868 resultados para methodology for cataloguing


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Atmospheric emissions from road transport have increased all around the world during the last decades more rapidly than from other pollution sources. For instance, they contribute to more than 25% of total CO, CO2, NOx, and fine particle emissions in most of the European countries. This situation shows the importance of road transport when complying with emission ceilings and air quality standards applied to these pollutants. This paper presents a modelling system to perform atmospheric emission projections (simultaneously both air quality pollutants and greenhouse gases) from road transport including the development of a tailored software tool (EmiTRANS) as a planning tool. The methodology has been developed with two purposes: 1) to obtain outputs used as inputs to the COPERT4 software to calculate emission projections and 2) to summarize outputs for policy making evaluating the effect of emission abatement measures for a vehicle fleet. This methodology has been applied to the calculation of emission projections in Spain up to 2020 under several scenarios, including a sensitivity analysis useful for a better interpretation and confidence building on the results. This case study demonstrates the EmiTRANS applicability to a country, and points out the need for combining both technical and non-technical measures (such as behavioural changes or demand management) to reduce emissions, indirectly improving air quality and contributing to mitigate climate change.

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Civil buildings are not specifically designed to support blast loads, but it is important to take into account these potential scenarios because of their catastrophic effects, on persons and structures. A practical way to consider explosions on reinforced concrete structures is necessary. With this objective we propose a methodology to evaluate blast loads on large concrete buildings, using LS-DYNA code for calculation, with Lagrangian finite elements and explicit time integration. The methodology has three steps. First, individual structural elements of the building like columns and slabs are studied, using continuum 3D elements models subjected to blast loads. In these models reinforced concrete is represented with high precision, using advanced material models such as CSCM_CONCRETE model, and segregated rebars constrained within the continuum mesh. Regrettably this approach cannot be used for large structures because of its excessive computational cost. Second, models based on structural elements are developed, using shells and beam elements. In these models concrete is represented using CONCRETE_EC2 model and segregated rebars with offset formulation, being calibrated with continuum elements models from step one to obtain the same structural response: displacement, velocity, acceleration, damage and erosion. Third, models basedon structural elements are used to develop large models of complete buildings. They are used to study the global response of buildings subjected to blast loads and progressive collapse. This article carries out different techniques needed to calibrate properly the models based on structural elements, using shells and beam elements, in order to provide results of sufficient accuracy that can be used with moderate computational cost.

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In order to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. Transport modelling literature has been increasingly aware that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users’ social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced; but links between international and Spanish perspectives are rarely dealt with. The overall objective of the thesis is to develop a stepped methodology that integrate diverse perspectives to evaluate the willingness to change patterns of urban mobility in Madrid, based on four steps: (1st) analysis of causal relationships between both objective and subjective personal variables, and travel behavior to capture pro-car and pro-public transport intentions; (2nd) exploring the potential influence of individual trip characteristics and social influence variables on transport mode choice; (3rd) identifying built environment dimensions on travel behavior; and (4th) exploring the potential influence on transport mode choice of extrinsic characteristics of individual trip using panel data, land use variables using spatial characteristics and social influence variables. The data used for this thesis have been collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) carried out in Madrid. Although the steps above are mainly methodological, the application to the area of Madrid allows deriving important results that can be directly used to forecast travel demand and to evaluate the benefits of specific policies that might be implemented in the area. The results demonstrated, respectively: (1st) transport policy actions are more likely to be effective when pro-car intention has been disrupted first; (2nd) the consideration of “helped” and “voluntary” users as tested here could have a positive and negative impact, respectively, on the use of public transport; (3rd) the importance of density, design, diversity and accessibility underlying dimensions responsible for land use variables; and (4th) there are clearly different types of combinations of social interactions, land use and time frame on travel behavior studies. Finally, with the objective to study the impact of demand measures to change urban mobility behavior, those previous results have been considered in a unique way, a hybrid discrete choice model has been used on a 5th step. Then it can be concluded that urban mobility behavior is not only ruled by the maximum utility criterion, but also by a strong psychological-environment concept, developed without the mediation of cognitive processes during choice, i.e., many people using public transport on their way to work do not do it for utilitarian reasons, but because no other choice is available. Regarding built environment dimensions, the more diversity place of residence, the more difficult the use of public transport or walking.

