Comparison of two injection systems in an HSDI diesel engine using split injection and different injector nozzles

The demand for reduced pollutant emissions has motivated various technological advances in passenger car diesel engines. This paper presents a study comparing two fuel injection systems and analyzing their combustion noise and pollutant emissions. The abilities of different injection strategies to meet strict regulations were evaluated. The difficult task of maintaining a constant specific fuel consumption while trying to reduce pollutant emissions was the aim of this study. The engine being tested was a 0.287-liter single-cylinder engine equipped with a common-rail injection system. A solenoid and a piezoelectric injector were tested in the engine. The engine was operated under low load conditions using two injection events, high EGR rates, no swirl, three injection pressures and eight different dwell times. Four injector nozzles with approximately the same fuel injection rate were tested using the solenoid injection system (10 and 12 orifice configuration) and piezoelectric system (6 and 12 orifice design). The injection system had a significant influence on pollutant emissions and combustion noise. The piezoelectric injector presented the best characteristics for future studies since it allows for shorter injection durations and greater precision, which means smaller fuel mass deliveries with faster responses.     

Optimal fueling strategies for locomotive fleets in railroad networks

Railroad companies spend billions of dollars each year to purchase fuel for thousands of locomotives across the railroad network. Each fuel station charges a site-dependent fuel price, and the railroad companies must pay an additional flat contracting fee in order to use it. This paper presents a linear mixed-integer mathematical model that integrates not only fuel station location decisions but also locomotive fueling schedule decisions. The proposed model helps railroads decide which fuel stations to contract, and how each locomotive should purchase fuel along its predetermined shipment path, such that no locomotive runs out of fuel while the summation of fuel purchasing costs, shipment delay costs (due to fueling), and contracting charges is minimized. A Lagrangian relaxation framework is proposed to decompose the problem into fueling schedule and facility location selection sub-problems. A network shortest path formulation of the fueling schedule sub-problem is developed to obtain an exact optimal solution to the fueling schedule sub-problem. The proposed framework is applied to a large-scale empirical case and is shown to effectively reduce system costs.     

A numerical investigation into strength and deformation characteristics of preloaded tubular members under lateral impact loads

This paper presents the results of a numerical investigation into the structural behaviour of preloaded tubular members under lateral impact loads by means of finite element method. The lateral load represents a statically modelled impact from collision between tubular member and a solid rectangular indenter. Three different kinds of end conditions have been applied to the model and the effects of boundary conditions are investigated. Also, the effect of preloading on the buckling strength as well as the ultimate strength for laterally impacted tubes is assessed and it will be shown that preloading and position of applying force directly affect these strengths. In other words, by increasing in the amount of preloading, ultimate strength reduces and member tends to collapse under lower amounts of loads. The influence of the position of applying lateral load has also been addressed and relevant results will be discussed. In order to verify the performance of numerical model, the results have been examined against an available experimental test.     

Factors contributing to the severity of intersection crashes

Road crashes are a leading cause of death and serious injuries both developed and developing countries. Intersections are recognized as being among the most hazardous locations on the roads. Although crashes at intersections form about 35 % of the reported accidents account for about 32% of traffic‐related serious injuries and fatalities in Singapore, there is no known study that examines the factors contributing to the severity of these crashes. In this study, the ordinal probit model was applied to crash data from 1992 to 2002 to investigate the role a variety of factors play in determining the severity of intersection crashes. Our study shows that vehicle type, road type, collision type, driver's characteristics and time of day are important determinants of the severity of crashes at intersections in Singapore.     

Estimating intersection O-D matrices from observed time-series of traffic counts: The zellner estimator

The problem of estimating intersection O-D matrices from input and output time-series of traffic counts is considered in this paper. Because of possible existence of significant correlation between the error terms across structural equations forming the O-D matrices, the seemingly unrelated estimator (Zellner estimator) was suggested. Estimation results showed evidence of strong correlation between error terms across-equations. Generally, the Zellner estimator produced more efficient estimates than did the ordinary least-squares estimator. Furthermore, the Zellner estimator satisfied all constraints and reproduced turning movements comparable to the actual ones.     

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

Transportation - There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been...     

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

ABSTRACT

This study provides a bibliometric review of 279 studies on the applications of big data and artificial intelligence (AI) in the maritime industry, published in 214 academic outlets, authored by 842 scholars. We extracted bibliographical data from the Web of Science database and analysed it using the Bibliometrix tool in R software. Based on citation analysis metrics, we revealed the most influential articles, journals, authors and institutions. Using the bibliographic coupling methodology, we identified four underlying research clusters: (1) digital transformation in maritime industry, (2) applications of big data from AIS, (3) energy efficiency and (4) predictive analytics. We analysed these clusters in detail and extracted future research questions. Besides, we present research collaboration networks on the institution and author level.     

Vulnerability evaluation of freight railway networks using a heuristic routing and scheduling optimization model

Transportation - Railway network is an integral part of the economy of many countries. Identifying critical network elements can help network executives to take appropriate preventive actions...     

A computational investigation of the effects of both-sides general corrosion on the buckling/plastic collapse behaviour and strength of stiffened plates

This paper presents the results of an investigation into the post-buckling behaviour and ultimate strength of imperfect corroded stiffened steel plates used in ships and other marine-related structures. A series of elastic–plastic large deflection finite element analyses is performed on stiffened steel plates suffering general corrosion wastage with random distribution. General corrosion is introduced into the finite element models using a random thickness surface model. The effects of corroded stiffened plate parameters on the post-buckling and ultimate strengths are evaluated in detail. The stiffeners of different symmetrical or unsymmetrical cross-sections are introduced into the models for analysis. Some distinctions are explored and highlighted between the behaviours of steel plates suffering general corrosion in unstiffened and stiffened cases. Finally, a proposal is given in order to simulate the average stress–average strain relationship of stiffened steel plates having both-surface general corrosion wastage.     

A quantum evolutionary algorithm for the second-best congestion pricing problem in urban traffic networks

This paper investigates the congestion pricing problem in urban traffic networks. A first-best strategy, a second-best strategy for toll leveling in closed cordons and a second-best strategy for determining both toll levels and toll points are considered. The problem is known to be a mixed integer programming model and formulated as a bi-level optimization problem, with an objective of maximizing the social welfare. A method is presented to solve the problem, based on a novel metaheuristic algorithm, namely quantum evolutionary algorithm (QEA). To verify the proposed method, the widely used genetic algorithm (GA) is also applied to solve the problem. The problem is solved for a medium-size urban traffic network and the results of the QEA are compared against the conventional GA. Computational results show that the QEA outperforms the GA in solution quality.