A modelling system to simulate goods movements at an urban scale

The paper reports a modelling system to simulate goods movements at an urban scale. It allows joint analysis of choices made by end-consumers (assumed to be families) and retailers. These movements are examined at two levels: analysis of commodity flows, in terms of quantity, generated by the consumption of commodities; analysis of commodity flows, in terms of vehicles, due to restocking. The first level allows us to calculate the goods quantity flows due to consumption and restocking; the second level allows us to determine the service, vehicles used and target time, as well as the route chosen for restocking sales outlets in order to estimate vehicle flows on the urban/metropolitan transportation network. The modelling system is a multi-step model and considers a disaggregated approach for each decisional level.     

A comprehensive analysis of household transportation expenditures relative to other goods and services: an application to United States consumer expenditure data

This paper proposes a multiple discrete continuous nested extreme value (MDCNEV) model to analyze household expenditures for transportation-related items in relation to a host of other consumption categories. The model system presented in this paper is capable of providing a comprehensive assessment of how household consumption patterns (including savings) would be impacted by increases in fuel prices or any other household expense. The MDCNEV model presented in this paper is estimated on disaggregate consumption data from the 2002 Consumer Expenditure Survey data of the United States. Model estimation results show that a host of household and personal socio-economic, demographic, and location variables affect the proportion of monetary resources that households allocate to various consumption categories. Sensitivity analysis conducted using the model demonstrates the applicability of the model for quantifying consumption adjustment patterns in response to rising fuel prices. It is found that households adjust their food consumption, vehicular purchases, and savings rates in the short run. In the long term, adjustments are also made to housing choices (expenses), calling for the need to ensure that fuel price effects are adequately reflected in integrated microsimulation models of land use and travel.     

Estimation method for railway passengers’ train choice behavior with smart card transaction data

Smart card systems have become the predominant method of collecting public transport fares in Japan. Transaction data obtained through smart cards have resulted in a large amount of archived information on how passengers use public transportation. The data have the potential to be used for modeling passenger behavior and demand for public transportation. This study focused on train choices made by railway passengers. If each passenger’s train choice can be identified over a long period of time, this information would be useful for improving the customer relationship management of the railway company and for improving train timetables. The aim of this study was to develop a methodology for estimating which train is boarded by each smart card holder. This paper presents a methodology and an algorithm for estimation using long-term transaction data. To validate the computation time and accuracy of the estimation, an empirical analysis is carried out using actual transaction data provided by a railway company in Japan. The results show that the proposed method is capable of estimating passenger usage patterns from smart card transaction data collected over a long time period.     

Simulation of unsteady free-surface flow around a ship hull using a fully coupled multi-phase flow method

An accurate, efficient algorithm for solving free surface flows around ship hulls is described. Accuracy is achieved using a compressive advection discretization which maintains a sharp free surface interface representation without relying on a small time step. Efficiency is obtained using a solution algorithm which implicitly couples velocity, pressure, and volume fractions. The algorithm has been implemented in a computational fluid dynamics code called CFX and is validated by means of a comparisonwith experimental data of benchmark cases in both steady and transient conditions.     

Development of an electric motor-driven pump unit for electro-hydraulic power steering with 42V power-Net

Motorization in vehicles is expanding rapidly for fuel efficiency, customer comfort, convenience, and safety features. These new electric loads represent an increase in the required electric power. This has generated interest in new, higher power systems such as the 42V Power Net. The electro-hydraulic power steering (EHPS) system is one of these systems. This paper presents the development of the electric motor-driven pump unit for the EHPS system using a 42V power-Net. The interior type permanent magnet synchronous motor (IPMSM) can be applied to this system with more power density per volume for compactness of the EHPS. In order to improve the system, the IPMSM and its control method was optimized for improved torque characteristics and electric power consumption. The performances of both the pump unit and the IPMSM have been verified by experimental results. Finally, all in one type the electric motor-driven pump unit are developed from the experiment verification.     

