13 resultados para Marine systems modelling

em Universidad Politécnica de Madrid


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This paper focuses on the implementation of fuel cells in marine systems as a propulsion system and energy source. The objective is to provide an overview of the pertinent legislation for marine applications of fuel cells. This work includes a characterization of some guidelines for the safe application of fuel cell systems on ships. It also describes two ships that have implemented fuel cells to obtain energy, the Viking Lady, the first marine ship to include this technology, and Greentug, a reference for new tugs

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Maximizing energy autonomy is a consistent challenge when deploying mobile robots in ionizing radiation or other hazardous environments. Having a reliable robot system is essential for successful execution of missions and to avoid manual recovery of the robots in environments that are harmful to human beings. For deployment of robots missions at short notice, the ability to know beforehand the energy required for performing the task is essential. This paper presents a on-line method for predicting energy requirements based on the pre-determined power models for a mobile robot. A small mobile robot, Khepera III is used for the experimental study and the results are promising with high prediction accuracy. The applications of the energy prediction models in energy optimization and simulations are also discussed along with examples of significant energy savings.

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The paper describes some relevant results of an on-going research aiming to elaborate a methodology to help the mobility management in natural parks, compatible with their protection missions: it has been developed a procedure to reproduce the mobility-environment relationships in various operational conditions. The final purpose is the identification of: a) the effects of various choices in transport planning, both at long term and strategic level; b) the most effective policies of mobility management. The work is articulated in the following steps: 1) definition of protected area on the basis of ecological and socio-economic criteria and legislative constraints; 2) analysis of mobility needs in the protected areas; 3) reconstruction of the state of the art of mobility management in natural parks at European level; 4) analysis of used traffic flows measurement methods; 5) analysis of environmental impacts due to transport systems modelling (air pollution and noise only); 6) identification of mitigation measures to be potentially applied. The whole methodology has been tested and validated on Italian case studies: i) the concerned area has been zoned according to the land-use peculiarities; ii) the local situations of transport infrastructure (roads and parking), services (public transport systems) and rules (traffic regulations) have been mapped with references to physical and functional attributes; iii) the mobility, both systematic and touristic, has been represented in an origin-destination matrix. By means of an assignment model the flows have been distributed and the corresponding average speeds to quantify gaseous and noise emissions was calculated, the criticalities in the reference scenario have been highlighted, as well as some alternative scenarios, including both operational and infrastructural measures have been identified. The comparison between projects and reference scenario allowed the quantification of effects (variation of emissions) for each scenario and a selection of the most effective management actions to be taken.

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The final purpose is the identification of: a) the effects of various choices in transport planning, both at long term and strategic level; b) the most effective policies of mobility management. The preliminary work was articulated in the following steps: 1) definition of protected area on the basis of ecological and socio-economic criteria and legislative constraints; 2) analysis of mobility needs in the protected areas; 3) reconstruction of the state of the art of mobility management in natural parks at European level; 4) analysis of used traffic flows measurement methods; 5) analysis of environmental impacts due to transport systems modelling (limited to air pollution and noise); 6) identification of mitigation measures to the potentially applied. The whole methodology has been firstly tested on the case study of the National Park of ?Gran Sasso and Monti della Laga? and further validated on the National Park of ?Gargano?, both located Italy: i) the concerned area has been zoned according to the land-use peculiarities; ii) the local situations of transport infrastructure (roads and parking), services (public transport systems) and rules (traffic regulations) have been mapped with references to physical and functional attributes; iii) the mobility, both systematic and touristic, has been synthetically represented in an origin-destination matrix. By means of an assignment model it has been determined the distribution of flows and the corresponding average speeds to quantify gaseous and noise emissions. On this basis the environmental criticalities in the reference scenario have been highlighted, as well as some alternative scenarios including both operational and infrastructural measures have been identified. The comparison between the projects and the reference scenario allowed the quantification of the effects (variation of emissions) for each scenario and a selection of the most effective management actions to be taken.

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Systems of Systems (SoS) present challenging features and existing tools result often inadequate for their analysis, especially for heteregeneous networked infrastructures. Most accident scenarios in networked systems cannot be addressed by a simplistic black or white (i.e. functioning or failed) approach. Slow deviations from nominal operation conditions may cause degraded behaviours that suddenly end up into unexpected malfunctioning, with large portions of the network affected. In this paper,we present a language for modelling networked SoS. The language makes it possible to represent interdependencies of various natures, e.g. technical, organizational and human. The representation of interdependencies is based on control relationships that exchange physical quantities and related information. The language also makes it possible the identification of accident scenarios, by representing the propagation of failure events throughout the network. The results can be used for assessing the effectiveness of those mechanisms and measures that contribute to the overall resilience, both in qualitative and quantitative terms. The presented modelling methodology is general enough to be applied in combination with already existing system analysis techniques, such as risk assessment, dependability and performance evaluation

