30 resultados para · Rail transportation


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The development of the tracks for the Tracked Hovercraft and Bliss Pendair Systems is described. Comment is made on the relative importance of track and suspension costs and of the need for tracks that are weather, vandal and noise proof. It is argued that the beam section required for a suspended air cushion is more likely to fit these requirements than that for beam riding vehicles, either air-cushion or magnetically suspended.

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A multi-dimensional combustion code implementing the Conditional Moment Closure turbulent combustion model interfaced with a well-established RANS two- phase flow field solver has been employed to study a broad range of operating conditions for a heavy duty direct-injection common-rail Diesel engine. These conditions include different loads (25%, 50%, 75% and full load) and engine speeds (1250 and 1830 RPM) and, with respect to the fuel path, different injection timings and rail pressures. A total of nine cases have been simulated. Excellent agreement with experimental data has been found for the pressure traces and the heat release rates, without adjusting any model constants. The chemical mechanism used contains a detailed NOx sub-mechanism. The predicted emissions agree reasonably well with the experimental data considering the range of operating points and given no adjustments of any rate constants have been employed. In an effort to identify CPU cost reduction potential, various dimensionality reduction strategies have been assessed. Furthermore, the sensitivity of the predictions with respect to resolution in particular relating to the CMC grid has been investigated. Overall, the results suggest that the presented modelling strategy has considerable predictive capability concerning Diesel engine combustion without requiring model constant calibration based on experimental data. This is true particularly for the heat release rates predictions and, to a lesser extent, for NOx emissions where further progress is still necessary. © 2009 SAE International.

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State and regional policies, such as low carbon fuel standards (LCFSs), increasingly mandate that transportation fuels be examined according to their greenhouse gas (GHG) emissions. We investigate whether such policies benefit from determining fuel carbon intensities (FCIs) locally to account for variations in fuel production and to stimulate improvements in FCI. In this study, we examine the FCI of transportation fuels on a lifecycle basis within a specific state, Minnesota, and compare the results to FCIs using national averages. Using data compiled from 18 refineries over an 11-year period, we find that ethanol production is highly variable, resulting in a 42% difference between carbon intensities. Historical data suggests that lower FCIs are possible through incremental improvements in refining efficiency and the use of biomass for processing heat. Stochastic modeling of the corn ethanol FCI shows that gains in certainty due to knowledge of specific refinery inputs are overwhelmed by uncertainty in parameters external to the refiner, including impacts of fertilization and land use change. The LCA results are incorporated into multiple policy scenarios to demonstrate the effect of policy configurations on the use of alternative fuels. These results provide a contrast between volumetric mandates and LCFSs. © 2011 Elsevier Ltd.

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Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

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Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

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The route planning problem for an order in freight transportation involves the selection of the best route for its transportation given a set of options that the network can offer. In its adaptive (or dynamic) version, the problem deals with the planning of a new route for an order while it is actually in transit typically because part or all of its pre-selected route is blocked or disrupted. In the intelligent product approach we are proposing, an order would be capable of identifying and evaluating such new routes in an automated manner and choosing the most preferable one without the intervention of humans. Because such approaches seek to mirror (and then automate) human decision making, in this paper we seek to identify new ways for dynamic route planning in industrial logistics inspired by the way people make similar decisions about their journey when they travel in multi-modal networks. We propose a new simulation game as a methodological tool for capturing their travel behaviour and we use it in this study. The results show that a simulation game can be used for capturing strategies and tactics of travellers and that intelligent products can provide a proper platform for the usage of such strategies in freight logistics. © 2012 IEEE.