20 resultados para Railroads Train dispatching

em Universidad Politécnica de Madrid


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The research work that here is summarized, it is classed on the area of dynamics and measures of railway safety, specifically in the study of the influence of the cross wind on the high-speed trains as well as the study of new mitigation measures like wind breaking structures or wind fences, with optimized shapes. The work has been developed in the Research Center in Rail Technology (CITEF), and supported by the Universidad Politécnica de Madrid, Spain.

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In order to satisfy the safety-critical requirements, the train control system (TCS) often employs a layered safety communication protocol to provide reliable services. However, both description and verification of the safety protocols may be formidable due to the system complexity. In this paper, interface automata (IA) are used to describe the safety service interface behaviors of safety communication protocol. A formal verification method is proposed to describe the safety communication protocols using IA and translate IA model into PROMELA model so that the protocols can be verified by the model checker SPIN. A case study of using this method to describe and verify a safety communication protocol is included. The verification results illustrate that the proposed method is effective to describe the safety protocols and verify deadlocks, livelocks and several mandatory consistency properties. A prototype of safety protocols is also developed based on the presented formally verifying method.

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The paper resumes the results obtained applying various implementations of the direct boundary element method (BEM) to the solution of the Laplace Equation governing the potential flow problem during everyday service manoeuvres of high-speed trains. In particular the results of train passing events at three different speed combinations are presented. Some recommendations are given in order to reduce calculation times which as is demonstrated can be cut down to not exceed reasonable limits even when using nowadays office PCs. Thus the method is shown to be a very valuable tool for the design engineer.

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Underpasses are common in modern railway lines. Wildlife corridors and drainage conduits often fall into this category of partially buried structures. Their dynamic behavior has received far less attention than that of other structures such as bridges, but their large number makes their study an interesting challenge from the viewpoint of safety and cost savings. Here, we present a complete study of a culvert, including on-site measurements and numerical modeling. The studied structure belongs to the high-speed railway line linking Segovia and Valladolid in Spain. The line was opened to traffic in 2004. On-site measurements were performed for the structure by recording the dynamic response at selected points of the structure during the passage of high-speed trains at speeds ranging between 200 and 300 km/h. The measurements provide not only reference values suitable for model fitting, but also a good insight into the main features of the dynamic behavior of this structure. Finite element techniques were used to model the dynamic behavior of the structure and its key features. Special attention is paid to vertical accelerations, the values of which should be limited to avoid track instability according to Eurocode. This study furthers our understanding of the dynamic response of railway underpasses to train loads.

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An electrically tunable system for the control of optical pulse sequences is proposed and demonstrated. It is based on the use of an electrooptic modulator for periodic phase modulation followed by a dispersive device to obtain the temporal Talbot effect. The proposed configuration allows for repetition rate multiplication with different multiplication factors and with the simultaneous control of the pulse train envelope by simply changing the electrical signal driving the modulator. Simulated and experimental results for an input optical pulse train of 10 GHz are shown for different multiplication factors and envelope shapes.

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An aerodynamic optimization of the ICE 2 high-speed train nose in term of front wind action sensitivity is carried out in this paper. The nose is parametrically defined by Be?zier Curves, and a three-dimensional representation of the nose is obtained using thirty one design variables. This implies a more complete parametrization, allowing the representation of a real model. In order to perform this study a genetic algorithm (GA) is used. Using a GA involves a large number of evaluations before finding such optimal. Hence it is proposed the use of metamodels or surrogate models to replace Navier-Stokes solver and speed up the optimization process. Adaptive sampling is considered to optimize surrogate model fitting and minimize computational cost when dealing with a very large number of design parameters. The paper introduces the feasi- bility of using GA in combination with metamodels for real high-speed train geometry optimization.

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- PV and HCPV compete in the utility market - PV cost reduction has been dramatic through volume - A complete off-the-shelf optics solution by Evonik and LPI - Based on the best-in-class design: The FK concentrator

