Made available in DSpace on 2014-06-12T15:52:55Z (GMT). No. of bitstreams: 1 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Nos últimos anos, a redução do consumo de energia das aplicações dos sistemas embarcados tem recebido uma grande atenção da comunidade científica, visto que, como o tempo de resposta e o baixo consumo de energia são requisitos conflitantes, esses estudos tornam-se altamente necessários. Nesse contexto, é proposta uma metodologia aplicada nas fases iniciais de projeto para dar suporte às decisões relativas ao consumo de energia e ao desempenho das aplicações desses dispositivos embarcados. Al´em disso, esse trabalho propõe modelos temporizados de eventos discretos que são avaliados através de uma metodologia de simulção estocástica com o objetivo de representar diferentes cenários dos sistemas com facilidade. Dessa forma, para cada cenário ´e preciso decidir o n´umero máximo de simulações e o tamanho de cada rodada da simulação, onde ambos os fatores podem impactar no desempenho para se obter tais estimativas. Essa metodologia considera também, um modelo intermediário que representa a descrição do comportamento do sistema e, é através desse modelo que cenários são analisados. Esse modelo intermediário ´e baseado em redes de Petri coloridas temporizadas que permitem não somente a anáise do software, mas também fornece suporte a um conjunto de métodos bem estabelecidos para verificações de propriedades. É nesse contexto que o software, ALUPAS, responsável por estimar o consumo de energia e o tempo de execução dos sistemas embarcados é apresentado. Por fim, um caso de estudo real, assim como tamb´em, exemplos customizados são apresentados com a finalidade de mostrar a aplicabilidade desse trabalho, onde usuários não especializados não precisam interagir diretamente com o formalismo de redes de Petri.

With the issuing of Pension Funds circular PF117 in 2004 in South Africa, regulation required valuation assumptions for defined benefit pension funds to be on a best-estimate basis. Allowance for prudence was to be made through explicit contingency reserves, in order to increase reporting transparency. These reserves for prudence, however, were not permitted to put the fund into deficit (the no-deficit clause). Analysis is conducted to understand the risk that PF117 poses to pension fund sponsors and members under two key measures: contribution rate risk and solvency risk. A stochastic model of a typical South African defined benefit fund is constructed with simulations run to determine the impact of the PF117 requirements. Findings show that a best-estimate funding basis, coupled with the no-deficit clause, results in significant risk under both contribution rate and solvency risk measures, particularly in the short-term. To mitigate these risks, alternative ways of introducing conservatism into the funding basis are required, with possible options including incorporating margins into investment return assumptions or the removal of the no-deficit clause.

Recent research in experimental and computational biology has revealed the necessity of using stochastic modeling and simulation to investigate the functionality and dynamics of gene networks. However, there is no sophisticated stochastic modeling techniques and efficient stochastic simulation algorithms (SSA) for analyzing and simulating gene networks. Therefore, the objective of this research is to design highly efficient and accurate SSAs, to develop stochastic models for certain real gene networks and to apply stochastic simulation to investigate such gene networks. To achieve this objective, we developed several novel efficient and accurate SSAs. We also proposed two stochastic models for the circadian system of Drosophila and simulated the dynamics of the system. The K-leap method constrains the total number of reactions in one leap to a properly chosen number thereby improving simulation accuracy. Since the exact SSA is a special case of the K-leap method when K=1, the K-leap method can naturally change from the exact SSA to an approximate leap method during simulation if necessary. The hybrid tau/K-leap and the modified K-leap methods are particularly suitable for simulating gene networks where certain reactant molecular species have a small number of molecules. Although the existing tau-leap methods can significantly speed up stochastic simulation of certain gene networks, the mean of the number of firings of each reaction channel is not equal to the true mean. Therefore, all existing tau-leap methods produce biased results, which limit simulation accuracy and speed. Our unbiased tau-leap methods remove the bias in simulation results that exist in all current leap SSAs and therefore significantly improve simulation accuracy without sacrificing speed. In order to efficiently estimate the probability of rare events in gene networks, we applied the importance sampling technique to the next reaction method (NRM) of the SSA and developed a weighted NRM (wNRM). We further developed a systematic method for selecting the values of importance sampling parameters. Applying our parameter selection method to the wSSA and the wNRM, we get an improved wSSA (iwSSA) and an improved wNRM (iwNRM), which can provide substantial improvement over the wSSA in terms of simulation efficiency and accuracy. We also develop a detailed and a reduced stochastic model for circadian rhythm in Drosophila and employ our SSA to simulate circadian oscillations. Our simulations showed that both models could produce sustained oscillations and that the oscillation is robust to noise in the sense that there is very little variability in oscillation period although there are significant random fluctuations in oscillation peeks. Moreover, although average time delays are essential to simulation of oscillation, random changes in time delays within certain range around fixed average time delay cause little variability in the oscillation period. Our simulation results also showed that both models are robust to parameter variations and that oscillation can be entrained by light/dark circles.

