Simulações computacionais são ferramentas essenciais para o estudo de sistemas físicos à temperatura finita. Geralmente, as técnicas utilizadas são: método de Monte Carlo (MC) e de Dinâmica Molecular (DM); tradicionalmente potenciais empíricos são empregados. Entretanto, esses potenciais são ajustados para uma dada configuração e não há nenhuma garantia de que eles também serão acurados para outras situações. Assim, existe um grande interesse em combinar as técnicas de simulação com métodos que descrevam a estrutura eletrônica com grande precisão, os chamados métodos de primeiros princípios. Nesse trabalho, implementamos um programa de MC no qual a energia total das configurações é obtida via Teoria do Funcional da Densidade (DFT). Como aplicação de nossa metodologia estudamos inicialmente um aglomerado de Silício (Si_5). Nessas simulações, investigamos as propriedades estruturais dos aglomerados em função da temperatura e estimamos a faixa de temperatura de transição de fase. Além disso, propomos uma nova abordagem para simulações de água, em que combinamos o MC ab initio com otimizações intramoleculares de geometria. Para exemplificar a metodologia, mostraremos os resultados das simulações para o dímero de água, um sistema protótipo em que aparecem os dois tipos de ligações: intra e intermoleculares. / Computer simulations are essential tools to the research of physical systems at finite temperatures. Monte Carlo (MC) and Molecular Dynamics (MD) methods are the major techniques used for this purpose, and empirical potentials are traditionally employed in these simulations. These potentials, however, are built to describe with precision the system near some region of its configuration space, thus there is no guarantee that they will provide reliable results in other instances. Therefore, there is a great interest in the combination of MC and MD simulations with methods that describe the electronic structure with high precision (ab initio methods). In this work we have developed a MC program where the total configurational energies are obtained via Density Functional Theory (DFT). As an initial application of our methodology we have studied a silicon cluster (Si5). In these simulations we have investigated the structural properties of these cluster at diferent temperatures and estimated the melting temperature. Furthermore, we also propose a new formulation for water simulations,where we combine the ab initio MC with intramolecular geometry optimizations. As an illustration of our methodology, we show the results for the water dimer simulations. This system is a prototype of the hydrogen bond where we already have both intra and intermolecular bonds.

The power usage of the communication technology industry and the consistent energy-related pollution are becoming major societal and economic concerns. These concern stimulated academia and industry to an intense activity in the new research area of green cellular networks. Bandwidth Efficiency (BE) is one of the most important metrics to select candidate technologies for next-generation wireless communications systems. Nevertheless, the important goal is to design new innovative network architecture and technologies needed to encounter the explosive development in cellular data demand without increasing the power consumption. As a result, Energy Efficiently (EE) has become another significant metric for evaluating the performance of wireless communications systems. MIMO technology has drawn lots of attention in wireless communication, as it gives substantial increases in link range and throughput without an additional increase in bandwidth or transmits power. Multi-user MIMO (MU-MIMO) regarded when evolved Base Station equipped with multiple antennas communicates with several User Terminal (UEs) at the same time. MU-MIMO is capable of improving either the reliability or the BE by improving either the multiplexing gains or diversity gains. A proposed new idea in MU-MIMO refers to the system that uses hundreds of antennas to serve dozens of UEs simultaneously. This so-called, Large Scale-MIMO (LS MIMO) regarded as a candidate technique for future wireless communication systems. An analysis is conducted to investigate the performance of the proposed uplink and downlink of LS MIMO systems with different linear processing techniques at the base station. The most common precoding and receive combining are considered: minimum mean squared error (MMSE), maximum ratio transmission/combining (MRT/MRC), and zero-forcing (ZF)processing. The fundamental problems answered on how to select the number of (BS) antennas M, number of active (UEs) K, and the transmit power to cover a given area with maximal EE. The EE is defined as the number of bits transferred per Joule of energy. A new power consumption model is proposed to emphasise that the real power scales faster with M and K than scaling linearly. The new power consumption model is utilised for deriving closed-form EE maximising values of the number of BS antennas, number of active UEs and transmit power under the assumption that ZF processing is deployed in the uplink and downlink transmissions for analytic convenience. This analysis is then extended to the imperfect CSI case and to symmetric multi-cell scenarios. These expressions provide valuable design understandings on the interaction between systems parameters, propagation environment, and different components of the power consumption model. Analytical results are assumed only for ZF with perfect channel state information (CSI) to compute closed-form expression for the optimal number of UEs, number of BS antennas, and transmit power. Numerical results are provided (a) for all the investigated schemes with perfect CSI and in a single-cell scenario; (b) for ZF with imperfect CSI, and in a multi-cell scenario. The simulation results show that (a) an LS MIMO with 100 - 200 BS antennas are the correct number of antennas for energy efficiency maximisation; (b) these number of BS antennas should serve number of active UEs of the same size; (c) since the circuit power increases the transmit power should increase with number of BS antennas; (d) the radiated power antenna is in the range of 10-100 mW and decreases with number of BS antennas; (e) ZF processing provides the highest EE in all the scenarios due to active interference-suppression at affordable complexity. Therefore, these are highly relevant results that prove LS MIMO is the technique to achieve high EE in future cellular networks.

The thesis is focused on risk and uncertainty in decision theory. It introduces principles of choosing the best alternative in case of uncertainty and risk, as well as different ways how to quantify and manage the risk, therefore the risk management. The thesis also discusses simulation, definition of random numbers and generating of these numbers. Monte Carlo method is widely used in this area. One of the applications based on Monte Carlo method is Crystal Ball; detailed description of this application is also mentioned. At the close, an example of the capital project valuation is provided as the demonstration of Crystal Ball application.

