Plasma-assisted processing and deposition of materials is an important component of modern industrial applications, with plasma reactors sharing 30% to 40% of manufacturing steps in microelectronics production [1]. Development of new flexible electronics increases demands for efficient high-throughput deposition methods and roll-to-roll processing of materials. The current work represents an attempt of practical design and numerical modeling of a plasma enhanced chemical vapor deposition system. The system utilizes plasma at standard pressure and temperature to activate a chemical precursor for protective coatings. A specially designed linear plasma head, that consists of two parallel plates with electrodes placed in the parallel arrangement, is used to resolve clogging issues of currently available commercial plasma heads, as well as to increase the flow-rate of the processed chemicals and to enhance the uniformity of the deposition. A test system is build and discussed in this work. In order to improve operating conditions of the setup and quality of the deposited material, we perform numerical modeling of the plasma system. The theoretical and numerical models presented in this work comprehensively describe plasma generation, recombination, and advection in a channel of arbitrary geometry. Number density of plasma species, their energy content, electric field, and rate parameters are accurately calculated and analyzed in this work. Some interesting engineering outcomes are discussed with a connection to the proposed setup. The numerical model is implemented with the help of high-performance parallel technique and evaluated at a cluster for parallel calculations. A typical performance increase, calculation speed-up, parallel fraction of the code and overall efficiency of the parallel implementation are discussed in details.

In this thesis we study efficient parallel iterative solution algorithms for multi-physics problems. In particular, we consider fluid structure interaction (FSI) problems, a type of multi-physics problem in which a fluid and a deformable solid interact. All computations were performed in Oomph-Lib, a finite element library for the simulation of multi-physics problems. In Oomph-Lib, the constituent problems in a multi-physics problem are coupled monolithically, and the resulting system of non-linear equations solved with Newton's method. This requires the solution of sequences of large, sparse linear systems, for which optimal solvers are essential. The linear systems arising from the monolithic discretisation of multi-physics problems are natural candidates for solution with block-preconditioned Krylov subspace methods.We developed a generic framework for the implementation of block preconditioners within Oomph-Lib. Furthermore the framework is parallelised to facilitate the efficient solution of very large problems. This framework enables the reuse of all of Oomph-Lib's existing linear algebra infrastructure and preconditioners (including block preconditioners). We will demonstrate that a wide range of block preconditioners can be seamlessly implemented in this framework, leading to optimal iterative solvers with good parallel scaling.We concentrate on the development of an effective preconditioner for a FSI problem formulated in an arbitrary Lagrangian Eulerian (ALE) framework with pseudo-solid node updates (for the deforming fluid mesh). We begin by considering the pseudo-solid subsidiary problem; the deformation of a solid governed by equations of large displacement elasticity, subject to a prescribed boundary displacement imposed with Lagrange multiplier. We present a robust, optimal, augmented-Lagrangian type preconditioner for the resulting saddle-point linear system and prove analytically tight bounds for the spectrum of the preconditioned operator with respect to the discrete problem size.This pseudo-solid preconditioner is incorporated into a block preconditioner for the full FSI problem. One key feature of the FSI preconditioner is that existing optimal single physics preconditioners (such as the well known Navier-Stokes Least Squares Commutator preconditioner) can be employed to approximately solve the linear systems associated with the constituent sub-problems. We evaluate its performance on selected 2D and 3D problems. The preconditioner is optimal for most problems considered. In cases when sub-optimality is detected, we explain the reasons for such behavior and suggest potential improvements.

