14 resultados para Topological defect

em Universidad Politécnica de Madrid


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The detailed study of the deterioration suffered by the materials of the components of a nuclear facility, in particular those forming part of the reactor core, is a topic of great interest which importance derives in large technological and economic implications. Since changes in the atomic-structural properties of relevant components pose a risk to the smooth operation with clear consequences for security and life of the plant, controlling these factors is essential in any development of engineering design and implementation. In recent times, tungsten has been proposed as a structural material based on its good resistance to radiation, but still needs to be done an extensive study on the influence of temperature on the behavior of this material under radiation damage. This work aims to contribute in this regard. Molecular Dynamics (MD) simulations were carried out to determine the influence of temperature fluctuations on radiation damage production and evolution in Tungsten. We have particularly focused our study in the dynamics of defect creation, recombination, and diffusion properties. PKA energies were sampled in a range from 5 to 50 KeV. Three different temperature scenarios were analyzed, from very low temperatures (0-200K), up to high temperature conditions (300-500 K). We studied the creation of defects, vacancies and interstitials, recombination rates, diffusion properties, cluster formation, their size and evolution. Simulations were performed using Lammps and the Zhou EAM potential for W

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The Fractal Image Informatics toolbox (Oleschko et al., 2008 a; Torres-Argüelles et al., 2010) was applied to extract, classify and model the topological structure and dynamics of surface roughness in two highly eroded catchments of Mexico. Both areas are affected by gully erosion (Sidorchuk, 2005) and characterized by avalanche-like matter transport. Five contrasting morphological patterns were distinguished across the slope of the bare eroded surface of Faeozem (Queretaro State) while only one (apparently independent on the slope) roughness pattern was documented for Andosol (Michoacan State). We called these patterns ?the roughness clusters? and compared them in terms of metrizability, continuity, compactness, topological connectedness (global and local) and invariance, separability, and degree of ramification (Weyl, 1937). All mentioned topological measurands were correlated with the variance, skewness and kurtosis of the gray-level distribution of digital images. The morphology0 spatial dynamics of roughness clusters was measured and mapped with high precision in terms of fractal descriptors. The Hurst exponent was especially suitable to distinguish between the structure of ?turtle shell? and ?ramification? patterns (sediment producing zone A of the slope); as well as ?honeycomb? (sediment transport zone B) and ?dinosaur steps? and ?corals? (sediment deposition zone C) roughness clusters. Some other structural attributes of studied patterns were also statistically different and correlated with the variance, skewness and kurtosis of gray distribution of multiscale digital images. The scale invariance of classified roughness patterns was documented inside the range of five image resolutions. We conjectured that the geometrization of erosion patterns in terms of roughness clustering might benefit the most semi-quantitative models developed for erosion and sediment yield assessments (de Vente and Poesen, 2005).

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We present a technique to reconstruct the electromagnetic properties of a medium or a set of objects buried inside it from boundary measurements when applying electric currents through a set of electrodes. The electromagnetic parameters may be recovered by means of a gradient method without a priori information on the background. The shape, location and size of objects, when present, are determined by a topological derivative-based iterative procedure. The combination of both strategies allows improved reconstructions of the objects and their properties, assuming a known background.

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Most empirical disciplines promote the reuse and sharing of datasets, as it leads to greater possibility of replication. While this is increasingly the case in Empirical Software Engineering, some of the most popular bug-fix datasets are now known to be biased. This raises two significants concerns: first, that sample bias may lead to underperforming prediction models, and second, that the external validity of the studies based on biased datasets may be suspect. This issue has raised considerable consternation in the ESE literature in recent years. However, there is a confounding factor of these datasets that has not been examined carefully: size. Biased datasets are sampling only some of the data that could be sampled, and doing so in a biased fashion; but biased samples could be smaller, or larger. Smaller data sets in general provide less reliable bases for estimating models, and thus could lead to inferior model performance. In this setting, we ask the question, what affects performance more? bias, or size? We conduct a detailed, large-scale meta-analysis, using simulated datasets sampled with bias from a high-quality dataset which is relatively free of bias. Our results suggest that size always matters just as much bias direction, and in fact much more than bias direction when considering information-retrieval measures such as AUC and F-score. This indicates that at least for prediction models, even when dealing with sampling bias, simply finding larger samples can sometimes be sufficient. Our analysis also exposes the complexity of the bias issue, and raises further issues to be explored in the future.