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Descripción y análisis critic de una metodología de taller de posgrado a realizar entre dos universidades en idioma ingles y con el apoyo de las nuevas tecnologías

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In the European context of upgrading the housing stock energy performance, multiple barriers hinder the wide uptake of sustainable retrofitting practices. Moreover, some of these may imply negative effects often disregarded. Policy makers need to identify how to increase and improve retrofitting practices from the comprehensive point of view of sustainability. None of the existing assessment tools addresses all the issues relevant for sustainable development in a local situation from a life cycle perspective. Life cycle sustainability assessment methodology, or LCSA, analyzes environmental and socioeconomic impacts. The environmental part is quite developed, but the socioeconomic aspect is still challenging. This work proposes socioeconomic criteria to be included in a LCSA to assess retrofitting works in the specific context of Brussels-Capital Region. LCSA feasibility and challenging methodology aspects are discussed.

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Advanced composite materials are increasingly used in the strengthening of reinforced concrete (RC) structures. The use of externally bonded strips made of fibre-reinforced plastics (FRP) as strengthening method has gained widespread acceptance in recent years since it has many advantages over the traditional techniques. However, unfortunately, this strengthening method is often associated with a brittle and sudden failure caused by some form of FRP bond failure, originated at the termination of the FRP material or at intermediate areas in the vicinity of flexural cracks in the RC beam. Up to date, little effort in the early prediction of the debonding in its initial instants even though this effect is not noticeable by simple visual observation. An early detection of this phenomenon might help in taking actions to prevent future catastrophes. Fibre-optic Bragg grating (FBG) sensors are able to measure strains locally with high resolution and accuracy. Furthermore, as their physical size is extremely small compared with other strain measuring components, it enables to be embedded at the concrete-FRP interface for determining the strain distribution without influencing the mechanical properties of the host materials. This paper shows the development of a debonding identification methodology based on strains experimentally measured. For, it a simplified model is implemented to simulate the behaviour of FRP-strengthened reinforced concrete beams. This model is taken as a basis to. develop an model updating procedure able to detect minor debonding at the concrete-FRP interface from experimental strains obtained by using FBG sensors embedded at the interface

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This paper develops a model to analyze the upside potential of profitability of the SAREB (“Asset Management Company for Assets Arising from Bank Restructuring”), the Spanish “Bad Bank”. The model is based in the Real Options methodology, that is especially adequate due to the convergence of two elements, (i) depreciated assets with a high upside potential, and (ii) a highly volatile market as it has shown to be the real estate Spanish market. Our results suggest that the SAREB has a higher than expected profitability potentialthat would be dedicated to increase the return to its shareholders, mainly private banks. Consequently we also show that after the financial crisis are emerging two types of banks in Spain, in one hand the losers who are transferring their real estate assets at a deep discount, and in the other hand the winners, capturing the upside potential of those assets as shareholders of SAREB, and consequently consolidating their strength in the Spanish Real Estate Industry. It is worth to mention that Governments should make an effort in properly redistribute the wealth generated by the real Estate industry.

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Urban mobility in Europe is always a responsibility of the municipalities which propose measures to reduce CO2 emissions in terms of mobility aimed at reducing individual private transport (car). The European Commission's Action Plan on Urban Mobility calls for an increase in the take-up of Sustainable Urban Mobility Plans in Europe. SUMPs aim to create a sustainable urban transport system. Europe has got some long term initiatives and has been using some evaluation procedures, many of them through European projects. Nevertheless, the weak point with the SUMPs in Spain, has been the lack of concern about the evaluation and the effectiveness of the measures implemented in a SUMP. For this reason, it is difficult to know exactly whether or not the SUMPs have positively influenced in the modal split of the cities, and its contribution to reduce CO2 levels. The case of the City of Burgos is a very illustrative example as it developed a CiViTAS project during the years 2005-2009, with a total investment of 6M?. The results have been considered as ?very successful? even at European level. The modal split has changed considerably for better, The cost-effectiveness ratio of the SUMP in the city can be measured with the CO2 ton saved, specifically 36 ? per CO2 ton saved, which is fully satisfactory and in line with calculations from other European researchers. Additionally, the authors propose a single formula to measure the effectiveness of the activities developed under the umbrella of a SUMP.