Les dépendances fonctionnelles fournissent une information sémantique sur les données d’une table en mettant en lumière les liens de corrélation qui les unient. Dans cette thèse, nous traitons du problème de l’extraction de ces dépendances en proposant un contexte unifié permettant la découverte de n’importe quel type de dépendances fonctionnelles (dépendances de clé, dépendances fonctionnelles conditionnelles, que la validité soit complète ou approximative). Notre algorithme, ParaCoDe, s’exécute en parallèle sur les candidats, réduisant ainsi le temps global de calcul. De ce fait, il est très compétitif vis-à-vis des approches séquentielles connues à ce jour. Les dépendances satisfaites sur une table nous servent à résoudre le problème de la matérialisation partielle du cube de données. Nous présentons une caractérisation de la solution optimale dans laquelle le coût de chaque requête est borné par un seuil de performance fixé préalablement et dont la taille est minimale. Cette spécification de la solution donne un cadre unique pour décrire et donc comparer formellement les techniques de résumé de cubes de données. / Functional dependancies provide a semantic information over data from a table to exhibit correlation links. In this thesis, we deal with the dependancy discovery problem by proposing a unified context to extract any type of functional dependencies (key dependencies, conditional functional dependencies, with an exact or an approximate validity). Our algorithm, ParaCoDe, runs in parallel on candidates there by reducing the global time of computations. Hence, it is very competitive comparated to sequential appoaches known today. Satisfied dependencies on a table are used to solve the problem of partial materiali-zation of data cube. We present a characterization of the optimal solution in which the cost of each query is bounded by a before hand fixed performance threshold and its size is minimal. This specification of the solution gives a unique framework to describe and formally compare summarization techniques of data cubes.

Aerodynamic shape optimization and multidisciplinary optimization algorithms have the potential not only to improve conventional aircraft, but also to enable the design of novel configurations. By their very nature, these algorithms generate and analyze a large number of unique shapes, resulting in high computational costs. In order to improve their efficiency and enable their use in the early stages of the design process, a fast and robust flow solution algorithm is necessary. This thesis presents an efficient parallel Newton-Krylov-Schur flow solution algorithm for the three-dimensional Navier-Stokes equations coupled with the Spalart-Allmaras one-equation turbulence model. The algorithm employs second-order summation-by-parts (SBP) operators on multi-block structured grids with simultaneous approximation terms (SATs) to enforce block interface coupling and boundary conditions. The discrete equations are solved iteratively with an inexact-Newton method, while the linear system at each Newton iteration is solved using the flexible Krylov subspace iterative method GMRES with an approximate-Schur parallel preconditioner. The algorithm is thoroughly verified and validated, highlighting the correspondence of the current algorithm with several established flow solvers. The solution for a transonic flow over a wing on a mesh of medium density (15 million nodes) shows good agreement with experimental results. Using 128 processors, deep convergence is obtained in under 90 minutes. The solution of transonic flow over the Common Research Model wing-body geometry with grids with up to 150 million nodes exhibits the expected grid convergence behavior. This case was completed as part of the Fifth AIAA Drag Prediction Workshop, with the algorithm producing solutions that compare favourably with several widely used flow solvers. The algorithm is shown to scale well on over 6000 processors. The results demonstrate the effectiveness of the SBP-SAT spatial discretization, which can be readily extended to high order, in combination with the Newton-Krylov-Schur iterative method to produce a powerful parallel algorithm for the numerical solution of the Reynolds-averaged Navier-Stokes equations. The algorithm can efficiently solve the flow over a range of clean geometries, making it suitable for use at the core of an optimization algorithm.

Aerodynamic shape optimization and multidisciplinary optimization algorithms have the potential not only to improve conventional aircraft, but also to enable the design of novel configurations. By their very nature, these algorithms generate and analyze a large number of unique shapes, resulting in high computational costs. In order to improve their efficiency and enable their use in the early stages of the design process, a fast and robust flow solution algorithm is necessary. This thesis presents an efficient parallel Newton-Krylov-Schur flow solution algorithm for the three-dimensional Navier-Stokes equations coupled with the Spalart-Allmaras one-equation turbulence model. The algorithm employs second-order summation-by-parts (SBP) operators on multi-block structured grids with simultaneous approximation terms (SATs) to enforce block interface coupling and boundary conditions. The discrete equations are solved iteratively with an inexact-Newton method, while the linear system at each Newton iteration is solved using the flexible Krylov subspace iterative method GMRES with an approximate-Schur parallel preconditioner. The algorithm is thoroughly verified and validated, highlighting the correspondence of the current algorithm with several established flow solvers. The solution for a transonic flow over a wing on a mesh of medium density (15 million nodes) shows good agreement with experimental results. Using 128 processors, deep convergence is obtained in under 90 minutes. The solution of transonic flow over the Common Research Model wing-body geometry with grids with up to 150 million nodes exhibits the expected grid convergence behavior. This case was completed as part of the Fifth AIAA Drag Prediction Workshop, with the algorithm producing solutions that compare favourably with several widely used flow solvers. The algorithm is shown to scale well on over 6000 processors. The results demonstrate the effectiveness of the SBP-SAT spatial discretization, which can be readily extended to high order, in combination with the Newton-Krylov-Schur iterative method to produce a powerful parallel algorithm for the numerical solution of the Reynolds-averaged Navier-Stokes equations. The algorithm can efficiently solve the flow over a range of clean geometries, making it suitable for use at the core of an optimization algorithm.