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La influencia de la aerodinámica en el diseño de los trenes de alta velocidad, unida a la necesidad de resolver nuevos problemas surgidos con el aumento de la velocidad de circulación y la reducción de peso del vehículo, hace evidente el interés de plantear un estudio de optimización que aborde tales puntos. En este contexto, se presenta en esta tesis la optimización aerodinámica del testero de un tren de alta velocidad, llevada a cabo mediante el uso de métodos de optimización avanzados. Entre estos métodos, se ha elegido aquí a los algoritmos genéticos y al método adjunto como las herramientas para llevar a cabo dicha optimización. La base conceptual, las características y la implementación de los mismos se detalla a lo largo de la tesis, permitiendo entender los motivos de su elección, y las consecuencias, en términos de ventajas y desventajas que cada uno de ellos implican. El uso de los algorimos genéticos implica a su vez la necesidad de una parametrización geométrica de los candidatos a óptimo y la generación de un modelo aproximado que complementa al método de optimización. Estos puntos se describen de modo particular en el primer bloque de la tesis, enfocada a la metodología seguida en este estudio. El segundo bloque se centra en la aplicación de los métodos a fin de optimizar el comportamiento aerodinámico del tren en distintos escenarios. Estos escenarios engloban los casos más comunes y también algunos de los más exigentes a los que hace frente un tren de alta velocidad: circulación en campo abierto con viento frontal o viento lateral, y entrada en túnel. Considerando el caso de viento frontal en campo abierto, los dos métodos han sido aplicados, permitiendo una comparación de las diferentes metodologías, así como el coste computacional asociado a cada uno, y la minimización de la resistencia aerodinámica conseguida en esa optimización. La posibilidad de evitar parametrizar la geometría y, por tanto, reducir el coste computacional del proceso de optimización es la característica más significativa de los métodos adjuntos, mientras que en el caso de los algoritmos genéticos se destaca la simplicidad y capacidad de encontrar un óptimo global en un espacio de diseño multi-modal o de resolver problemas multi-objetivo. El caso de viento lateral en campo abierto considera nuevamente los dos métoxi dos de optimización anteriores. La parametrización se ha simplificado en este estudio, lo que notablemente reduce el coste numérico de todo el estudio de optimización, a la vez que aún recoge las características geométricas más relevantes en un tren de alta velocidad. Este análisis ha permitido identificar y cuantificar la influencia de cada uno de los parámetros geométricos incluídos en la parametrización, y se ha observado que el diseño de la arista superior a barlovento es fundamental, siendo su influencia mayor que la longitud del testero o que la sección frontal del mismo. Finalmente, se ha considerado un escenario más a fin de validar estos métodos y su capacidad de encontrar un óptimo global. La entrada de un tren de alta velocidad en un túnel es uno de los casos más exigentes para un tren por el pico de sobrepresión generado, el cual afecta a la confortabilidad del pasajero, así como a la estabilidad del vehículo y al entorno próximo a la salida del túnel. Además de este problema, otro objetivo a minimizar es la resistencia aerodinámica, notablemente superior al caso de campo abierto. Este problema se resuelve usando algoritmos genéticos. Dicho método permite obtener un frente de Pareto donde se incluyen el conjunto de óptimos que minimizan ambos objetivos. ABSTRACT Aerodynamic design of trains influences several aspects of high-speed trains performance in a very significant level. In this situation, considering also that new aerodynamic problems have arisen due to the increase of the cruise speed and lightness of the vehicle, it is evident the necessity of proposing an optimization study concerning the train aerodynamics. Thus, the aerodynamic optimization of the nose shape of a high-speed train is presented in this thesis. This optimization is based on advanced optimization methods. Among these methods, genetic algorithms and the adjoint method have been selected. A theoretical description of their bases, the characteristics and the implementation of each method is detailed in this thesis. This introduction permits understanding the causes of their selection, and the advantages and drawbacks of their application. The genetic algorithms requirethe geometrical parameterization of any optimal candidate and the generation of a metamodel or surrogate model that complete the optimization process. These points are addressed with a special attention in the first block of the thesis, focused on the methodology considered in this study. The second block is referred to the use of these methods with the purpose of optimizing the aerodynamic performance of a high-speed train in several scenarios. These scenarios englobe the most representative operating conditions of high-speed trains, and also some of the most exigent train aerodynamic problems: front wind and cross-wind situations in open air, and the entrance of a high-speed train in a tunnel. The genetic algorithms and the adjoint method have been applied in the minimization of the aerodynamic drag on the train with front wind in open air. The comparison of these methods allows to evaluate the methdology and computational cost of each one, as well as the resulting minimization of the aerodynamic drag. Simplicity and robustness, the straightforward realization of a multi-objective optimization, and the capability of searching a global optimum are the main attributes of genetic algorithm. However, the requirement of geometrically parameterize any optimal candidate is a significant drawback that is avoided with the use of the adjoint method. This independence of the number of design variables leads to a relevant reduction of the pre-processing and computational cost. Considering the cross-wind stability, both methods are used again for the minimization of the side force. In this case, a simplification of the geometric parameterization of the train nose is adopted, what dramatically reduces the computational cost of the optimization process. Nevertheless, some of the most important geometrical characteristics are still described with this simplified parameterization. This analysis identifies and quantifies the influence of each design variable on the side force on the train. It is observed that the A-pillar roundness is the most demanding design parameter, with a more important effect than the nose length or the train cross-section area. Finally, a third scenario is considered for the validation of these methods in the aerodynamic optimization of a high-speed train. The entrance of a train in a tunnel is one of the most exigent train aerodynamic problems. The aerodynamic consequences of high-speed trains running in a tunnel are basically resumed in two correlated phenomena, the generation of pressure waves and an increase in aerodynamic drag. This multi-objective optimization problem is solved with genetic algorithms. The result is a Pareto front where a set of optimal solutions that minimize both objectives.