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The main problem to study vertical drainage from the moisture distribution, on a vertisol profile, is searching for suitable methods using these procedures. Our aim was to design a digital image processing methodology and its analysis to characterize the moisture content distribution of a vertisol profile. In this research, twelve soil pits were excavated on a ba re Mazic Pellic Vertisols ix of them in May 13/2011 and the rest in May 19 /2011 after a moderate rainfall event. Digital RGB images were taken from each vertisol pit using a Kodak? camera selecting a size of 1600x945 pixels. Each soil image was processed to homogenized brightness and then a spatial filter with several window sizes was applied to select the optimum one. The RGB image obtained were divided in each matrix color selecting the best thresholds for each one, maximum and minimum, to be applied and get a digital binary pattern. This one was analyzed by estimating two fractal scaling exponents box counting dimension D BC) and interface fractal dimension (D) In addition, three pre-fractal scaling coefficients were determinate at maximum resolution: total number of boxes intercepting the foreground pattern (A), fractal lacunarity (?1) and Shannon entropy S1). For all the images processed the spatial filter 9x9 was the optimum based on entropy, cluster and histogram criteria. Thresholds for each color were selected based on bimodal histograms.

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Fresnel lenses used as primary optics in concentrating photovoltaic modules may show warping produced by lens manufacturing or module assembly (e.g., stress during molding or weight load) or due to stress during operation (e.g., mismatch of thermal expansion between different materials). To quantify this problem, a simple method called “checkerboard method” is presented. The proposed method identifies shape errors on the front surface of primary lenses by analyzing the Fresnel reflections. This paper also deals with the quantification of the effects these curvatures have on their optical performance and on the electrical performance of concentrating modules incorporating them. This method can be used to perform quality control of Fresnel lenses in scenarios of high volume production.

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A methodology for developing an advanced communications system for the Deaf in a new domain is presented in this paper. This methodology is a user-centred design approach consisting of four main steps: requirement analysis, parallel corpus generation, technology adaptation to the new domain, and finally, system evaluation. During the requirement analysis, both the user and technical requirements are evaluated and defined. For generating the parallel corpus, it is necessary to collect Spanish sentences in the new domain and translate them into LSE (Lengua de Signos Española: Spanish Sign Language). LSE is represented by glosses and using video recordings. This corpus is used for training the two main modules of the advanced communications system to the new domain: the spoken Spanish into the LSE translation module and the Spanish generation from the LSE module. The main aspects to be generated are the vocabularies for both languages (Spanish words and signs), and the knowledge for translating in both directions. Finally, the field evaluation is carried out with deaf people using the advanced communications system to interact with hearing people in several scenarios. In this evaluation, the paper proposes several objective and subjective measurements for evaluating the performance. In this paper, the new considered domain is about dialogues in a hotel reception. Using this methodology, the system was developed in several months, obtaining very good performance: good translation rates (10% Sign Error Rate) with small processing times, allowing face-to-face dialogues.

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We consider the situation where there are several alternatives for investing a quantity of money to achieve a set of objectives. The choice of which alternative to apply depends on how citizens and political representatives perceive that such objectives should be achieved. All citizens with the right to vote can express their preferences in the decision-making process. These preferences may be incomplete. Political representatives represent the citizens who have not taken part in the decision-making process. The weight corresponding to political representatives depends on the number of citizens that have intervened in the decision-making process. The methodology we propose needs the participants to specify for each alternative how they rate the different attributes and the relative importance of attributes. On the basis of this information an expected utility interval is output for each alternative. To do this, an evidential reasoning approach is applied. This approach improves the insightfulness and rationality of the decision-making process using a belief decision matrix for problem modeling and the Dempster?Shafer theory of evidence for attribute aggregation. Finally, we propose using the distances of each expected utility interval from the maximum and the minimum utilities to rank the alternative set. The basic idea is that an alternative is ranked first if its distance to the maximum utility is the smallest, and its distance to the minimum utility is the greatest. If only one of these conditions is satisfied, a distance ratio is then used.