Polymers is a class of molecules which can have many different structures due to a large number of degrees of freedom. Many biopolymers, e.g. DNA, but also synthetic macromolecules have special structural features due to their backbone stiffness. Since such structural properties are important for e.g. the biological function, a lot of effort has been put into the investigation of the configurational properties of semi-stiff molecules. A theoretical treatment of these systems is often accompanied by computer simulations. The main idea is to compare theoretically derived models with experimental results for real polymers. Using Monte Carlo simulations, I have investigated how this computational technique can build a bridge between theoretical models and experimentally observed phenomena. The effort was mainly directed to develop sampling techniques, for efficiently exploring the configurational space of semi-stiff chains in a wide range of structures. The work was concentrated on compact conformations, since they, as is well known from previous studies, are difficult to sample using conventional methods. In my studies I have shown that the simple and, at a first glance, time consuming method of bead-by-bead regrow as a way of changing the configuration of a semi-stiff chain gave very promising and encouraging results when combined with modern simulation techniques, like Entropic Sampling with the Wang-Landau algorithm. The resulting simulation package was also suitable for parallelization which resulted in a further speed-up of the calculations. In addition to the more elaborate sampling methods, I also investigated external conditions to induce compaction of a semi-stiff polymer. In the case of a polyampholyte the condensing agent could be a multivalent salt, creating effective attraction between the loops of the chain, while for neutral polymers, an external field and the geometry of the confining volume can induce a compaction.

Šifrování multimediálních datových přenosů v reálném čase je jednou z úloh telekomunikační infrastruktury pro dosažení nezbytné úrovně zabezpečení. Rychlost provedení šifrovacího algoritmu může hrát klíčovou roli ve velikosti zpoždění jednotlivých paketů a proto je tento úkol zajímavým z hlediska optimalizačních metod. Tato práce se zaměřuje na možnosti paralelizace zpracování SRTP pro účely telefonní ústředny s využitím OpenCL frameworku a následnou analýzu potenciálního zlepšení.

De nombreuses applications industrielles mettent en jeu des écoulements gaz-particules, comme les turbines aéronautiques et les réacteurs a lit fluidisé de l'industrie chimique. La prédiction des propriétés de la phase dispersée, est essentielle à l'amélioration et la conception des dispositifs conformément aux nouvelles normes européennes des émissions polluantes. L'objectif de cette these est de développer le formalisme Euler- Lagrange dans un solveur parallèle et non-structuré pour la simulation aux grandes échelles pour ce type d'écoulements. Ce travail est motivé par l'augmentation rapide de la puissance de calcul des machines massivement parallèles qui ouvre une nouvelle voie pour des simulations qui étaient prohibitives il y a une décennie. Une attention particulière a été portée aux structures de données afin de conserver une certaine simplicité et la portabilité du code sur des differentes! architectures. Les développements sont validés pour deux configurations : un cas académique de turbulence homogène isotrope décroissante et un calcul polydisperse d'un jet turbulent recirculant chargé en particules. L'équilibrage de charges de particules est mis en évidence comme une solution prometteuse pour les simulations diphasiques Lagrangiennes afin d'améliorer les performances des calculs lorsque le déséquilibrage est trop important. / Particle-laden flows occur in industrial applications ranging from droplets in gas turbines tofluidized bed in chemical industry. Prediction of the dispersed phase properties such as concentration and dynamics are crucial for the design of more efficient devices that meet the new pollutant regulations of the European community. The objective of this thesis is to develop an Euler-Lagrange formulation on a parallel and unstructured solver for large- eddy simulation. This work is motivated by the rapid increase in computing power which opens a new way for simulations that were prohibitive one decade ago. Special attention is taken to keep data structure simplicity and code portability. Developments are validated in two configurations : an academic test of a decaying homogeneous isotropic turbulence and a polydisperse two-phase flow of a confined bluff body. The use of load-balancing capabilities is highlighted as a promising solut! ion in Lagrangian two-phase flow simulations to improve performance when strong imbalance of the dispersed phase is present

