992 resultados para Lattice Boltzmann method


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Pós-graduação em Física - IFT

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Diese Arbeit legt eine neue Methode zur Simulation derDynamik vonPolymeren in verdünnter und halbverdünnterLösung vor. Die Effizienz der Methode und derAnstieg der Computerleistung in den letzten Jahren erlaubenes, weitaus komplexere Systeme als bisher zu betrachten.Die neue Methode modelliert die Polymere als Kugel-Feder-Ketten, die mittels Molekulardynamik simuliertwerden. Die Flüssigkeit wird durch die numerischeLösung der Kontinuitätsgleichungund der Navier-Stokes-Gleichung mit derLattice-Boltzmann-Methodemodelliert. Die Flüssigkeit wird über eineReibungskraft an die Monomere des Kugel-Feder-Modellsgekoppelt. Die Methode wird auf das Problem einer flexiblen EinzelketteimLösungsmittel angewendet. Der Vergleich derErgebnisse mit einer existierenden reinenMolekulardynamik-Simulationergibt Übereinstimmung innerhalb weniger Prozent,während die neueMethode um etwa einen Faktor 20 weniger CPU-Zeitbenötigt. Eine semiflexible Kette zeigt völliganderes Verhalten: Die Hydrodynamik spielt im Gegensatz zur flexiblen Ketteeineuntergeordnete Rolle. Simulationen von halbverdünntenLösungen flexibler Kettenbestehend aus insgesamt 50000 Monomeren zeigen zum erstenMal direkt dieAbschirmung sowohl der Volumenausschluss-Wechselwirkung alsauch derHydrodynamik.

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Questa tesi si focalizza sullo studio dei modelli fisico-matematici attualmente in uso per la simulazione di fluidi al calcolatore con l’obiettivo di fornire nozioni di base e avanzate sull’utilizzo di tali metodi. La trattazione ha lo scopo di facilitare la comprensione dei principi su cui si fonda la simulazione di fluidi e rappresenta una base per la creazione di un proprio simulatore. E’ possibile studiare le caratteristiche di un fluido in movimento mediante due approcci diversi, l’approccio lagrangiano e l’approccio euleriano. Mentre l’approccio lagrangiano ha lo scopo di conoscere il valore, nel tempo, di una qualsiasi proprietà di ciascuna particella che compone il fluido, l’approccio euleriano, fissato uno o più punti del volume di spazio occupato da quest’ultimo, vuole studiare quello che accade, nel tempo, in quei punti. In particolare, questa tesi approfondisce lo studio delle equazioni di Navier-Stokes, approcciandosi al problema in maniera euleriana. La soluzione numerica del sistema di equazioni differenziali alle derivate parziali derivante dalle equazioni sopracitate, approssima la velocità del fluido, a partire dalla quale è possibile risalire a tutte le grandezze che lo caratterizzano. Attenzione viene riservata anche ad un modello facente parte dell’approccio semi-lagrangiano, il Lattice Boltzmann, considerato una via di mezzo tra i metodi puramente euleriani e quelli lagrangiani, che si basa sulla soluzione dell’equazione di Boltzmann mediante modelli di collisione di particelle. Infine, analogamente al metodo di Lattice Boltzmann, viene trattato il metodo Smoothed Particles Hydrodynamics, tipicamente lagrangiano, secondo il quale solo le proprietà delle particelle comprese dentro il raggio di una funzione kernel, centrata nella particella di interesse, influenzano il valore della particella stessa. Un resoconto pratico della teoria trattata viene dato mediante delle simulazioni realizzate tramite il software Blender 2.76b.

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Amorphous carbon has been investigated for a long time. Since it has the random orientation of carbon atoms, its density depends on the position of each carbon atom. It is important to know the density of amorphous carbon to use it for modeling advance carbon materials in the future. Two methods were used to create the initial structures of amorphous carbon. One is the random placement method by randomly locating 100 carbon atoms in a cubic lattice. Another method is the liquid-quench method by using reactive force field (ReaxFF) to rapidly decrease the system of 100 carbon atoms from the melting temperature. Density functional theory (DFT) was used to refine the position of each carbon atom and the dimensions of the boundaries to minimize the ground energy of the structure. The average densities of amorphous carbon structures created by the random placement method and the liquid-quench method are 2.59 and 2.44 g/cm3, respectively. Both densities have a good agreement with previous works. In addition, the final structure of amorphous carbon generated by the liquid-quench method has lower energy.