Les études théoriques en épidémiologie utilisent principalement des équations différentielles pour étudier (voire tenter de prévoir) les processus infectieux liés aux maladies contagieuses, souvent sous des hypothèses peu réalistes (ex: des populations spatialement homogènes). Cependant ces modèles ne sont pas bien adaptés pour étudier les processus épidémiologiques à différentes échelles et ils ne sont pas efficaces pour prédire correctement les épidémies. De tels modèles devraient notamment être liés à la structure sociale et spatiale des populations. Dans cette thèse, nous proposons un ensemble de nouveaux modèles dans lesquels différents niveaux de spatialité (par exemple la structure locale de la population, en particulier la dynamique de groupe, la distribution spatiale des individus dans l'environnement, le rôle des personnes résistantes, etc.) sont pris en compte pour expliquer et prédire la façon dont des maladies transmissibles se développent et se répandent à différentes échelles, même à l'échelle de grandes populations. La manière dont les modèles que nous avons développé sont paramétrés leur permet en outre d'être reliés entre eux pour bien décrire en même temps le processus épidémiologique à grande échelle (population d'une grande ville, pays ...) mais avec précision dans des zones de surface limitée (immeubles de bureaux, des écoles). Nous sommes d'abord parvenus à inclure la notion de groupes dans des systèmes d'équations différentielles de modèles SIR (susceptibles, infectés, résistants) par une réécriture des dynamiques de population s'inspirant des réactions enzymatiques avec inhibition non compétitive : les groupes (une forme de complexe) se forment avec des compositions différentes en individus S, I et R, et les individus R se comportent ici comme des inhibiteurs non compétitifs. Nous avons ensuite couplé de tels modèles SIR avec la dynamique globale des groupes simulée par des algorithmes stochastiques dans un espace homogène, ou avec les dynamiques de groupe émergentes obtenues dans des systèmes multi-agents. Comme nos modèles fournissent de l'information bien détaillée à différentes échelles (c'est-à-dire une résolution microscopique en temps, en espace et en population), nous pouvons proposer une analyse de criticité des processus épidémiologiques. Nous pensons en effet que les maladies dans un environnement social et spatial donné présentent des signatures caractéristiques et que de telles mesures pourraient permettre l'identification des facteurs qui modifient leur dynamique.Nous visons ainsi à extraire l'essence des systèmes épidémiologiques réels en utilisant différents modèles mathématique et numériques. Comme nos modèles peuvent prendre en compte les comportements individuels et les dynamiques de population, ils sont en mesure d'utiliser des informations provenant du BigData, collectée par les technologies des réseaux mobiles et sociaux. Un objectif à long terme de ce travail est d'utiliser de tels modèles comme de nouveaux outils pour réduire les épidémies en guidant les rythmes et organisation humaines, par exemple en proposant de nouvelles architectures et en changeant les comportements pour limiter les propagations épidémiques. / Theoretical studies in epidemiology mainly use differential equations, often under unrealistic assumptions (e.g. spatially homogeneous populations), to study the development and spreading of contagious diseases. Such models are not, however, well adapted understanding epidemiological processes at different scales, nor are they efficient for correctly predicting epidemics. Yet, such models should be closely related to the social and spatial structure of populations. In the present thesis, we propose a series of new models in which different levels of spatiality (e.g. local structure of population, in particular group dynamics, spatial distribution of individuals in the environment, role of resistant people, etc) are taken into account, to explain and predict how communicable diseases develop and spread at different scales, even at the scale of large populations. Furthermore, the manner in which our models are parametrised allow them to be connected together so as to describe the epidemiological process at a large scale (population of a big town, country ...) and with accuracy in limited areas (office buildings, schools) at the same time.We first succeed in including the notion of groups in SIR (Susceptible, Infected, Recovered) differential equation systems by a rewriting of the SIR dynamics in the form of an enzymatic reaction in which group-complexes of different composition in S, I and R individuals form and where R people behave as non-competitive inhibitors. Then, global group dynamics simulated by stochastic algorithms in a homogeneous space, as well emerging ones obtained in multi-agent systems, are coupled to such SIR epidemic models. As our group-based models provide fine-grain information (i.e. microscopical resolution of time, space and population) we propose an analysis of criticality of epidemiological processes. We think that diseases in a given social and spatial environment present characteristic signatures and that such measurements could allow the identification of the factors that modify their dynamics.We aim here to extract the essence of real epidemiological systems by using various methods based on different computer-oriented approaches. As our models can take into account individual behaviours and group dynamics, they are able to use big-data information yielded from smart-phone technologies and social networks. As a long term objective derived from the present work, one can expect good predictions in the development of epidemics, but also a tool to reduce epidemics by guiding new environmental architectures and by changing human health-related behaviours.

