790 resultados para Inertial Reels.
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Dry-wall laser inertial fusion (LIF) chambers will have to withstand strong bursts of fast charged particles which will deposit tens of kJ m−2 and implant more than 1018 particles m−2 in a few microseconds at a repetition rate of some Hz. Large chamber dimensions and resistant plasma-facing materials must be combined to guarantee the chamber performance as long as possible under the expected threats: heating, fatigue, cracking, formation of defects, retention of light species, swelling and erosion. Current and novel radiation resistant materials for the first wall need to be validated under realistic conditions. However, at present there is a lack of facilities which can reproduce such ion environments. This contribution proposes the use of ultra-intense lasers and high-intense pulsed ion beams (HIPIB) to recreate the plasma conditions in LIF reactors. By target normal sheath acceleration, ultra-intense lasers can generate very short and energetic ion pulses with a spectral distribution similar to that of the inertial fusion ion bursts, suitable to validate fusion materials and to investigate the barely known propagation of those bursts through background plasmas/gases present in the reactor chamber. HIPIB technologies, initially developed for inertial fusion driver systems, provide huge intensity pulses which meet the irradiation conditions expected in the first wall of LIF chambers and thus can be used for the validation of materials too.
The technofusion project for fusion technology development: opportunities for the inertial community
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The new Spanish installation for fusion research (Technofusion) has been approved by both the national and regional governments. Funding up to 80-100 M€ will be invested in the construction of seven laboratories to cover many aspects relevant to fusion technology development. This work discusses their utility for inertial fusion research.
The technofusion project for fusion technology development: opportunities for the inertial community
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Technofusion will be the new Spanish singular scientific-technical installation for fusion research. The research activities will be focused on seven areas of materials research considered the most relevant ones for further technological developments of fusion energy. In principle, most of the infrastructure in Technofusion will be useful for both, magnetic (MC) and inertial (IC) confinement fusion communities and most of the research and developments carried out for one of the fusion concepts will be valid and transferable to the other. However, some aspects related to first wall materials strongly differ in MC and IC approaches. This is due to the very different typical ion energy and deposited powers in both cases.
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Systems inertial confinement fusion (ICF) need of a manufacturing process targets very accurate and efficient (Fig. A). Due to the frequency needed for energy production techniques are necessary to achieve high repetition rates, however it is also necessary to increase or maintain the quality and efficiency of these targets. In order to observe more resolution possible problems in the target manufacture (B), we propose the following theoretical methodology, by means of which analyze different phenomena present in the conditions which are fabrication and handled deuterium tritium target spheres (DT ice). Recent experiments show that addition of instabilities caused by the geometry of the solid layer of DT ice (C), and the cover (ablator), one can relate the loss of power delivery in the implosion due to different conformations of the solid layers with regarding handling conditions.
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Final lenses in laser fusion plants. Challenges for the protection of the final lenses. Plasmonic nanoparticles. Radiation resistance
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The availability of inertial sensors embedded in mobile devices has enabled a new type of interaction based on the movements or “gestures” made by the users when holding the device. In this paper we propose a gesture recognition system for mobile devices based on accelerometer and gyroscope measurements. The system is capable of recognizing a set of predefined gestures in a user-independent way, without the need of a training phase. Furthermore, it was designed to be executed in real-time in resource-constrained devices, and therefore has a low computational complexity. The performance of the system is evaluated offline using a dataset of gestures, and also online, through some user tests with the system running in a smart phone.
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In the last years, there has been a continued growth in the number of offshore operations for handling large equipment and objects, with emphasis on installation and maintenance of devices for exploiting marine renewable energy like generators for harnessing wind, waves and currents energy. Considering the behaviour of these devices during manoeuvrings, and due to their size and by the interaction with the surrounding fluid, the effect of inertial forces and torques is very important, which requires a specific modelling. This paper especially discusses the masses and moments of inertia modelling problem, with the aim to use it in the simulation of the complex manoeuvres of these devices and in the automatic control systems designed for their offshore operations. Given the importance and complexity of the added mass modelling, a method for its early design identification, developed by the R&D Group on Marine Renewable Energy Technologies of the UPM (GITERM) and its use on special cases like emersion manoeuvres of devices from underwater to the surface will be presented.
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A sensitivity analysis has been performed to assess the influence of the inertial properties of railway vehicles on their dynamic behaviour. To do this, 216 dynamic simulations were performed modifying, one at a time, the masses, moments of inertia and heights of the centre of gravity of the carbody, the bogie and the wheelset. Three values were assigned to each parameter, corresponding to the percentiles 10, 50 and 90 of a data set stored in a database of railway vehicles. After processing the results of these simulations, the analyzed parameters were sorted by increasing influence. It was also found which of these parameters could be estimated with a lesser degree of accuracy for future simulations without appreciably affecting the simulation results. In general terms, it was concluded that the most sensitive inertial properties are the mass and the vertical moment of inertia, and the least sensitive ones the longitudinal and lateral moments of inertia.
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A numerical method providing the optimal laser intensity profiles for a direct-drive inertial confinement fusion scheme has been developed. The method provides an alternative approach to phase-space optimization studies, which can prove computationally expensive. The method applies to a generic irradiation configuration characterized by an arbitrary number NB of laser beams provided that they irradiate the whole target surface, and thus goes beyond previous analyses limited to symmetric configurations. The calculated laser intensity profiles optimize the illumination of a spherical target. This paper focuses on description of the method, which uses two steps: first, the target irradiation is calculated for initial trial laser intensities, and then in a second step the optimal laser intensities are obtained by correcting the trial intensities using the calculated illumination. A limited number of example applications to direct drive on the Laser MegaJoule (LMJ) are described.