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Soil voids manifest the cumulative effect of local pedogenic processes and ultimately influence soil behavior - especially as it pertains to aeration and hydrophysical properties. Because of the relatively weak attenuation of X-rays by air, compared with liquids or solids, non-disruptive CT scanning has become a very attractive tool for generating three-dimensional imagery of soil voids. One of the main steps involved in this analysis is the thresholding required to transform the original (greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice?Boltzmann models (Baveye et al., 2010). The objective of the current work is to apply an innovative approach to quantifying soil voids and pore networks in original X-ray CT imagery using Relative Entropy (Bird et al., 2006; Tarquis et al., 2008). These will be illustrated using typical imagery representing contrasting soil structures. Particular attention will be given to the need to consider the full 3D context of the CT imagery, as well as scaling issues, in the application and interpretation of this index.

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The process of liquid silicon infiltration is investigated for channels with radii from 0.25 to 0.75 [mm] drilled in compact carbon preforms. The advantage of this setup is that the study of the phenomenon results to be simplified. For comparison purposes, attempts are made in order to work out a framework for evaluating the accuracy of simulations. The approach relies on dimensionless numbers involving the properties of the surface reaction. It turns out that complex hydrodynamic behavior derived from second Newton law can be made consistent with Lattice-Boltzmann simulations. The experiments give clear evidence that the growth of silicon carbide proceeds in two different stages and basic mechanisms are highlighted. Lattice-Boltzmann simulations prove to be an effective tool for the description of the growing phase. Namely, essential experimental constraints can be implemented. As a result, the existing models are useful to gain more insight on the process of reactive infiltration into porous media in the first stage of penetration, i.e. up to pore closure because of surface growth. A way allowing to implement the resistance from chemical reaction in Darcy law is also proposed.

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A new numerical procedure is proposed to investigate cracking behaviors induced by mismatch between the matrix phase and aggregates due to matrix shrinkage in cement-based composites. This kind of failure processes is simplified in this investigation as a purely spontaneous mechanical problem, therefore, one main difficulty during simulating the phenomenon lies that no explicit external load serves as the drive to propel development of this physical process. As a result, it is different from classical mechanical problems and seems hard to be solved by using directly the classical finite element method (FEM), a typical kind of "load -> medium -> response" procedures. As a solution, the actual mismatch deformation field is decomposed into two virtual fields, both of which can be obtained by the classical FEM. Then the actual response is obtained by adding together the two virtual displacement fields based on the principle of superposition. Then, critical elements are detected successively by the event-by-event technique. The micro-structure of composites is implemented by employing the generalized beam (GB) lattice model. Numerical examples are given to show the effectiveness of the method, and detailed discussions are conducted on influences of material properties.

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An extended technique derived from triple-axis diffraction setup was proposed to measure lattice parameters of cubic GaN(c-GaN) films. The fully relaxed lattice parameters of c-GaN are determined to be 4.5036+0.0004 Angstrom, which is closer to the values of a hypothetical perfect crystal. The speculated zero setting correction (Deltatheta) is very slight and within the range of the accuracy of measurement. Additionally, we applied this method to analyze strain of four different kinds of c-GaN samples. It is found that in-plane strain caused by large lattice mismatch and thermal expansion coefficients mismatch directly influence the epilayer growth at high temperatures, indicating that the relaxation of tensile strain after thermal annealing helps to improve the crystalline quality of c-GaN films and optical properties. (C) 2003 Elsevier Science B.V. All rights reserved.