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We develop a simplified model of choked flow in pipes for CO2-water solutions as an important step in the modelling of a whole hydraulic system with the intention of eliminating the carbon dioxide generated in air-independent submarine propulsion. The model is based on an approximate fitting of the homogeneous isentropic solution upstream of a valve (or any other area restriction), for given fluid conditions at the entrance. The relative maximum choking back-pressure is computed as a function of area restriction ratio. Although the procedure is generic for gas solutions, numeric values for the non-dimensional parameters in the analysis are developed only for choking in the case of carbon dioxide solutions up to the pure-water limit.

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The aim of this paper is to explain the chloride concentration profiles obtained experimentally from control samples of an offshore platform after 25 years of service life. The platform is located 12 km off the coast of the Brazilian province Rio Grande do Norte, in the north-east of Brazil. The samples were extracted at different orientations and heights above mean sea level. A simple model based on Fick’s second law is considered and compared with a finite element model which takes into account transport of chloride ions by diffusion and convection. Results show that convective flows significantly affect the studied chloride penetrations. The convection velocity is obtained by fitting the finite element solution to the experimental data and seems to be directly proportional to the height above mean sea level and also seems to depend on the orientation of the face of the platform. This work shows that considering solely diffusion as transport mechanism does not allow a good prediction of the chloride profiles. Accounting for capillary suction due to moisture gradients permits a better interpretation of the material’s behaviour.

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The aim of this chapter is to discuss the applicability of recently proposed knowledge modelling tools to the development of agent-based systems. The discussion is derived from the real world experience of a particular software tool called KSM (Knowledge Structure Manager). The chapter provides details about this tool and then proceeds to show in which forms the software may be used to support the development of agent-based systems. Two multiagent systems, one in the field of telecommunications management and the other one in the field of flood control, are described. Conclusions about these studies are presented, summarizing the main contributions that knowledge modelling tools can bring to the development of agent-based systems.

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This paper presents the knowledge model of a distributed decision support system, that has been designed for the management of a national network in Ukraine. It shows how advanced Artificial Intelligence techniques (multiagent systems and knowledge modelling) have been applied to solve this real-world decision support problem: on the one hand its distributed nature, implied by different loci of decision-making at the network nodes, suggested to apply a multiagent solution; on the other, due to the complexity of problem-solving for local network administration, it was useful to apply knowledge modelling techniques, in order to structure the different knowledge types and reasoning processes involved. The paper sets out from a description of our particular management problem. Subsequently, our agent model is described, pointing out the local problem-solving and coordination knowledge models. Finally, the dynamics of the approach is illustrated by an example.

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Hybrid Stepper Motors are widely used in open-loop position applications. They are the choice of actuation for the collimators in the Large Hadron Collider, the largest particle accelerator at CERN. In this case the positioning requirements and the highly radioactive operating environment are unique. The latter forces both the use of long cables to connect the motors to the drives which act as transmission lines and also prevents the use of standard position sensors. However, reliable and precise operation of the collimators is critical for the machine, requiring the prevention of step loss in the motors and maintenance to be foreseen in case of mechanical degradation. In order to make the above possible, an approach is proposed for the application of an Extended Kalman Filter to a sensorless stepper motor drive, when the motor is separated from its drive by long cables. When the long cables and high frequency pulse width modulated control voltage signals are used together, the electrical signals difer greatly between the motor and drive-side of the cable. Since in the considered case only drive-side data is available, it is therefore necessary to estimate the motor-side signals. Modelling the entire cable and motor system in an Extended Kalman Filter is too computationally intensive for standard embedded real-time platforms. It is, in consequence, proposed to divide the problem into an Extended Kalman Filter, based only on the motor model, and separated motor-side signal estimators, the combination of which is less demanding computationally. The efectiveness of this approach is shown in simulation. Then its validity is experimentally demonstrated via implementation in a DSP based drive. A testbench to test its performance when driving an axis of a Large Hadron Collider collimator is presented along with the results achieved. It is shown that the proposed method is capable of achieving position and load torque estimates which allow step loss to be detected and mechanical degradation to be evaluated without the need for physical sensors. These estimation algorithms often require a precise model of the motor, but the standard electrical model used for hybrid stepper motors is limited when currents, which are high enough to produce saturation of the magnetic circuit, are present. New model extensions are proposed in order to have a more precise model of the motor independently of the current level, whilst maintaining a low computational cost. It is shown that a significant improvement in the model It is achieved with these extensions, and their computational performance is compared to study the cost of model improvement versus computation cost. The applicability of the proposed model extensions is demonstrated via their use in an Extended Kalman Filter running in real-time for closed-loop current control and mechanical state estimation. An additional problem arises from the use of stepper motors. The mechanics of the collimators can wear due to the abrupt motion and torque profiles that are applied by them when used in the standard way, i.e. stepping in open-loop. Closed-loop position control, more specifically Field Oriented Control, would allow smoother profiles, more respectful to the mechanics, to be applied but requires position feedback. As mentioned already, the use of sensors in radioactive environments is very limited for reliability reasons. Sensorless control is a known option but when the speed is very low or zero, as is the case most of the time for the motors used in the LHC collimator, the loss of observability prevents its use. In order to allow the use of position sensors without reducing the long term reliability of the whole system, the possibility to switch from closed to open loop is proposed and validated, allowing the use of closed-loop control when the position sensors function correctly and open-loop when there is a sensor failure. A different approach to deal with the switched drive working with long cables is also presented. Switched mode stepper motor drives tend to have poor performance or even fail completely when the motor is fed through a long cable due to the high oscillations in the drive-side current. The design of a stepper motor output fillter which solves this problem is thus proposed. A two stage filter, one devoted to dealing with the diferential mode and the other with the common mode, is designed and validated experimentally. With this ?lter the drive performance is greatly improved, achieving a positioning repeatability even better than with the drive working without a long cable, the radiated emissions are reduced and the overvoltages at the motor terminals are eliminated.

