It has been shown in many studies that turbulent flows are highly dependent on their initial conditions. This thesis explores turbulent flow using direct numerical simulation (DNS) in a variety of situations, and culminates in the development of physically realizable initial conditions. The reaction of isotropic homogeneous turbulent flow to the instantaneous insertion of a wall is investigated using two-point correlations. A model with which to predict the behavior of the two-point correlations is also proposed. The proposed model utilizes a reflection technique that with a linear operation, it accurately predicts the behavior of the non-linear two point correlations. The model works exceedingly well for correlations involving wall-perpendicular velocities, but does not predict correlations involving only wall-parallel velocities as well. A vorticity approach is covered, in an effort to highlight which parts of the correlation decomposition are important to the prediction of the correlations after wall imposition. The vorticity study also helps highlight why the proposed linear model predicts the flow. The impact of the initial conditions on axisymmetric contraction flow of turbulent flow is examined, and as a consequence new initial conditions are developed based off of a physically realizable flow condition. The development of the new-initial conditions and the resulting fields are covered, as well as a study on the value of the turbulent decay exponent associated with decay of isotropic turbulent velocity fields.

Dans un contexte de globalisation des marchés, les partenariats inter-firmes et les joint ventures internationales (JVI) se sont considérablement développés à l’échelle mondiale. La littérature montre qu’en dépit des nombreux avantages offerts aux entreprises, ces stratégies demeurent risquées avec un niveau de performance hétérogène. Dans le cadre de cette recherche doctorale, nous proposons d’étudier l’impact des conditions initiales sur la longévité et les modalités de sortie des joint ventures implantées dans les pays de la Méditerranée. Dans cet objectif, nous avons retenu une perspective holistique en mobilisant trois ensembles de variables : l’environnement de la structure commune, les caractéristiques des partenaires et celles de la joint venture. Ces conditions initiales, prises en compte au moment de la formation de la relation, sont considérées comme des éléments « déstabilisateurs » influençant la durée de la relation partenariale. Afin de déterminer l’influence de ces variables, nous avons construit une base de données, à partir de la presse économique. L’échantillon est constitué de 124 JVI implantées dans huit pays de la région méditerranéenne et créées entre 1996 et 2003. Les analyses statistiques de survie nous ont permis de montrer que le type des JVI (JVI créées par des investissements greenfield ou par acquisition) et le degré de similarité des activités entre le partenaire étranger et la JVI exercent une influence significative sur la longévité. / Inter-firm partnerships and international joint ventures (IJV) have developed significantly at the global scale. Previous studies show that, despite their benefits, these strategies remain risky, with a heterogeneous level of performance. In this doctoral dissertation, we aim to analyze the impact of initial conditions on longevity and exit modes of joint ventures established in Mediterranean countries. For this purpose, we have chosen a holistic approach by using three sets of variables: the environment of the common structure, the characteristics of the partner companies and the characteristics of the joint venture. Such initial conditions, under which IJVs are formed, are considered as "destabilizing" factors influencing the duration of the partnership. In order to determine the influence of these variables, we created a database, relying on the international business press. The sample includes 124 IJVs which were formed between 1996 and 2003 and implemented in eight countries of the Mediterranean region. Survival analysis shows that the type of IJV (created by greenfield investments or by acquisition) and the industry relatedness of an IJV to its foreign parent have a significant influence on longevity.