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The self-assembly of symmetric coil-rod-coil ABA-type triblock copolymer melts is studied by applying self-consistent field lattice techniques in a three-dimensional space. The self-assembled ordered structures differ significantly with the variation of the volume fraction of the rod component, which include lamellar, wave lamellar, gyroid, perforated lamellar, cylindrical, and spherical-like phases. To understand the physical essence of these phases and the regimes of occurrence, we construct the phase diagram, which matches qualitatively with the existing experimental results. Compared with the coil-rod AB diblock copolymer, our results revealed that the interfacial grafting density of the separating rod and coil segments shows important influence on the self-assembly behaviors of symmetric coil-rod-coil ABA triblock copolymer melts. We found that the order-disorder transition point changes from f(rod)=0.5 for AB diblock copolymers to f(rod)=0.6 for ABA triblock copolymers. Our results also show that the spherical-like and cylindrical phases occupy most of the region in the phase diagram, and the lamellar phase is found stable only at the high volume fraction of the rod.

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Molecular dynamics simulations are adopted to calculate the equation of state characteristic parameters P*, rho*, and T* of isotactic polypropylene (iPP) and poly(ethylene-co-octene) (PEOC), which can be further used in the Sanchez-Lacombe lattice fluid theory (SLLFT) to describe the respective physical properties. The calculated T* is a function of the temperature, which was also found in the literature. To solve this problem, we propose a Boltzmann fitting of the data and obtain T* at the high-temperature limit. With these characteristic parameters, the pressure-volume-temperature (PVT) data of iPP and PEOC are predicted by the SLLFT equation of state. To justify the correctness of our results, we also obtain the PVT data for iPP and PEOC by experiments. Good agreement is found between the two sets of data. By integrating the Euler-Lagrange equation and the Cahn-Hilliard relation, we predict the density profiles and the surface tensions for iPP and PEOC, respectively. Furthermore, a recursive method is proposed to obtain the characteristic interaction energy parameter between iPP and PEOC. This method, which does not require fitting to the experimental phase equilibrium data, suggests an alternative way to predict the phase diagrams that are not easily obtained in experiments.

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In this paper, based on the consideration of covalent behavior of adjacent ions in crystals, a calculation formula of lattice energy was proposed. In which, the concept of ionic effective valence and the empirical formula covalent energy were introduced,

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L’apprentissage supervisé de réseaux hiérarchiques à grande échelle connaît présentement un succès fulgurant. Malgré cette effervescence, l’apprentissage non-supervisé représente toujours, selon plusieurs chercheurs, un élément clé de l’Intelligence Artificielle, où les agents doivent apprendre à partir d’un nombre potentiellement limité de données. Cette thèse s’inscrit dans cette pensée et aborde divers sujets de recherche liés au problème d’estimation de densité par l’entremise des machines de Boltzmann (BM), modèles graphiques probabilistes au coeur de l’apprentissage profond. Nos contributions touchent les domaines de l’échantillonnage, l’estimation de fonctions de partition, l’optimisation ainsi que l’apprentissage de représentations invariantes. Cette thèse débute par l’exposition d’un nouvel algorithme d'échantillonnage adaptatif, qui ajuste (de fa ̧con automatique) la température des chaînes de Markov sous simulation, afin de maintenir une vitesse de convergence élevée tout au long de l’apprentissage. Lorsqu’utilisé dans le contexte de l’apprentissage par maximum de vraisemblance stochastique (SML), notre algorithme engendre une robustesse accrue face à la sélection du taux d’apprentissage, ainsi qu’une meilleure vitesse de convergence. Nos résultats sont présent ́es dans le domaine des BMs, mais la méthode est générale et applicable à l’apprentissage de tout modèle probabiliste exploitant l’échantillonnage par chaînes de Markov. Tandis que le gradient du maximum de vraisemblance peut-être approximé par échantillonnage, l’évaluation de la log-vraisemblance nécessite un estimé de la fonction de partition. Contrairement aux approches traditionnelles qui considèrent un modèle donné comme une boîte noire, nous proposons plutôt d’exploiter la dynamique de l’apprentissage en estimant les changements successifs de log-partition encourus à chaque mise à jour des paramètres. Le problème d’estimation est reformulé comme un problème d’inférence similaire au filtre de Kalman, mais sur un graphe bi-dimensionnel, où les dimensions correspondent aux axes du temps et au paramètre de température. Sur le thème de l’optimisation, nous présentons également un algorithme permettant d’appliquer, de manière efficace, le gradient naturel à des machines de Boltzmann comportant des milliers d’unités. Jusqu’à présent, son adoption était limitée par son haut coût computationel ainsi que sa demande en mémoire. Notre algorithme, Metric-Free Natural Gradient (MFNG), permet d’éviter le calcul explicite de la matrice d’information de Fisher (et son inverse) en exploitant un solveur linéaire combiné à un produit matrice-vecteur efficace. L’algorithme est prometteur: en terme du nombre d’évaluations de fonctions, MFNG converge plus rapidement que SML. Son implémentation demeure malheureusement inefficace en temps de calcul. Ces travaux explorent également les mécanismes sous-jacents à l’apprentissage de représentations invariantes. À cette fin, nous utilisons la famille de machines de Boltzmann restreintes “spike & slab” (ssRBM), que nous modifions afin de pouvoir modéliser des distributions binaires et parcimonieuses. Les variables latentes binaires de la ssRBM peuvent être rendues invariantes à un sous-espace vectoriel, en associant à chacune d’elles, un vecteur de variables latentes continues (dénommées “slabs”). Ceci se traduit par une invariance accrue au niveau de la représentation et un meilleur taux de classification lorsque peu de données étiquetées sont disponibles. Nous terminons cette thèse sur un sujet ambitieux: l’apprentissage de représentations pouvant séparer les facteurs de variations présents dans le signal d’entrée. Nous proposons une solution à base de ssRBM bilinéaire (avec deux groupes de facteurs latents) et formulons le problème comme l’un de “pooling” dans des sous-espaces vectoriels complémentaires.