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The aim of this paper is to explain the chloride concentration profiles obtained experimentally from control samples of an offshore platform after 25 years of service life. The platform is located 12 km off the coast of the Brazilian province Rio Grande do Norte, in the north-east of Brazil. The samples were extracted at different orientations and heights above mean sea level. A simple model based on Fick’s second law is considered and compared with a finite element model which takes into account transport of chloride ions by diffusion and convection. Results show that convective flows significantly affect the studied chloride penetrations. The convection velocity is obtained by fitting the finite element solution to the experimental data and seems to be directly proportional to the height above mean sea level and also seems to depend on the orientation of the face of the platform. This work shows that considering solely diffusion as transport mechanism does not allow a good prediction of the chloride profiles. Accounting for capillary suction due to moisture gradients permits a better interpretation of the material’s behaviour

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Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning médium and long-term ?the modus operandi? of these organizations. Despite the growing importance of these systems, most proposals do not include its total evelopment, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.

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La diabetes comprende un conjunto de enfermedades metabólicas que se caracterizan por concentraciones de glucosa en sangre anormalmente altas. En el caso de la diabetes tipo 1 (T1D, por sus siglas en inglés), esta situación es debida a una ausencia total de secreción endógena de insulina, lo que impide a la mayoría de tejidos usar la glucosa. En tales circunstancias, se hace necesario el suministro exógeno de insulina para preservar la vida del paciente; no obstante, siempre con la precaución de evitar caídas agudas de la glucemia por debajo de los niveles recomendados de seguridad. Además de la administración de insulina, las ingestas y la actividad física son factores fundamentales que influyen en la homeostasis de la glucosa. En consecuencia, una gestión apropiada de la T1D debería incorporar estos dos fenómenos fisiológicos, en base a una identificación y un modelado apropiado de los mismos y de sus sorrespondientes efectos en el balance glucosa-insulina. En particular, los sistemas de páncreas artificial –ideados para llevar a cabo un control automático de los niveles de glucemia del paciente– podrían beneficiarse de la integración de esta clase de información. La primera parte de esta tesis doctoral cubre la caracterización del efecto agudo de la actividad física en los perfiles de glucosa. Con este objetivo se ha llevado a cabo una revisión sistemática de la literatura y meta-análisis que determinen las respuestas ante varias modalidades de ejercicio para pacientes con T1D, abordando esta caracterización mediante unas magnitudes que cuantifican las tasas de cambio en la glucemia a lo largo del tiempo. Por otro lado, una identificación fiable de los periodos con actividad física es un requisito imprescindible para poder proveer de esa información a los sistemas de páncreas artificial en condiciones libres y ambulatorias. Por esta razón, la segunda parte de esta tesis está enfocada a la propuesta y evaluación de un sistema automático diseñado para reconocer periodos de actividad física, clasificando su nivel de intensidad (ligera, moderada o vigorosa); así como, en el caso de periodos vigorosos, identificando también la modalidad de ejercicio (aeróbica, mixta o de fuerza). En este sentido, ambos aspectos tienen una influencia específica en el mecanismo metabólico que suministra la energía para llevar a cabo el ejercicio y, por tanto, en las respuestas glucémicas en T1D. En este trabajo se aplican varias combinaciones de técnicas de aprendizaje máquina y reconocimiento de patrones sobre la fusión multimodal de señales de acelerometría y ritmo cardíaco, las cuales describen tanto aspectos mecánicos del movimiento como la respuesta fisiológica del sistema cardiovascular ante el ejercicio. Después del reconocimiento de patrones se incorpora también un módulo de filtrado temporal para sacar partido a la considerable coherencia temporal presente en los datos, una redundancia que se origina en el hecho de que en la práctica, las tendencias en cuanto a actividad física suelen mantenerse estables a lo largo de cierto tiempo, sin fluctuaciones rápidas y repetitivas. El tercer bloque de esta tesis doctoral aborda el tema de las ingestas en el ámbito de la T1D. En concreto, se propone una serie de modelos compartimentales