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Most CPV systems are based on Fresnel lenses. Among these, LPI-patented Fresnel-Köhler (FK) concentrator outstands owing to performance and practical reasons. The VentanaTM power train is the first off-the-shelf commercial product based on the FK and comprises both the primary (POE) lenses (a 36-units 1×1 m2 acrylic panel manufactured by EVONIK and 10×) and glass (or Savosil) secondary optics (SOE). This high concentration optical train (Cg=1,024×, ~250mm optical depth) fits with 5×5 mm2 (at least) solar cells. The optical train is the fruit of a 1-year development that has included design, modeling, prototyping and characterization, and through the process LPI had the opportunity to find out how well the actual performance correlates with models, but also learned practical aspects of a CPV system of this kind, some of which have very positive impact on system performance and reliability.

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Importancia del ejercicio en un tratamiento de pérdia de peso

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Los pasos inferiores son muy numerosos en las líneas de ferrocarril. Su comportamiento dinámico ha recibido mucha menos atención que el de otras estructuras como los puentes, pero su elevado número hace que su estudio sea económicamente relevante con vista a optimizar su forma, manteniendo la seguridad. El proyecto de puentes según el Eurocódigo incluye comprobaciones de estados límite de tensiones bajo carga dinámica. En el caso de pasos inferiores, las comprobaciones pueden resultar tan costosas como aquellas de puentes, pese a que su coste es mucho menor. Por tanto, se impone la búsqueda de unas reglas de cálculo simplificado que pongan en consonancia el coste de la estructura con el esfuerzo necesario para su proyecto. Este artículo propone un conjunto de reglas basadas en un estudio paramétrico = Underpasses are common in modern railway lines. Wildlife corridors and drainage conduits often fall into this category of partially buried structures. Their dynamic behavior has received far less attention than that of other structures such as bridges, but their large number makes their study an interesting challenge from the viewpoint of safety and cost savings. The bridge design rules in accordance with the Eurocode involve checks on stresses according to dynamic loading. In the case of underpasses, those checks may be as much as those for bridges. Therefore, simplified design rules may align the design effort with their cost. Such a set of rules may provide estimations of response parameters based on the key parameters influencing the result. This paper contains a proposal based on a parametric study.

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At present, engineering problems required quite a sophisticated calculation means. However, analytical models still can prove to be a useful tool for engineers and scientists when dealing with complex physical phenomena. The mathematical models developed to analyze three different engineering problems: photovoltaic devices analysis; cup anemometer performance; and high-speed train pressure wave effects in tunnels are described. In all cases, the results are quite accurate when compared to testing measurements.

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The optimization of the nose shape of a high-speed train entering a tunnel has been performed using genetic algorithms(GA).This optimization method requires the parameterization of each optimal candidate as a design vector.The geometrical parameterization of the nose has been defined using three design variables that include the most characteristic geometrical factors affecting the compression wave generated at the entry of the train and the aerodynamic drag of the train.

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When dealing with the design of a high-speed train, a multiobjective shape optimization problem is formulated, as these vehicles are object of many aerodynamic problems which are known to be in conflict. More mobility involves an increase in both the cruise speed and lightness, and these requirements directly influence the stability and the ride comfort of the passengers when the train is subjected to a side wind. Thus, crosswind stability plays a more relevant role among the aerodynamic objectives to be optimized. An extensive research activity is observed on aerodynamic response in crosswind conditions.

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Genetic algorithms (GA) have been used for the minimization of the aerodynamic drag of a train subject to front wind. The significant importance of the external aerodynamic drag on the total resistance a train experiments as the cruise speed is increased highlights the interest of this study. A complete description of the methodology required for this optimization method is introduced here, where the parameterization of the geometry to be optimized and the metamodel used to speed up the optimization process are detailed. A reduction of about a 25% of the initial aerodynamic drag is obtained in this study, what confirms GA as a proper method for this optimization problem. The evolution of the nose shape is consistent with the literature. The advantage of using metamodels is stressed thanks to the information of the whole design space extracted from it. The influence of each design variable on the objective function is analyzed by means of an ANOVA test.