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This work implements an optimization of the phosphorus gettering effect during the contact co-firing step by means of both simulations and experiments in an industrial belt furnace. An optimized temperature profile, named ‘extended co-firing step’, is presented. Simulations show that the effect of the short annealing on the final interstitial iron concentration depends strongly on the initial contamination level of the material and that the ‘extended co-firing’ temperature profile can enhance the gettering effect within a small additional time. Experimental results using sister wafers from the same multicrystalline silicon ingot confirm these trends and show the potential of this new defect engineering tool to improve the solar cell efficiency.

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We introduce an easily computable topological measure which locates the effective crossover between segregation and integration in a modular network. Segregation corresponds to the degree of network modularity, while integration is expressed in terms of the algebraic connectivity of an associated hypergraph. The rigorous treatment of the simplified case of cliques of equal size that are gradually rewired until they become completely merged, allows us to show that this topological crossover can be made to coincide with a dynamical crossover from cluster to global synchronization of a system of coupled phase oscillators. The dynamical crossover is signaled by a peak in the product of the measures of intracluster and global synchronization, which we propose as a dynamical measure of complexity. This quantity is much easier to compute than the entropy (of the average frequencies of the oscillators), and displays a behavior which closely mimics that of the dynamical complexity index based on the latter. The proposed topological measure simultaneously provides information on the dynamical behavior, sheds light on the interplay between modularity and total integration, and shows how this affects the capability of the network to perform both local and distributed dynamical tasks.

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Algebraic topology (homology) is used to analyze the state of spiral defect chaos in both laboratory experiments and numerical simulations of Rayleigh-Bénard convection. The analysis reveals topological asymmetries that arise when non-Boussinesq effects are present. The asymmetries are found in different flow fields in the simulations and are robust to substantial alterations to flow visualization conditions in the experiment. However, the asymmetries are not observable using conventional statistical measures. These results suggest homology may provide a new and general approach for connecting spatiotemporal observations of chaotic or turbulent patterns to theoretical models.

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We study the stability and dynamics of non-Boussinesq convection in pure gases ?CO2 and SF6? with Prandtl numbers near Pr? 1 and in a H2-Xe mixture with Pr= 0.17. Focusing on the strongly nonlinear regime we employ Galerkin stability analyses and direct numerical simulations of the Navier-Stokes equations. For Pr ? 1 and intermediate non-Boussinesq effects we find reentrance of stable hexagons as the Rayleigh number is increased. For stronger non-Boussinesq effects the usual, transverse side-band instability is superseded by a longitudinal side-band instability. Moreover, the hexagons do not exhibit any amplitude instability to rolls. Seemingly, this result contradicts the experimentally observed transition from hexagons to rolls. We resolve this discrepancy by including the effect of the lateral walls. Non-Boussinesq effects modify the spiral defect chaos observed for larger Rayleigh numbers. For convection in SF6 we find that non-Boussinesq effects strongly increase the number of small, compact convection cells and with it enhance the cellular character of the patterns. In H2-Xe, closer to threshold, we find instead an enhanced tendency toward roll-like structures. In both cases the number of spirals and of targetlike components is reduced. We quantify these effects using recently developed diagnostics of the geometric properties of the patterns.

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Motivated by the observation of spiral patterns in a wide range of physical, chemical, and biological systems, we present an automated approach that aims at characterizing quantitatively spiral-like elements in complex stripelike patterns. The approach provides the location of the spiral tip and the size of the spiral arms in terms of their arc length and their winding number. In addition, it yields the number of pattern components (Betti number of order 1), as well as their size and certain aspects of their shape. We apply the method to spiral defect chaos in thermally driven Rayleigh- Bénard convection and find that the arc length of spirals decreases monotonically with decreasing Prandtl number of the fluid and increasing heating. By contrast, the winding number of the spirals is nonmonotonic in the heating. The distribution function for the number of spirals is significantly narrower than a Poisson distribution. The distribution function for the winding number shows approximately an exponential decay. It depends only weakly on the heating, but strongly on the Prandtl number. Large spirals arise only for larger Prandtl numbers. In this regime the joint distribution for the spiral length and the winding number exhibits a three-peak structure, indicating the dominance of Archimedean spirals of opposite sign and relatively straight sections. For small Prandtl numbers the distribution function reveals a large number of small compact pattern components.