Gillespie's Stochastic Simulation Algorithm (SSA) provides an elegant simulation approach for simulating models composed of coupled chemical reactions. Although this approach can be used to describe a wide variety biological, chemical, and ecological systems, often systems have external behaviors that are difficult or impossible to characterize using chemical reactions alone. This work extends the applicability of the SSA by adding mechanisms for the inclusion of external events and external triggers. We define events as changes that occur in the system at a specified time while triggers are defined as changes that occur to the system when a particular condition is fulfilled. We further extend the SSA with the efficient implementation of these model parameters. This work allows numerous systems that would have previously been impossible or impractical to model using the SSA to take advantage of this powerful simulation technique.

This study focuses on the development of a stochastic simulation methodology to study the effects of cure kinetics uncertainty, in plane fibre misalignment and boundary conditions uncertainty on the cure process of composite materials. Differential Scanning Calorimetry was used to characterise cure kinetics variability of a commercial epoxy resin used in aerospace applications. It was found that cure kinetics uncertainty is associated with variations in the initial degree of cure, activation energy and reaction order. Image analysis was employed to characterise in plane fibre misalignment in a carbon fibre ±45º non-crimp fabric. The experimental results showed that variability in tow orientation was significant with a standard deviation of about 1.2º. A set of experiments using an infusion set-up was carried out to quantify boundary conditions uncertainty related to tool temperature, ambient temperature and surface heat transfer coefficient using thermocouples (tool/ambient temperature) and heat flux sensors (surface heat transfer coefficient). It was concluded that boundary conditions uncertainty can show considerable short term and long term variability. Conventional Monte Carlo and Probabilistic Collocation Method were integrated with a thermo-mechanical cure simulation model in order to investigate the effect of cure kinetics, fibre misalignment and boundary conditions variability on process outcome. The cure model was developed and implemented using a finite element model incorporating appropriate material sub-models of cure kinetics, specific heat capacity, thermal conductivity, moduli, thermal expansion and cure shrinkage. The effect of cure kinetics uncertainty on the temperature overshoot of a thick carbon fibre epoxy flat panel was investigated using the two stochastic simulation schemes. The stochastic simulation results showed that variability in cure kinetics can introduce a significant scatter in temperature overshoot, presenting a coefficient of variation of about 30%. Furthermore, it was shown that the collocation method can offer an efficient solution with significantly lower computational cost compared to Monte Carlo at comparable accuracy. Stochastic simulation of the cure of an angle shaped carbon fibre-epoxy component within the Monte Carlo scheme showed that fibre misalignment can cause considerable variability in the process outcome. The coefficient of variation of maximum residual stress can reach up to approximately 2% (standard deviation of 1 MPa) whilst qualitative and quantitative variations in final distortion of the cured part occur with the standard deviation in twist and corner angle reaching values of 0.4 º and 0.05º respectively. Simulation of the cure of a thin carbon fibre-epoxy panel within the Monte Carlo scheme indicated that surface heat transfer and tool temperature variability dominate variability in cure time, resulting in a coefficient of variation of about 22%. In addition to Monte Carlo, the effect of surface heat transfer coefficient and tool temperature variations on cure time was addressed using the collocation method. It was found that probabilistic collocation is capable of capturing variability propagation with good accuracy while offering tremendous benefits in terms of computational costs.

