal constraints. Further, the study attempts to explore the relationship between physical and subjective well-being and daily activity engagement decisions of the elderly; where subjective well-being is derived from reported needs satisfaction with life and different domains of it. To this end, data from the Disabilities and Use of Time survey of Panel Study of Income Dynamics was used to estimate a panel version of MDCEV model. In addition to person- and household-level demographic variables, activity participation and time use choices of elderly were found to vary across different levels of reported physical and subjective well-being measures. The model estimation results were plausible and provide interesting insights into the activity engagement choices of the elderly with implications for transportation policy development. Among other socio-demographic variables, living arrangements (living with family versus in elderly homes) were found to have significant influence on how people participate into different in-home versus out-of-home activities. For example, elderly living in the elderly home were found to participate more into out-of-home activities compared to people living with families. Elderly with disabilities were found to compensate lower participation into out-of-home activities with more participation into in-home activities. Considerable heterogeneity was observed in time engagement behavior of the elderly across reported levels of satisfaction with finance, job and cognitive needs. For example, elderly expressing high satisfaction with job was found to spend less time in in-home social activities. Elderly reporting higher satisfaction with finance were found to spend more time into OH social and shopping activities.     

Evaluating air emission inventories and indicators from cruise vessels at ports

This paper provides an estimation of air emissions (CO₂, NO_X, SO_X and PM) released by cruise vessels at the port level. The methodology is based on the “full bottom-up” approach and starts by evaluating the fuel consumed by each vessel on the basis of its individual port activities (manoeuvring, berthing and hoteling). The Port of Barcelona was selected as the site at which to perform the analysis, in which 125 calls of 30 cruise vessels were monitored. Real-time data from the automatic identification system (AIS), factor emissions from engine certificates and vessel characteristics from IHS Sea-web database were also collected for the analysis. The research findings show that the most appropriate indicators are inventory emissions per “port-time gross tonnage”, “port-time passenger” and “port time”. These emission indicators improve our understanding of cruise emissions and will facilitate the work that aims to estimate reliably and quickly the in-port ship emission inventories of cruise ports.