An experimental study of the effect of initial conditions on the development of Rayleigh Taylor Instabilities (RTI) at low Atwood numbers (order of 10-4) was performed in the water channel facility at TAMU. Initial conditions of the flow were generated using a controllable, highly reliable Servo motor. The uniqueness of the study is the system’s capability of generating the required initial conditions precisely as compared to the previous endeavors. Backlit photography was used for imaging and ensemble averaging of the images was performed to study mixing width characteristics in different regimes of evolution of Rayleigh-Taylor Instability (RTI). High-speed imaging of the flows was performed to provide insights into the growth of bubble and spikes in the linear and non-linear regime of instability development. RTI are observed in astrophysics, geophysics and in many instances in nature. The vital role of RTI in the feasibility and efficiency of the Inertial Confinement Fusion (ICF) experiment warrants a comprehensive study of the effect of mixing characteristics of RTI and its dependence on defining parameters. With this broader objective in perspective, the objectives of this present investigation were mainly threefold: First was the validation of the novel setup of the Water channel system. Towards this objective, validation of Servo motor, splitter plate thickness effects, density and temperature measurements and single-mode experiments were performed. The second objective was to study the mixing and growth characteristics of binary and multi-mode initial perturbations seeking an explanation of behavior of the resultant flow structures by performing the first ever set of such highly controlled experiments. The first-ever set of experiments with highly controlled multi-mode initial conditions was performed. The final objective of this study was to measure and compare the bubble and spike velocities with single-mode initial conditions with existing analytical models. The data derived from these experiments would qualitatively and quantitatively enhance the understanding of dependence of mixing width on parametric initial conditions. The knowledge would contribute towards a generalized theory for RTI mixing with specified dependence on various parameters, which has a wide range of applications. The system setup was validated to provide a reliable platform for the novel multi-modal experiments to be performed in the future. It was observed that the ensemble averaged mixing width of the binary system does not vary significantly with the phase-difference between the modes of a binary mode initial condition experiment, whereas it varies with the amplitudes of the component modes. In the exponential and non-linear regimes of evolution, growth rates of multi-mode perturbations were found to be higher than the component modes, whereas saturation growth rates correspond to the dominant wavelength. Quadratic saturation growth rate constants, alpha were found to be about 0.07 ± 0.01 for binary and multi modes whereas single-mode data measured alpha about 0.06 ± 0.01. High-speed imaging was performed to measure bubble and spike amplitudes to obtain velocities and growth rates. It was concluded that higher temporal and spatial resolution was required for accurate measurement. The knowledge gained from the above study will facilitate a better understanding of the physics underlying Rayleigh-Taylor instability. The results of this study will also help validating numerical models for simulation of this instability, thereby providing predictive capability for more complex configurations.

Magister Commercii - MCom / Nearly half a century after independence, the Cameroon economy has experienced little or no growth in per capita incomes in spite of the enormous natural and human potentials of the country and in spite of the huge packages of aid and subsequent debt relief received from the international donor community, suggesting a more profound cause to the development problems facing the country. Under the current WTO rules-based system of multi-lateral trade management, Cameroon, like other poor countries, is left with limited scope for effective implementation of industrial and trade policies that could bail her out of her present predicament. Against this backdrop, this study seeks to explore the fundamental determinants of sustainable growth within the context of the Cameroonian economy. While acknowledging the role of openness to international markets in promoting growth, its effects could only be maximised with the attainment of certain threshold conditions such as the availability of basic skills, provision of vital infrastructure services and public goods, and good governance. In a nutshell, for development to happen, the country needs not only well functioning markets, but also good governments that do not steal the fruits of workers' labour. Drawing on the endogenous growth models, the study suggests that incentives for investment in knowledge capital, for infrastructure provision and for good governance could bail the country out of its low level traps, setting it on the path of sustainable growth in an evermore globalising world economy.

No description available.