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We employ numerical computations of the full Navier-Stokes equations to investigate non-Boussinesq convection in a rotating system using water as the working fluid. We identify two regimes. For weak non- Boussinesq effects the Hopf bifurcation from steady to oscillating (whirling) hexagons is supercritical and typical states exhibit defect chaos that is systematically described by the cubic complex Ginzburg-Landau equation. For stronger non-Boussinesq effects the Hopf bifurcation becomes subcritical and the oscil- lations exhibit localized chaotic bursting, which is modeled by a quintic complex Ginzburg-Landau equation.

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In this work, we introduce the Object Kinetic Monte Carlo (OKMC) simulator MMonCa and simulate the defect evolution in three different materials. We start by explaining the theory of OKMC and showing some details of how such theory is implemented by creating generic structures and algorithms in the objects that we want to simulate. Then we successfully reproduce simulated results for defect evolution in iron, silicon and tungsten using our simulator and compare with available experimental data and similar simulations. The comparisons validate MMonCa showing that it is powerful and flexible enough to be customized and used to study the damage evolution of defects in a wide range of solid materials.

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The era of the seed-cast grown monocrystalline-based silicon ingots is coming. Mono-like, pseudomono or quasimono wafers are product labels that can be nowadays found in the market, as a critical innovation for the photovoltaic industry. They integrate some of the most favorable features of the conventional silicon substrates for solar cells, so far, such as the high solar cell efficiency offered by the monocrystalline Czochralski-Si (Cz-Si) wafers and the lower cost, high productivity and full square-shape that characterize the well-known multicrystalline casting growth method. Nevertheless, this innovative crystal growth approach still faces a number of mass scale problems that need to be resolved, in order to gain a deep, 100% reliable and worldwide market: (i) extended defects formation during the growth process; (ii) optimization of the seed recycling; and (iii) parts of the ingots giving low solar cells performance, which directly affect the production costs and yield of this approach. Therefore, this paper presents a series of casting crystal growth experiments and characterization studies from ingots, wafers and cells manufactured in an industrial approach, showing the main sources of crystal defect formation, impurity enrichment and potential consequences at solar cell level. The previously mentioned technological drawbacks are directly addressed, proposing industrial actions to pave the way of this new wafer technology to high efficiency solar cells.

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Safety is one of the most important feature in the aviation industry, and this involves too many factors. One of these is the aircraft maintenance. Over time, the procedures have been changing, and improving themselves. Non Destructive Testing (NDT) appeared in the late 19th century as a great option, because it enabled to inspect any structure without damaging it. Nowadays, there are several kinds of NDT, but ultrasound is one of the most widely used. This Master Thesis is devoted to an innovative ultrasound technique for crack detection. A technique, whose main aim lies in getting a good location of defects from a few measures, breaking with the currently widespread methods, as phased array. It is not necessary to use trains of waves, only discrete excitations, which means a great saving of time and energy. This work is divided into two steps: the first is to develop a multiphysics simulator, which is able to solve linear elasticity 3D problems (via Finite Element Method, FEM). This simulator allows to obtain in a computationally efficient way the displacement field for different frequencies and excitations. The solution of this elastic problem is needed to be used in the second step, which consists of generating a code that implements a mathematical tool named topological derivative, allowing to locate defects in the studied domain. In this work, the domain is a plate, and the defect is a hidden spherical void. The simulator has been developed using open source software (Elmer, Gmsh, ...), achieving a highly versatile simulator, which allows to change the configuration easily: domain size and shape, number and position of transducers, etc. Just one comercial software is used, Matlab. It is used to implement the topological derivative. In this work, the performance of the method is tested in several examples comparing the results when one or more frequencies are considered for different configurations of emisors/receptors.

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The determination of the local Lagrangian evolution of the flow topology in wall-bounded turbulence, and of the Lagrangian evolution associated with entrainment across the turbulent / non-turbulent interface into a turbulent boundary layer, require accurate tracking of a fluid particle and its local velocity gradients. This paper addresses the implementation of fluid-particle tracking in both a turbulent boundary layer direct numerical simulation and in a fully developed channel flow simulation. Determination of the sub-grid particle velocity is performed using both cubic B-spline, four-point Hermite spline and higher-order Hermite spline interpolation. Both wall-bounded flows show similar oscillations in the Lagrangian tracers of both velocity and velocity gradients, corresponding to the movement of particles across the boundaries of computational cells. While these oscillation in the particle velocity are relatively small and have negligible effect on the particle trajectories for time-steps of the order of CFL = 0.1, they appear to be the cause of significant oscillations in the evolution of the invariants of the velocity gradient tensor.