y se evalúan éstos en función de su capacidad para describir matemáticamente el efecto remoto de las concetraciones plasmáticas de insulina exógena sobre las tasas de eleiminación de la glucosa atribuible a la ingesta; un aspecto hasta ahora no incorporado en los principales modelos de paciente para T1D existentes en la literatura. Los datos aquí utilizados se obtuvieron gracias a un experimento realizado por el Institute of Metabolic Science (Universidad de Cambridge, Reino Unido) con 16 pacientes jóvenes. En el experimento, de tipo ‘clamp’ con objetivo variable, se replicaron los perfiles individuales de glucosa, según lo observado durante una visita preliminar tras la ingesta de una cena con o bien alta carga glucémica, o bien baja. Los seis modelos mecanísticos evaluados constaban de: a) submodelos de doble compartimento para las masas de trazadores de glucosa, b) un submodelo de único compartimento para reflejar el efecto remoto de la insulina, c) dos tipos de activación de este mismo efecto remoto (bien lineal, bien con un punto de corte), y d) diversas condiciones iniciales. ABSTRACT Diabetes encompasses a series of metabolic diseases characterized by abnormally high blood glucose concentrations. In the case of type 1 diabetes (T1D), this situation is caused by a total absence of endogenous insulin secretion, which impedes the use of glucose by most tissues. In these circumstances, exogenous insulin supplies are necessary to maintain patient’s life; although caution is always needed to avoid acute decays in glycaemia below safe levels. In addition to insulin administrations, meal intakes and physical activity are fundamental factors influencing glucose homoeostasis. Consequently, a successful management of T1D should incorporate these two physiological phenomena, based on an appropriate identification and modelling of these events and their corresponding effect on the glucose-insulin balance. In particular, artificial pancreas systems –designed to perform an automated control of patient’s glycaemia levels– may benefit from the integration of this type of information. The first part of this PhD thesis covers the characterization of the acute effect of physical activity on glucose profiles. With this aim, a systematic review of literature and metaanalyses are conduced to determine responses to various exercise modalities in patients with T1D, assessed via rates-of-change magnitudes to quantify temporal variations in glycaemia. On the other hand, a reliable identification of physical activity periods is an essential prerequisite to feed artificial pancreas systems with information concerning exercise in ambulatory, free-living conditions. For this reason, the second part of this thesis focuses on the proposal and evaluation of an automatic system devised to recognize physical activity, classifying its intensity level (light, moderate or vigorous) and for vigorous periods, identifying also its exercise modality (aerobic, mixed or resistance); since both aspects have a distinctive influence on the predominant metabolic pathway involved in fuelling exercise, and therefore, in the glycaemic responses in T1D. Various combinations of machine learning and pattern recognition techniques are applied on the fusion of multi-modal signal sources, namely: accelerometry and heart rate measurements, which describe both mechanical aspects of movement and the physiological response of the cardiovascular system to exercise. An additional temporal filtering module is incorporated after recognition in order to exploit the considerable temporal coherence (i.e. redundancy) present in data, which stems from the fact that in practice, physical activity trends are often maintained stable along time, instead of fluctuating rapid and repeatedly. The third block of this PhD thesis addresses meal intakes in the context of T1D. In particular, a number of compartmental models are proposed and compared in terms of their ability to describe mathematically the remote effect of exogenous plasma insulin concentrations on the disposal rates of meal-attributable glucose, an aspect which had not yet been incorporated to the prevailing T1D patient models in literature. Data were acquired in an experiment conduced at the Institute of Metabolic Science (University of Cambridge, UK) on 16 young patients. A variable-target glucose clamp replicated their individual glucose profiles, observed during a preliminary visit after ingesting either a high glycaemic-load or a low glycaemic-load evening meal. The six mechanistic models under evaluation here comprised: a) two-compartmental submodels for glucose tracer masses, b) a single-compartmental submodel for insulin’s remote effect, c) two types of activations for this remote effect (either linear or with a ‘cut-off’ point), and d) diverse forms of initial conditions.