9 resultados para Fusion process

em Universidad Politécnica de Madrid


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Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

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Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e.artifacts, in the resulting fusedimages. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values associated with single pixels. This effect increases as the spatial resolution image increases. To minimize this problem, we propose a new paradigm based on local measurements of the fractal dimension (FD). Fractal dimension maps (FDMs) are generated for each of the source images (panchromatic and each band of the multi-spectral images) with the box-counting algorithm and by applying a windowing process. The average of source image FDMs, previously indexed between 0 and 1, has been used for discrimination of different land covers present in satellite images. This paradigm has been applied through the fusion methodology based on the discrete wavelet transform (DWT), using the à trous algorithm (WAT). Two different scenes registered by optical sensors on board FORMOSAT-2 and IKONOS satellites were used to study the behaviour of the proposed methodology. The implementation of this approach, using the WAT method, allows adapting the fusion process to the roughness and shape of the regions present in the image to be fused. This improves the quality of the fusedimages and their classification results when compared with the original WAT method

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This work is motivated in providing and evaluating a fusion algorithm of remotely sensed images, i.e. the fusion of a high spatial resolution panchromatic image with a multi-spectral image (also known as pansharpening) using the dual-tree complex wavelet transform (DT-CWT), an effective approach for conducting an analytic and oversampled wavelet transform to reduce aliasing, and in turn reduce shift dependence of the wavelet transform. The proposed scheme includes the definition of a model to establish how information will be extracted from the PAN band and how that information will be injected into the MS bands with low spatial resolution. The approach was applied to Spot 5 images where there are bands falling outside PAN’s spectrum. We propose an optional step in the quality evaluation protocol, which is to study the quality of the merger by regions, where each region represents a specific feature of the image. The results show that DT-CWT based approach offers good spatial quality while retaining the spectral information of original images, case SPOT 5. The additional step facilitates the identification of the most affected regions by the fusion process.

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The aim of inertial confinement fusion is the production of energy by the fusion of thermonuclear fuel (deuterium-tritium) enclosed in a spherical target due to its implosion. In the direct-drive approach, the energy needed to spark fusion reactions is delivered by the irradiation of laser beams that leads to the ablation of the outer shell of the target (the so-called ablator). As a reaction to this ablation process, the target is accelerated inwards, and, provided that this implosion is sufficiently strong a symmetric, the requirements of temperature and pressure in the center of the target are achieved leading to the ignition of the target (fusion). One of the obstacles capable to prevent appropriate target implosions takes place in the ablation region where any perturbation can grow even causing the ablator shell break, due to the ablative Rayleigh-Taylor instability. The ablative Rayleigh-Taylor instability has been extensively studied throughout the last 40 years in the case where the density/temperature profiles in the ablation region present a single front (the ablation front). Single ablation fronts appear when the ablator material has a low atomic number (deuterium/tritium ice, plastic). In this case, the main mechanism of energy transport from the laser energy absorption region (low density plasma) to the ablation region is the electron thermal conduction. However, recently, the use of materials with a moderate atomic number (silica, doped plastic) as ablators, with the aim of reducing the target pre-heating caused by suprathermal electrons generated by the laser-plasma interaction, has demonstrated an ablation region composed of two ablation fronts. This fact appears due to increasing importance of radiative effects in the energy transport. The linear theory describing the Rayleigh-Taylor instability for single ablation fronts cannot be applied for the stability analysis of double ablation front structures. Therefore, the aim of this thesis is to develop, for the first time, a linear stability theory for this type of hydrodynamic structures.

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The elemental distribution for as-received (AR), H implanted (AI) and post-implanted annealed (A) Eurofer and ODS-Eurofer steels has been characterized by means of micro Particle Induced X-ray Emission (μ-PIXE), micro Elastic Recoil Detection (μ-ERD) and Secondary Ion Mass Spectrometry (SIMS). The temperature and time-induced H diffusion has been analyzed by Resonance Nuclear Reaction Analysis (RNRA), Thermal Desorption Spectroscopy (TDS), ERDA and SIMS techniques. μ-PIXE measurements point out the presence of inhomogeneities in the Y distribution for ODS-Eurofer samples. RNRA and SIMS experiments evidence that hydrogen easily outdiffuses in these steels even at room temperature. ERD data show that annealing at temperatures as low as 300 °C strongly accelerates the hydrogen diffusion process, driving out up to the 90% of the initial hydrogen.

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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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In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

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Nowadays, the projects LIFE (Laser Inertial Fusion Energy) in USA and HiPER (High Power Laser Energy Research) in Europe are the most advanced ones to demonstrate laser fusion energy viability. One of the main points of concern to properly achieve ignition is the performance of the final optics (lenses) under the severe irradiation conditions that take place in fusion facilities. In this paper, we calculate the radiation fluxes and doses as well as the radiation-induced temperature enhancement and colour centre formation in final lenses assuming realistic geometrical configurations for HiPER and LIFE. On these bases, the mechanical stresses generated by the established temperature gradients are evaluated showing that from a mechanical point of view lenses only fulfil specifications if ions resulting from the imploding target are mitigated. The absorption coefficient of the lenses is calculated during reactor startup and steady-state operation. The obtained results reveal the necessity of new solutions to tackle ignition problems during the startup process for HiPER. Finally, we evaluate the effect of temperature gradients on focal length changes and lens surface deformations. In summary, we discuss the capabilities and weak points of silica lenses and propose alternatives to overcome predictable problems

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The EFDA-ITER programme for materials wants to develop new structural materials for future nuclear magnetic fusion reactors. In this context, special attention must be paid in the development of new composite materials that could support the hard working conditions of the nuclear fusion reactors: high temperature, high stresses, and high radiation.