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El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

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La electrónica digital moderna presenta un desafío a los diseñadores de sistemas de potencia. El creciente alto rendimiento de microprocesadores, FPGAs y ASICs necesitan sistemas de alimentación que cumplan con requirimientos dinámicos y estáticos muy estrictos. Específicamente, estas alimentaciones son convertidores DC-DC de baja tensión y alta corriente que necesitan ser diseñados para tener un pequeño rizado de tensión y una pequeña desviación de tensión de salida bajo transitorios de carga de una alta pendiente. Además, dependiendo de la aplicación, se necesita cumplir con otros requerimientos tal y como proveer a la carga con ”Escalado dinámico de tensión”, donde el convertidor necesitar cambiar su tensión de salida tan rápidamente posible sin sobreoscilaciones, o ”Posicionado Adaptativo de la Tensión” donde la tensión de salida se reduce ligeramente cuanto más grande sea la potencia de salida. Por supuesto, desde el punto de vista de la industria, las figuras de mérito de estos convertidores son el coste, la eficiencia y el tamaño/peso. Idealmente, la industria necesita un convertidor que es más barato, más eficiente, más pequeño y que aún así cumpla con los requerimienos dinámicos de la aplicación. En este contexto, varios enfoques para mejorar la figuras de mérito de estos convertidores se han seguido por la industria y la academia tales como mejorar la topología del convertidor, mejorar la tecnología de semiconducores y mejorar el control. En efecto, el control es una parte fundamental en estas aplicaciones ya que un control muy rápido hace que sea más fácil que una determinada topología cumpla con los estrictos requerimientos dinámicos y, consecuentemente, le da al diseñador un margen de libertar más amplio para mejorar el coste, la eficiencia y/o el tamaño del sistema de potencia. En esta tesis, se investiga cómo diseñar e implementar controles muy rápidos para el convertidor tipo Buck. En esta tesis se demuestra que medir la tensión de salida es todo lo que se necesita para lograr una respuesta casi óptima y se propone una guía de diseño unificada para controles que sólo miden la tensión de salida Luego, para asegurar robustez en controles muy rápidos, se proponen un modelado y un análisis de estabilidad muy precisos de convertidores DC-DC que tienen en cuenta circuitería para sensado y elementos parásitos críticos. También, usando este modelado, se propone una algoritmo de optimización que tiene en cuenta las tolerancias de los componentes y sensados distorsionados. Us ando este algoritmo, se comparan controles muy rápidos del estado del arte y su capacidad para lograr una rápida respuesta dinámica se posiciona según el condensador de salida utilizado. Además, se propone una técnica para mejorar la respuesta dinámica de los controladores. Todas las propuestas se han corroborado por extensas simulaciones y prototipos experimentales. Con todo, esta tesis sirve como una metodología para ingenieros para diseñar e implementar controles rápidos y robustos de convertidores tipo Buck. ABSTRACT Modern digital electronics present a challenge to designers of power systems. The increasingly high-performance of microprocessors, FPGAs (Field Programmable Gate Array) and ASICs (Application-Specific Integrated Circuit) require power supplies to comply with very demanding static and dynamic requirements. Specifically, these power supplies are low-voltage/high-current DC-DC converters that need to be designed to exhibit low voltage ripple and low voltage deviation under high slew-rate load transients. Additionally, depending on the application, other requirements need to be met such as to provide to the load ”Dynamic Voltage Scaling” (DVS), where the converter needs to change the output voltage as fast as possible without underdamping, or ”Adaptive Voltage Positioning” (AVP) where the output voltage is slightly reduced the greater the output power. Of course, from the point of view of the industry, the figures of merit of these converters are the cost, efficiency and size/weight. Ideally, the industry needs a converter that is cheaper, more efficient, smaller and that can still meet the dynamic requirements of the application. In this context, several approaches to improve the figures of merit of these power supplies are followed in the industry and academia such as improving the topology of the converter, improving the semiconductor technology and improving the control. Indeed, the control is a fundamental part in these applications as a very fast control makes it easier for the topology to comply with the strict dynamic requirements and, consequently, gives the designer a larger margin of freedom to improve the cost, efficiency and/or size of the power supply. In this thesis, how to design and implement very fast controls for the Buck converter is investigated. This thesis proves that sensing the output voltage is all that is needed to achieve an almost time-optimal response and a unified design guideline for controls that only sense the output voltage is proposed. Then, in order to assure robustness in very fast controls, a very accurate modeling and stability analysis of DC-DC converters is proposed that takes into account sensing networks and critical parasitic elements. Also, using this modeling approach, an optimization algorithm that takes into account tolerances of components and distorted measurements is proposed. With the use of the algorithm, very fast analog controls of the state-of-the-art are compared and their capabilities to achieve a fast dynamic response are positioned de pending on the output capacitor. Additionally, a technique to improve the dynamic response of controllers is also proposed. All the proposals are corroborated by extensive simulations and experimental prototypes. Overall, this thesis serves as a methodology for engineers to design and implement fast and robust controls for Buck-type converters.