La mise en œuvre de méthodes d'assimilation d'ensemble est une technique assez récente visant à simuler les erreurs d'analyse et de prévision d'un système d'assimilation de données. Cela permet d'une part d'estimer des covariances spatiales des erreurs de prévision, qui sont un ingrédient essentiel des systèmes d'assimilation de données, dans la mesure où elles permettent de filtrer et de propager spatialement l'information observée. La dépendance de ces covariances d'erreur à la situation météorologique devient ainsi accessible avec ces techniques d'ensemble. D'autre part, l'assimilation d'ensemble est également une méthode de plus en plus utilisée pour fournir des perturbations initiales aux systèmes de prévision d'ensemble. Une telle approche peut être mise en place non seulement dans un système modélisant l'atmosphère sur l'ensemble du globe, mais aussi dans un système régional à aire limitée, en utilisant dans ce cas des conditions limites latérales appropriées. Le sujet de thèse proposé consiste à examiner certaines propriétés de sensibilité de ces techniques d'assimilation d'ensemble dans ces deux types de contextes (à savoir global et régional, respectivement). Il s'agit premièrement d'étudier la sensibilité d'un système global d'assimilation d'ensemble à son initialisation. Cela sera mené en comparant une technique d'initialisation "à froid" (basée sur des perturbations initiales nulles) avec une méthode basée sur des perturbations initiales tirées d'un modèle de covariance. Dans une deuxième partie, la sensibilité d'une assimilation d'ensemble régionale aux conditions limites latérales sera examinée. Dans cette perspective, une comparaison entre différentes techniques de production des perturbations latérales sera réalisée. Il s'agit notamment de comparer les approches basées sur des perturbations latérales qui sont soit nulles, soit tirées d'un ensemble global, ou encore produites à l'aide d'un modèle de covariance. Ces études de sensibilité seront menées d'une part en utilisant des expérimentations avec les systèmes global Arpege et régional Aladin. Ce travail s'appuiera d'autre part sur une formalisation des équations qui gouvernent l'évolution des perturbations au sein d'une assimilation d'ensemble. Ces études devraient permettre de documenter les propriétés de ces assimilations d'ensemble, et de définir des stratégies de mise en œuvre en grandeur réelle pour l'assimilation de données ainsi qu'éventuellement pour la prévision d'ensemble. / The implementation of ensemble assimilation methods is a fairly recent technique used to simulate the analysis and forecast errors within a data assimilation system. On the one hand, this allows to estimate the spatial covariances of forecast errors, which are an essential component in data assimilation systems, insofar as they are used to filter and disseminate spatially the observed information. The dependence of such error covariances to the weather situation becomes accessible with these ensemble techniques. On the other hand, the ensemble assimilation is a method increasingly used to provide initial perturbations to ensemble prediction systems. Such approach may be implemented not only in a system modeling the atmosphere throughout the globe, but also in a regional system with limited area using suitable lateral boundary conditions. The proposed thesis consists on examining some sensitivity properties of these ensemble assimilation techniques in both contexts (global and regional, respectively). In the first part, the sensitivity of a global ensemble assimilation system to its initialization will be examined. This will be conducted by comparing a "cold" initialization technique (initial perturbations equal to zero) with a method based on initial perturbations drawn from a covariance model. In the second part, the sensitivity of a regional ensemble assimilation to lateral boundary conditions will be considered. In this context, a comparison between different techniques producing lateral boundaries will be achieved. It involves comparing approaches using lateral boundaries which are equal to zero or drawn from a global ensemble, or generated using a covariance model. These sensitivity studies will be conducted using experiments using the global and regional modeling systems, Arpège and Aladin respectively. Furthermore, this work will be based on a formalization of the equations governing the evolution of perturbations in an ensemble assimilation. These studies should help to document the ensemble assimilation properties, and develop strategies for implementing in real scale for data assimilation and possibly for ensemble prediction system.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-14T11:21:59Z No. of bitstreams: 1 joaopauloananiassilva.pdf: 3095899 bytes, checksum: 88e8d49f662cce4952a994126dbb718b (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-16T13:00:34Z (GMT) No. of bitstreams: 1 joaopauloananiassilva.pdf: 3095899 bytes, checksum: 88e8d49f662cce4952a994126dbb718b (MD5) / Made available in DSpace on 2017-03-16T13:00:34Z (GMT). No. of bitstreams: 1 joaopauloananiassilva.pdf: 3095899 bytes, checksum: 88e8d49f662cce4952a994126dbb718b (MD5) Previous issue date: 2016-09-12 / Este trabalho objetiva explorar a generalização e flexibilização da modelagem matemáticaparasimulaçãonuméricadasdinâmicasdecurtoelongoprazodoscomponentes dos sistemas elétricos de potência. Para isto, é apresentada uma metodologia que busca explicitar os elementos integradores mostrando como estes podem ser manipulados visando tornar a solução das dinâmicas em sistemas de potência mais flexível. Ao explicitar o elemento integrador é possível flexibilizar a escolha do método de integração, o cálculo das condições iniciais para as variáveis de estado e, inclusive, a estratégia para eliminação de dinâmicas dependendo do estudo a ser realizado. O método empregado para a solução do conjunto de equações algébrico-diferenciais é o simultâneo, ou seja, a rede é solucionada juntamente com as equações que modelam os equipamentos. Este conjunto é obtido através da conversão das equações diferenciais em equações das diferenças, empregando o método de integração trapezoidal, formando um único conjunto algébrico e não linear, que é resolvido pelo método de Newton-Raphson. Todos os aspectos discutidos neste trabalho referentes a modelagem matemática são empregados no desenvolvimento de uma ferramenta de simulação flexível utilizando a linguagem de programação Python. Por fim, a metodologia proposta e a ferramenta são avaliadas através do estudo de três sistemas teste. Os resultados obtidos são comparados aos do programa ANATEM e, na sequência, é realizada uma análise do desempenho computacional. / This work aims to explore the generalisation and flexibility of mathematical modelling to numerical simulation of dynamic short and long-term components of electric power systems. Thus, it is presented a methodology that seeks to clarify the integrating elements showing how these can be manipulated in order to make the solution of dynamics in power systems more flexible. After the integrating element be explained, it is possible to make the choice of integration method flexible, the calculation of initial conditions for the state variables and even the strategy for eliminating dynamics depending on the study to be performed. It was used the simultaneous method to solve the set of algebraic-differential equations. In other words, the network and the equations that model the equipment are solved in a single set of equations and simultaneously. It was used the trapezoidal integration method to convert the differential equations into difference equations. This process generates a non-linear algebraic set, which is solved by the Newton-Raphson method. Every aspect discussed in this work regarding the mathematical modelling are employed in the development of a flexible simulation tool using the Python programming language. Finally, the proposed methodology and the tool are evaluated by studying three different test systems. The obtained results are compared to the ANATEM program, following a computational efficiency analysis.