Les réseaux de fractures et les karsts constituent des discontinuités au sein de la roche qui affectent considérablement les écoulements de fluides, ce qui engendre des problèmes spécifiques dans divers domaines des géosciences. La problématique générale consiste à déterminer les caractéristiques géométriques et hydrauliques des réseaux de fractures ou de karsts. La caractérisation et la modélisation de ces structures se heurtent cependant à leur complexité géométrique et à leur distribution spatiale hétérogène. De plus, les observations et données directes concernant aussi bien les fractures et karsts que leur encaissant rocheux restent largement insuffisantes pour décrire avec certitudes leurs caractéristiques. Pour ces raisons, la modélisation de réseaux de fractures ou de karsts est le plus souvent réalisée dans un cadre probabiliste. Des simulations stochastiques de type objet ou pixel sont généralement mise en œuvre pour générer des modèles 3D de fractures ou karsts. Cependant les mécanismes sur lesquels repose ce type d'approche ne permet pas de reproduire toutes la complexité de ces objets naturels et fournit des modèles manquant de réalisme géologique.Dans ces travaux de thèse, nous proposons d'aborder la problématique de la modélisation des fractures et des karsts suivant une approche pseudo-génétique. Il s'agit de contraindre le processus de simulation stochastique de fractures et karsts par des règles géométriques et heuristiques qui imitent les processus physiques gouvernant leur formation. Deux méthodes poursuivant cet objectif ont été développées, l'une adressant la simulation des fractures et la seconde celle des karsts. Les modèles ainsi générés exposent des caractéristiques similaires à celles des réseaux de fractures et karsts naturels. / Fractures and karstic networks are known to significantly affect flow paths and therefore raise specific issues in a wide variety of geoscience fields. The common question beyond these problems isto determine whether there is a network of fractures and/or karstic conduits and if yes what are itsgeometrical and hydraulic characteristics. Characterization and modeling of these features is a challenge for it usually displays complex geometries and heterogeneous spatial distribution. Moreover, in most cases, neither fracture and karst nor their host environment can be observed or described with certainty at all scales and location of relevance. For these reasons, fractures and karstic networks are usually integrated into 3D geological model through a probabilistic framework. Stochastic object- or pixel-based simulations are commonly performed to generate 3D models of fractures and karst but failed to reproduce the whole complexity of these natural objects and 3D models often lack geological realism.To address the issues related to fracture and karst modeling, we present two genetic-like approaches. The motivation of this work is to constrain the stochastic simulation of fractures and karsts by geometrical and heuristic rules which mimic the physical processes governing their formation. The resulting fracture and karst models display similar characteristics as those of natural pattern.

[pt] O principal objetivo dessa dissertação é elaborar um modelo estocástico e implementar um simulador para a fluxo de caixa de ativos e passivos para uma simplificação de um plano de previdência privada de um único indivíduo. / [en] The main objective of this work is to propose a sthocastic model and to implement a simulator for the cash flow considering the assets and liabilities of a single person retirement plain.

Les réseaux karstiques s'organisent de manière hiérarchique et se comportent comme des drains pour l'écoulement des fluides souterrains. Cependant seule une partie limitée de ces réseaux karstiques est généralement humainement observable, et la connaissance globale d'un système reste limitée. Les simulations géostatistiques représentent un moyen d’étudier les différentes configurations des réseaux karstiques tridimensionnels (3D) probables et ainsi de déterminer les incertitudes sur le comportement du réservoir. Établir une telle démarche nécessite de comprendre les étapes de structuration d'un karst donné à partir de déterminations karstologiques permettant d'identifier la morphogenèse des formes exo- et endokarstique et de reconstituer l'évolution spéléogénétique d'un massif (spéléogenèse épigène ou hypogène, évolution du niveau de base, etc.). Cela a permis de définir une zonation de l'occurrence de l'organisation des structures karstiques (zone vadose, épiphréatique ou phréatique). En parallèle, l'analyse quantitative de géométries et de topologies de données 3D de cavités analogues a permis de comparer les différentes structures de réseaux karstiques et de fournir une base de données quantitative de caractéristiques morphologiques de cavités en fonction de processus spéléogénétiques. Deux approches géostatistiques ont été testées pour la simulation stochastique de réseaux karstiques. Elles reposent sur l'utilisation de méthodes classiques de géostatistiques basées-pixel : la simulation séquentielle d’indicatrice (SIS) et les simulations multipoints (MPS). / Karst networks are hierarchically organized and behave as drains for underground fluid flows. However, the humanly observed karst conduits represent only a limited part of the complete karst conduit system, and overall knowledge remains limited. Geostatistical stochastic simulations represent an interesting tool to study the different three-dimensional (3D) probable configurations of karst networks and then, to determine the uncertainties on the reservoir behaviors. This approach first requires understanding the successive stages of karst structuring of a reservoir and then to numerically reconstruct the 3D organization of karst structures. From karstological determinations, it is possible to identify the morphogenesis of the exo- and endokarst forms and to reconstitute the speleogenetic evolution of a massif (epigenic or hypogenic speleogenesis, evolution of the basic level, etc.). The speleogenetic reconstitutions then make it possible to identify the successive phases of the karst system structuration (epigenic or hypogenic speleogenesis, evolution of base level, etc.). In parallel, a quantitative analysis of the geometries and the topologies performed on 3D cave surveys permits to compare the different organizations of the karst network patterns, related to speleogenetic processes. This morphometric analysis provides a quantitative database of morphological characteristics according to their speleogenetic processes. Finally, two geostatistical approaches were tested to generate karst networks. They correspond to two classical pixel-based geostatistical methods: the sequential indicator simulation (SIS) and the multipoint simulations (MPS).