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Las terminales de contenedores son sistemas complejos en los que un elevado número de actores económicos interactúan para ofrecer servicios de alta calidad bajo una estricta planificación y objetivos económicos. Las conocidas como "terminales de nueva generación" están diseñadas para prestar servicio a los mega-buques, que requieren tasas de productividad que alcanzan los 300 movimientos/ hora. Estas terminales han de satisfacer altos estándares dado que la competitividad entre terminales es elevada. Asegurar la fiabilidad de las planificaciones del atraque es clave para atraer clientes, así como reducir al mínimo el tiempo que el buque permanece en el puerto. La planificación de las operaciones es más compleja que antaño, y las tolerancias para posibles errores, menores. En este contexto, las interrupciones operativas deben reducirse al mínimo. Las principales causas de dichas perturbaciones operacionales, y por lo tanto de incertidumbre, se identifican y caracterizan en esta investigación. Existen una serie de factores que al interactuar con la infraestructura y/o las operaciones desencadenan modos de fallo o parada operativa. Los primeros pueden derivar no solo en retrasos en el servicio sino que además puede tener efectos colaterales sobre la reputación de la terminal, o incluso gasto de tiempo de gestión, todo lo cual supone un impacto para la terminal. En el futuro inmediato, la monitorización de las variables operativas presenta gran potencial de cara a mejorar cualitativamente la gestión de las operaciones y los modelos de planificación de las terminales, cuyo nivel de automatización va en aumento. La combinación del criterio experto con instrumentos que proporcionen datos a corto y largo plazo es fundamental para el desarrollo de herramientas que ayuden en la toma de decisiones, ya que de este modo estarán adaptadas a las auténticas condiciones climáticas y operativas que existen en cada emplazamiento. Para el corto plazo se propone una metodología con la que obtener predicciones de parámetros operativos en terminales de contenedores. Adicionalmente se ha desarrollado un caso de estudio en el que se aplica el modelo propuesto para obtener predicciones de la productividad del buque. Este trabajo se ha basado íntegramente en datos proporcionados por una terminal semi-automatizada española. Por otro lado, se analiza cómo gestionar, evaluar y mitigar el efecto de las interrupciones operativas a largo plazo a través de la evaluación del riesgo, una forma interesante de evaluar el effecto que eventos inciertos pero probables pueden generar sobre la productividad a largo plazo de la terminal. Además se propone una definición de riesgo operativo junto con una discusión de los términos que representan con mayor fidelidad la naturaleza de las actividades y finalmente, se proporcionan directrices para gestionar los resultados obtenidos. Container terminals are complex systems where a large number of factors and stakeholders interact to provide high-quality services under rigid planning schedules and economic objectives. The socalled next generation terminals are conceived to serve the new mega-vessels, which are demanding productivity rates up to 300 moves/hour. These terminals need to satisfy high standards because competition among terminals is fierce. Ensuring reliability in berth scheduling is key to attract clients, as well as to reduce at a minimum the time that vessels stay the port. Because of the aforementioned, operations planning is becoming more complex, and the tolerances for errors are smaller. In this context, operational disturbances must be reduced at a minimum. The main sources of operational disruptions and thus, of uncertainty, are identified and characterized in this study. External drivers interact with the infrastructure and/or the activities resulting in failure or stoppage modes. The later may derive not only in operational delays but in collateral and reputation damage or loss of time (especially management times), all what implies an impact for the terminal. In the near future, the monitoring of operational variables has great potential to make a qualitative improvement in the operations management and planning models of terminals that use increasing levels of automation. The combination of expert criteria with instruments that provide short- and long-run data is fundamental for the development of tools to guide decision-making, since they will be adapted to the real climatic and operational conditions that exist on site. For the short-term a method to obtain operational parameter forecasts in container terminals. To this end, a case study is presented, in which forecasts of vessel performance are obtained. This research has been entirely been based on data gathered from a semi-automated container terminal from Spain. In the other hand it is analyzed how to manage, evaluate and mitigate disruptions in the long-term by means of the risk assessment, an interesting approach to evaluate the effect of uncertain but likely events on the long-term throughput of the terminal. In addition, a definition for operational risk evaluation in port facilities is proposed along with a discussion of the terms that better represent the nature of the activities involved and finally, guidelines to manage the results obtained are provided.