Designing a non-linear tracking controller for vehicle active suspension systems using an optimization process

In this paper, a new non-linear tracking controller for vehicle active suspension systems is analytically designed using an optimization process. The proposed scheme employs a realistic non-linear quarter-car model, which is composed of a hardening spring and a quadratic damping force. The control input is the external active suspension force and is determined by minimizing a performance index defined as a weighted combination of conflicting objectives, namely ride quality, handling performance and control energy. A linear skyhook model with standard parameters is used as the reference model to be tracked by the controller. The robustness of the proposed controller in the presence of modeling uncertainties is investigated. The performed analysis and the simulation results indicate that both vehicle ride comfort and handling performance can be improved using the minimum external force when the proposed non-linear controller is engaged with the model. Meanwhile, a compromise between different objectives and control energy can easily be made by regulating their respective weighting factors, which are the free parameters of the control law.     

Modelling dual carriageway lane changing using neural networks

Neural networks offer a potential alternative method of modelling driver behaviour within road traffic systems. This paper explores the application of neural networks to modelling the lane-changing decisions of drivers on dual carriageways. Two approaches are considered. The first, preliminary approach uses a prediction type of neural network with a single hidden layer and the back propagation learning algorithm to model the behaviour of an individual driver. A series of consecutive time-scan traffic patterns, which describe the driver's environment and changes over time as the selected vehicle travels along a link, are input to the neural network, which then predicts the new lane and position of the vehicle. Training data are collected from a human subject using an interactive driving simulation. The trained neural network successfully exhibited the rudiments of driving behaviour in terms of lane and speed changes. A major disadvantage of this approach was the difficulty in recording real-life data, which are required to train the neural network, for individual drivers. The second approach concentrates specifically on lane changing and makes use of a learning vector quantization classification type of neural network. Input to the neural network still consists primarily of time-scan traffic patterns, but the format is changed to facilitate the possibility of data acquisition using image processing. The neural network output classifies the input data by determining the new lane for the vehicle concerned. Performance in both testing and training was very good for data generated by the rule-based driver-decision model of a microscopic simulation. Performance in testing was less satisfactory for data taken directly from a road and highlighted the need for extensive data sets for successful training.     

Experimental validation of a mathematical model of a reed-valve reciprocating air compressor from an automotive-braking system

Mathematical simulation is the process of designing a model of a real system and then conducting experiments with the simulation to understand the system’s behavior. Mathematical simulation is widely used for investigating and designing compressors, and with a minimal number of simplifying assumptions, mathematical models can be used in conjunction with modern computing tools to solve complicated problems. A considerable amount of previous research has focused on the mathematical modeling of reciprocating air compressors used in automotive braking. The aim of the present work was to experimentally validate the mathematical model for such compressors. We present a simplified and effective mathematical model for estimating compressor performance, and this model can easily be executed using personal computers. Parameters such as compressor speed, discharge pressure and clearance volume were evaluated in terms of their effect on the thermodynamic behavior of compressors. The model can predict cylinder pressure, cylinder volume, cylinder temperature, valve lift and resultant torque at different crank angles; it can also predict the free air delivered and the indicated power of the compressor. Therefore, the model has been validated using experimental results.     

Method for analyzing epicyclic gearboxes

This paper presents a method for analyzing epicyclic gearboxes by evaluating the speeds, torques and power of the external elements in epicyclic gear mechanisms, as well as the total ratios of the gear box. The method is based on the equations that describe each epicyclic gear mechanism and rules that assign appropriate codes to the external elements. The method emphasizes how power flows are transmitted through the epicyclic gears, as well as power losses. Analysis of an epicyclic gear box is performed to illustrate the proposed method.     

A comparative analysis of the European and North-American approaches to dealing with major oil spills

Background  

The question of what should be the right level of preparedness to react to a major oil spill (i.e. the EXXON VALDEZ spill, the ERIKA spill, and the PRESTIGE spill) is highly debated, especially in the aftermath of such spills. Little research, however, has been conducted with the aim to identify and compare governments’ best practices not only to fund preparedness measures but also to assess the countries’ ability to respond effectively to catastrophic oil spills. It is the author’s belief that important lessons can be learnt from a comparative analysis of countries’ best practices.