Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.     

Topological analysis of powertrains for refuse-collecting vehicles based on real routes–Part I: Hybrid hydraulic powertrain

In this two-part paper, a topological analysis of powertrains for refuse-collecting vehicles (RCVs) based on the simulation of different architectures (internal combustion engine, hybrid electric, and hybrid hydraulic) on real routes is proposed. In this first part, a characterization of a standard route is performed, analyzing the average power consumption and the most frequent working points of an internal combustion engine (ICE) in real routes. This information is used to define alternative powertrain architectures. A hybrid hydraulic powertrain architecture is proposed and modelled. The proposed powertrain model is executed using two different control algorithms, with and without predictive strategies, with data obtained from real routes. A calculation engine (an algorithm which runs the vehicle models on real routes), is presented and used for simulations. This calculation engine has been specifically designed to analyze if the different alternative powertrain delivers the same performance of the original ICE. Finally, the overall performance of the different architectures and control strategies are summarized into a fuel and energy consumption table, which will be used in the second part of this paper to compare with the different architectures based on hybrid electric powertrain. The overall performance of the different architectures indicates that the use of a hybrid hydraulic powertrain with simple control laws can reduce the fuel consumption up to a 14 %.     

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle’s mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.     

Enabling a viable technique for the optimization of LNG carrier cargo operations

In this study, we optimize the loading and discharging operations of the Liquefied Natural Gas (LNG) carrier. First, we identify the required precautions for LNG carrier cargo operations. Next, we prioritize these precautions using the analytic hierarchy process (AHP) and experts’ judgments, in order to optimize the operational loading and discharging exercises of the LNG carrier, prevent system failure and human error, and reduce the risk of marine accidents. Thus, the objective of our study is to increase the level of safety during cargo operations.     

自行车流视频识别判断方法研究

考虑算法的实时性,交通流个体识别往往采用轮廓特征来描述。由于自行车与行人的很多轮廓特征值相近,在复杂城市交通环境中,从慢行交通流中准确地识别出自行车是目前采用视频检测交通流的难点之一。通过现场视频检测获取足够的样本外轮廓数据,分析检测目标轮廓的高、宽、高宽比、面积等典型轮廓特征,发现目标轮廓高宽比特征能较好地识别出行人、自行车等慢行交通,并给出合适的取值范围。研究表明自行车高宽比能够较好地成为视频识别的依据,为自行车视频识别提供数据。     

Institutional reform in ports of developing countries: the case of Lebanon—part I: the plan

Upon the expiry of the concession contract signed between Lebanon and a private company for the Port of Beirut operation (in December 1990), the Government appointed a temporary commission to operate the port under the rules of the expiring concession. The legality of this measure has since always been questioned, while the temporary commission underwent three major personnel changes which clearly prevented any long-term thinking or planning. In 1998, the temporary commission entered into a 20-year joint venture for the establishment of a container terminal. Meanwhile, Lebanon's two main ports were facing major regional competition, while competing against each other to some degree. Thus, the need became urgent to end the temporary status and propose reforms to the entire sector. To that end, the Ministry of Public Works and Transport was commissed by the Government to propose a permanent institutional framework for the port of Beirut while assessing the need for a national maritime sector regulator. This paper presents the recommendations for the institutional reform of the Lebanese maritime transport sector.     

Estimation of wave-induced ship hull bending moment from ship motion measurements

A time-domain technique for estimating wave-induced ship hull bending moment from ship motion measurements is presented. This technique is developed to improve hull response monitoring systems. Artificial neural networks are used to model the time-domain relationship between the wave-induced vertical bending moment and the coupled heave and pitch motions. The application of the proposed technique is validated using experimental data.     

Innovative strategies for urban car-sharing systems and a simulator to assess their performance

In this paper, three innovative car-sharing systems for urban areas are proposed, based on fleets of individual intelligent vehicles with three service characteristics: instant access, open-ended reservations and one-way trips. These features provide high flexibility but create an uneven distribution of vehicles among stations. Therefore, relocation of vehicles must be performed. Three different system procedures are proposed: in the first system, relocations are performed by users; in the other two, vehicles relocate automatically, thanks to their automation. In the first two systems, vehicles are accessible only at stations, whereas in the third they are also accessible along roads. In order to provide transport managers with a tool to test systems in different realities, an object-oriented simulator is developed. The simulation provides outputs of system performance, in terms of user waiting times and system efficiency. The proposed systems are simulated for the city of Genoa, in Italy, and a comparative analysis is presented.     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

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.