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Human Activity Recognition (HAR) is an emerging research field with the aim to identify the actions carried out by a person given a set of observations and the surrounding environment. The wide growth in this research field inside the scientific community is mainly explained by the high number of applications that are arising in the last years. A great part of the most promising applications are related to the healthcare field, where it is possible to track the mobility of patients with motor dysfunction as also the physical activity in patients with cardiovascular risk. Until a few years ago, by using distinct kind of sensors, a patient follow-up was possible. However, far from being a long-term solution and with the smartphone irruption, that monitoring can be achieved in a non-invasive way by using the embedded smartphone’s sensors. For these reasons this Final Degree Project arises with the main target to evaluate new feature extraction techniques in order to carry out an activity and user recognition, and also an activity segmentation. The recognition is done thanks to the inertial signals integration obtained by two widespread sensors in the greater part of smartphones: accelerometer and gyroscope. In particular, six different activities are evaluated walking, walking-upstairs, walking-downstairs, sitting, standing and lying. Furthermore, a segmentation task is carried out taking into account the activities performed by thirty users. This can be done by using Hidden Markov Models and also a set of tools tested satisfactory in speech recognition: HTK (Hidden Markov Model Toolkit).
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El Reconocimiento de Actividades Humanas es un área de investigación emergente, cuyo objetivo principal es identificar las acciones realizadas por un sujeto analizando las señales obtenidas a partir de unos sensores. El rápido crecimiento de este área de investigación dentro de la comunidad científica se explica, en parte, por el elevado número de aplicaciones que están surgiendo en los últimos años. Gran parte de las aplicaciones más prometedoras se encuentran en el campo de la salud, donde se puede hacer un seguimiento del nivel de movilidad de pacientes con trastornos motores, así como monitorizar el nivel de actividad física en pacientes con riesgo cardiovascular. Hasta hace unos años, mediante el uso de distintos tipos de sensores se podía hacer un seguimiento del paciente. Sin embargo, lejos de ser una solución a largo plazo y gracias a la irrupción del teléfono inteligente, este seguimiento se puede hacer de una manera menos invasiva, haciendo uso de la gran variedad de sensores integrados en este tipo de dispositivos. En este contexto nace este Trabajo de Fin de Grado, cuyo principal objetivo es evaluar nuevas técnicas de extracción de características para llevar a cabo un reconocimiento de actividades y usuarios así como una segmentación de aquellas. Este reconocimiento se hace posible mediante la integración de señales inerciales obtenidas por dos sensores presentes en la gran mayoría de teléfonos inteligentes: acelerómetro y giróscopo. Concretamente, se evalúan seis tipos de actividades realizadas por treinta usuarios: andar, subir escaleras, bajar escaleras, estar sentado, estar de pie y estar tumbado. Además y de forma paralela, se realiza una segmentación temporal de los distintos tipos de actividades realizadas por dichos usuarios. Todo ello se llevará a cabo haciendo uso de los Modelos Ocultos de Markov, así como de un conjunto de herramientas probadas satisfactoriamente en reconocimiento del habla: HTK (Hidden Markov Model Toolkit).
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The small viscosity asymptotics of the inertial range of local structure and of the wall region in wallbounded turbulent shear flow are compared. The comparison leads to a sharpening of the dichotomy between Reynolds number dependent scaling (power-type) laws and the universal Reynolds number independent logarithmic law in wall turbulence. It further leads to a quantitative prediction of an essential difference between them, which is confirmed by the results of a recent experimental investigation. These results lend support to recent work on the zero viscosity limit of the inertial range in turbulence.
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Parkinson's disease (PD) is a neuro-degenerative disorder, the second most common after Alzheimer's disease. After diagnosis, treatments can help to relieve the symptoms, but there is no known cure for PD. PD is characterized by a combination of motor and no-motor dysfunctions. Among the motor symptoms there is the so called Freezing of Gait (FoG). The FoG is a phenomenon in PD patients in which the feet stock to the floor and is difficult for the patient to initiate movement. FoG is a severe problem, since it is associated with falls, anxiety, loss of mobility, accidents, mortality and it has substantial clinical and social consequences decreasing the quality of life in PD patients. Medicine can be very successful in controlling movements disorders and dealing with some of the PD symptoms. However, the relationship between medication and the development of FoG remains unclear. Several studies have demonstrated that visual or auditory rhythmical cuing allows PD patients to improve their motor abilities. Rhythmic auditory stimulation (RAS) was shown to be particularly effective at improving gait, specially with patients that manifest FoG. While RAS allows to reduce the time and the effects of FoGs occurrence in PD patients after the FoG is detected, it can not avoid the episode due to the latency of detection. An improvement of the system would be the prediction of the FoG. This thesis was developed following two main objectives: (1) the finding of specifics properties during pre FoG periods different from normal walking context and other walking events like turns and stops using the information provided by the inertial measurements units (IMUs) and (2) the formulation of a model for automatically detect the pre FoG patterns in order to completely avoid the upcoming freezing event in PD patients. The first part focuses on the analysis of different methods for feature extraction which might lead in the FoG occurrence.
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"Printed collections of ancient and modern Scottish melodies": p. xi-xvi.
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Publisher's plate no.: 15376-89.