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We discuss the generalized eigenvalue problem for computing energies and matrix elements in lattice gauge theory, including effective theories such as HQET. It is analyzed how the extracted effective energies and matrix elements converge when the time separations are made large. This suggests a particularly efficient application of the method for which we can prove that corrections vanish asymptotically as exp(-(E(N+1) - E(n))t). The gap E(N+1) - E(n) can be made large by increasing the number N of interpolating fields in the correlation matrix. We also show how excited state matrix elements can be extracted such that contaminations from all other states disappear exponentially in time. As a demonstration we present numerical results for the extraction of ground state and excited B-meson masses and decay constants in static approximation and to order 1/m(b) in HQET.

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The pulmonary crackling and the formation of liquid bridges are problems that for centuries have been attracting the attention of scientists. In order to study these phenomena, it was developed a canonical cubic lattice-gas­ like model to explain the rupture of liquid bridges in lung airways [A. Alencar et al., 2006, PRE]. Here, we further develop this model and add entropy analysis to study thermodynamic properties, such as free energy and force. The simulations were performed using the Monte Carlo method with Metropolis algorithm. The exchange between gas and liquid particles were performed randomly according to the Kawasaki dynamics and weighted by the Boltzmann factor. Each particle, which can be solid (s), liquid (l) or gas (g), has 26 neighbors: 6 + 12 + 8, with distances 1, √2 and √3, respectively. The energy of a lattice's site m is calculated by the following expression: Em = ∑k=126 Ji(m)j(k) in witch (i, j) = g, l or s. Specifically, it was studied the surface free energy of the liquid bridge, trapped between two planes, when its height is changed. For that, was considered two methods. First, just the internal energy was calculated. Then was considered the entropy. It was fond no difference in the surface free energy between this two methods. We calculate the liquid bridge force between the two planes using the numerical surface free energy. This force is strong for small height, and decreases as the distance between the two planes, height, is increased. The liquid-gas system was also characterized studying the variation of internal energy and heat capacity with the temperature. For that, was performed simulation with the same proportion of liquid and gas particle, but different lattice size. The scale of the liquid-gas system was also studied, for low temperature, using different values to the interaction Jij.