An analysis using numerical methods can calculate electrical and construction characteristics parameters of microwave devices quite accurately. However, numerical methods require a lot of computation resources and time for calculations to be made. Rapid perfection of the computer technologies and software with implementation of the numerical methods has laid down the conditions to the rapid design of the microwave devices using computers. / Disertacijoje nagrinėjamos mikrobangų įtaisų analizės ir sintezės proble-mos, taikant lygiagrečiąsias kompiuterines sistemas. Pagrindiniai tyrimo objektai yra daugialaidės mikrojuostelinės linijos ir meandrinės mikrojuostelinės vėlinimo linijos. Šie objektai leidžia perduoti, sinchronizuoti bei vėlinti siunčiamus signalus ir yra neatsiejama dalis daugelio mikrobangų prietaisų. Jų operatyvi ir tiksli analizė bei sintezė sąlygoja įtaisų kūrimo spartinimą. Pagrindinis disertacijos tikslas – sukurti lygiagrečiąsias metodikas ir algoritmus, skirtus sparčiai ir tiksliai atlikti minėtų linijų analizę ir sintezę. Sukurtų algoritmų ir metodikų taikymo sritis – mikrobangų įtaisų modeliavimo ir automatizuoto projektavimo progra-minė įranga.

Работа содержит описание построения доверительной полосы стохастического хаоса и реализацию алгоритмов исследования n-мерных моделей. В работе рассматривается дискретная модель, представленная в виде нелинейной динамической системы разностных уравнений, которая описывает динамику взаимодействия потребителей. Выделяются две задачи, которые были поставлены и выполнены в рамках данной работы для расширения программного инструментария исследования динамических систем такого рода. Для двумерного случая осуществляется стохастический анализ чувствительности хаоса через построение доверительной области с использованием критических линий. Помимо этого, описывается разработанный и реализованный алгоритм построения внешней границы хаоса. Производится переход к n-мерному варианту модели (взаимодействие n потребителей). Выделяется 4 алгоритма для исследования n-мерной модели: 1. построение фазовой траектории, 2. построение бифуркационной диаграммы, 3. построение карты режимов, 4. построение показателей Ляпунова. Описывается реализация данных алгоритмов с уклоном в параллельные вычисления. Реализация алгоритмов выполнена на языке программирования C# (платформа .NET) в виде консольного приложения для запуска параллельных вычислений на вычислительном кластере УрФУ. / The work contains description of confidence band construction of a stochastic chaos and realization of algorithms for n-dimensional models studying. The thesis considers a discrete model presented in the form of a nonlinear dynamic system of difference equations, which describes the dynamic of consumer interaction. There are two task that were set and performed in this work to expand the software tools for research dynamic sys-tems of this kind. For the two-dimensional case, a stochastic analysis of the sensitivity of chaos is carried out through the construction of a confidence band using critical lines. In addition, there is description and implementation of algorithm, that can build outer boundary of chaos. A transition is made to the n-dimensional version of the model (interaction of n consumers). There are 4 algorithms for studying the n-dimensional model: 1. phase trajectory building, 2. bifurcation diagram building, 3. mode map building, 4. Lyapunov components building. Algorithm implementation is described with a bias in parallel computations. The algorithms are implemented with C# programming language (.NET platform) in the form of a console application for running parallel computations on the computing cluster of the Ural Federal University.