Ao longo dos anos, pesquisadores têm liderado estudos com o objetivo de investigar o perfil de consumo de água em edifícios, os quais contribuem para o conhecimento no que tange ao correto dimensionamento dos sistemas prediais. No contexto dos métodos para a caracterização das solicitações, as rotinas comumente empregadas para a obtenção das vazões de projeto foram, em sua maioria, propostas na metade do século XX. Estes modelos precisam ser revisados e readequados para a realidade de conservação existente atualmente. Nos últimos anos, alguns estudos propuseram modelos de simulação com foco de aplicação em sistemas prediais de distribuição de água, devido ao comportamento aleatório e temporal das solicitações neste tipo de sistema. Neste trabalho foi proposto um modelo de simulação estocástica da demanda de água em edifícios residenciais, que contemplou a modelagem comportamental dos usuários e a interação destes com o sistema, a fim de aperfeiçoar o processo de dimensionamento dos sistemas prediais de distribuição de água. Para isto, foram revisadas as bases teóricas de modelos propostos anteriormente com interesse de identificar aspectos significativos e construir um novo modelo, que mesclou a modelagem comportamental dos usuários e do sistema hidráulico. Para a obtenção dos valores das variáveis intervenientes, foi feita uma consulta em trabalhos dentro do contexto nacional e uma coleta de dados em campo. Os resultados da pesquisa em campo mostraram a correlação entre a rotina dos usuários e o volume de água consumida e um aumento médio de 192% do valor da vazão de projeto obtida pelo Método dos Pesos Relativos quando comparada com as vazões obtidas no medidor dos apartamentos monitorados. Em posse de todos os dados de entrada, foram feitas diferentes simulações que variaram o tipo do chuveiro instalado nos apartamentos. Quando comparadas as vazões obtidas pela simulação e pelo Método dos Pesos Relativos, em todos os componentes do sistema, a redução da vazão de projeto variou entre 4% e 61%. Em termos de consumo de material, a redução ficou entre 25% a 63%. / Over the years, researchers have been conducting studies to investigate the water consumption profile in buildings, which contribute to the knowledge regarding the correct sizing of the building hydraulic systems. In context of the methods for characterization of requests, the routines commonly used to obtain the project flows were mostly proposed in mid-20th-century. These models need to be revised and adapted to nowadays water conservation reality. In recent years, some studies have proposed simulation models with application focus in water distribution systems, due to the random and temporal behavior of the requests in this type of system. In this study, a stochastic simulation model of water demand in residential buildings has been proposed, which contemplated the behavioral modeling of users and their interaction with the system, in order to improve the design process of water distribution systems. For such, the theoretical bases of previously- proposed models for the identification of significant aspects for the construction of a new model were revised, which merged the behavioral modeling of users and the hydraulic system. In order to obtain the values of intervening variables, fieldworks and a review was conducted in papers which treated about the Brazilian context. The results of the data collected on the fieldworks show a correlation between the routine of users and the volume of water consumed. Besides, there was an average increase of 192% in the value of the project flow rate obtained by the Brazilian Standard Method when compared with the flows obtained in the monitored apartments. Considering the input data in the model, different simulations - with several different types of showers installed in the apartments - were made. When comparing the flows obtained by the simulation and the Brazilian Standard Method, in all components of the system, the reduction of the project flow varied between 4% and 61%. In terms of material consumption, the reduction was between 25% and 63%.