This thesis develops the methodology for solving initial boundary value problems with the use of summation-by-parts discretizations. The combination of high orders of accuracy and a systematic approach to construct provably stable boundary and interface procedures makes this methodology especially suitable for scientific computations with high demands on efficiency and robustness. Most classes of high order methods can be applied in a way that satisfies a summation-by-parts rule. These include, but are not limited to, finite difference, spectral and nodal discontinuous Galerkin methods. In the first part of this thesis, the summation-by-parts methodology is extended to the time domain, enabling fully discrete formulations with superior stability properties. The resulting time discretization technique is closely related to fully implicit Runge-Kutta methods, and may alternatively be formulated as either a global method or as a family of multi-stage methods. Both first and second order derivatives in time are considered. In the latter case also including mixed initial and boundary conditions (i.e. conditions involving derivatives in both space and time). The second part of the thesis deals with summation-by-parts discretizations on multi-block and hybrid meshes. A new formulation of general multi-block couplings in several dimensions is presented and analyzed. It collects all multi-block, multi-element and  hybrid summation-by-parts schemes into a single compact framework. The new framework includes a generalized description of non-conforming interfaces based on so called summation-by-parts preserving interpolation operators, for which a new theoretical accuracy result is presented.

本研究設計了一些實驗來檢測學習完混沌資料的神經網路系統是否為混沌系統，驗證的方法是檢驗是否具有混沌資料的四個特性，這四個特性包括：有限性、非週期性、確定性、及對初始條件的敏感依賴。同時，更進一步地利用上述學習完的網路系統來預測所學習的混沌模型，這麼做的目的是想要了解：學習後的網路系統是一個混沌系統時，與學習後網路系統不是一個混沌系統時，其預測能力的比較。 此外，我們亦從理論上證明：學習完混沌資料後的神經網路系統無法重建其所學習的混沌模型。然而，有時網路系統卻能夠模擬成一個混沌系統；如果使用模擬成混沌系統的神經網路來預測具有混沌現象的資料，換句話說，也就可能是使用一個混沌系統去預測另一個混沌系統，根據混沌的特性 -- 對初始條件的敏感依賴，這樣的預測應該會造成相當大的誤差；不過，從本研究的實驗中發現，無論學習後的神經網路系統是否為一個混沌系統，對其預測能力並無顯著的影響。 本論文希望能給「用神經網路系統來預測具有混沌現象的金融市場或其他領域」一些貢獻與幫助。 / This paper uses some experimental designs to detect if the Neural Networks system after learning the chaotic data is a chaotic system. That is verified via testing four characteristics in chaotic data, inclusive of boundedness, determinism, aperiodicity and sensitive dependence on initial conditions. Further, this paper uses the result above to predict the learned chaotic model. The purpose is to probe into if the Neural Networks system after learning the chaotic data is a chaotic system and is used to predict, how good the short-term and the long-term predictions will be? And, compare with if the Neural Networks system after learning the chaotic data is not a chaotic system and is used to predict, how large the error will be? We present the Neural Network systems after learning the chaotic data never can rebuild the learned chaotic model. But, sometimes the Neural Network system would mimic as a chaotic system. So, if we take Neural Network system to predict something with chaotic phenomena, it is possible to use one chaotic system to predict another chaotic system. According to the property of sensitive dependence on initial conditions, it should make large errors. However, from the experiments we design, we find whether the Neural Network system after learning is a chaotic system or not, it has no influence on its predicting effect. This hint is applied to use ANN to predict in financial markets or other areas with chaotic phenomenon.

Oil well blow outs are investigated to determine methods to quickly and accurately respond to an emergency situation. Flow rate is needed to guide containment and dispersal operations. The Stratified Integral Multiphase Plume, SIMP, model was used to investigate the range of initial conditions available to integral modeling. Sensitivity to initial conditions is modest, but without experimental data at the appropriate scale the most accurate condition is unable to be determined. Flow rates are difficult to directly measure in blow out situations, so another method must be determined; therefore, sensitivity of several parameters to flow rate was also evaluated. Methane concentration in the first intrusion can be used in conjunction with velocity and trap height measurements to determine flow rate using an integral model. Plume width and temperature were determined to have little sensitivity. Separately, a containment dome was tested in the laboratory to determine if a full scale dome can be used to contain an oil leak in the field. The dome was found to have satisfactory entrapment in the designed position.