Dissertation deals with the analysis of investment projects. Specifically it is focused on the utilization of probability approaches to analysis of investment projects. These approaches are represented by scenario analysis and Monte Carlo simulation.The treatis contains critical comparison of both approaches and offers the set of recommendation to the application of both methods. The inherent part of this work is postaudits analysis which are accompanied by the set of recommendation as well.

Neste trabalho estudamos o efeito hidrofóbico no sistema benzenoágua. Nossa estratégia é avaliar as propriedades das ligações de hidrogênio entre as moléculas de água nas proximidades da molécula e benzeno. Utilizamos as ferramentas da mecânica quântica e o método de simulação computacional para este estudo. A análise estrutural e energética detalhada dos clusters benzenoágua mostra que a ligação de hidrogênio é mais forte quando na presença do benzeno. A investigação pelo método de simulação Monte Carlo corrobora estas conclusões e ainda fornece os efeitos da variação de tempeatura. Verificamos que o aumento da temperatura afeta todas as moléculas aumentando a desordem líquida, no entanto, constatamos a manutenção de uma estrutura de ligações de hidrogênio mais fortes as proximidades do benzeno. A interação entre duas moléculas de benzeno também foi analisada, mostrando que a interação benzenobenzeno é bem mais forte na presença da água. / The hydrophobic effect is studied for the benzene-water system. The properties of the hydrogen bond between the water molecules around the benzene is evaluated using both classical and quantum mechanical methods. Hydrophobic hydration analysis shows that the hydrogen bond interaction is stronger in the presence of benzene. This is verified both by ab initio quantum mechanical methods and classical Monte Carlo simulation. Temperature dependence is investigated. Although increasing temperature increases the disorder the hydrogen bonds between the water molecules are still stronger for those in the proximities of the benzene. Hydrophobic interaction is also investigated. It is seen that the benzene-benzene interaction is stronger in the water environment.

Nesta tese, foram desenvolvidas três metodologias para análise dos riscos de interrupções em processos eletro-eletrônicos provocadas por faltas nos sistemas de distribuição de energia elétrica. Estas metodologias são: Monte Carlo, Enumeração de Estados e Híbrido. Com a utilização destas metodologias, são avaliados índices relativos às interrupções de longa duração e às variações de tensão de curta duração (afundamentos, elevações e disrupções de tensão) em cada consumidor da rede de distribuição de energia elétrica. Em cada barra do sistema, as freqüências de ocorrências de cada índice são obtidas, classificadas por faixas de magnitude e duração dos eventos. Conhecendo informações sobre a configuração e parâmetros de rede e sobre os dispositivos de proteção, através de um conjunto de simulações, é possível mapear as áreas de risco relativas aos fenômenos de interrupção e variações de tensão de curta duração (VTCDs). Dispondo ainda do conjunto de curvas de sensibilidade dos processos industriais, avaliam-se as freqüências de disrupções de processos, esperadas por ano no ponto analisado, isto é, o número de vezes que um processo apresenta mau funcionamento e possivelmente interrupção devido a uma VTCD. Também é apresentada nesta tese uma formulação matemática que permite realizar a inclusão do custo do prejuízo pela falta da qualidade de energia nos consumidores em modelos clássicos para o tratamento de problemas de planejamento da operação e da expansão de sistemas de distribuição de energia elétrica. Os métodos para avaliação das áreas de risco e custos de interrupção de processos por faltas nas redes de distribuição foram implementados em um sistema computacional. Resultados da aplicação em redes de distribuição reais permitem avaliar vantagens e desvantagens de cada um dos métodos. Para observar o impacto do prejuízo nos consumidores, são utilizados resultados obtidos na literatura para realizar a comparação e obter o custo total envolvendo custos de investimento de novas obras, custo de perdas de energia e custo do prejuízo pela falta da qualidade de energia nos consumidores existentes na rede de distribuição de energia elétrica. / Three methodologies for risk assessment of interruptions in electrical and electronic sensitive devices are herein developed. These interruptions are mainly due to faults in electric power distribution systems. The methodologies are herein named Monte Carlo Method, State Enumerating Method and Hybrid Method. These methods allow for the evaluation of indices related to long duration interruptions and voltages sags and swells in each customer supplied by the distribution network. The power quality indices (expected number of events per year) are classified according to voltage amplitude and event duration. The information regarding network configuration and parameters as well as protection devices are input for a set of simulations that result in mapping the indices related to long duration interruptions and short duration voltage variations along the network. By considering the sensitivity curves for industrial processes, the method determines the frequency of process disruptions, i.e. the number of events in which the customer process malfunctions, or it is damaged or it is interrupted due to voltage sags or swells. This thesis also shows a mathematical formulation that includes costs regarding customer losses caused by poor power quality to conventional models that deal with operation and expansion planning of electric power distribution systems. The proposed methods for assessing risks and interruption costs in customer processes due to faults in distribution networks were implemented in a computational system. Case studies in real distribution networks show advantages and disadvantages of each method. In order to determine losses in customer processes, some literature results are taken as a basis to determine the total planning costs, that include the parcels corresponding to the reinforcement capital, power losses and power quality costs, that consider customer interruptions and disruptions due to voltage sags and swells.

Reconstructed tomographic image resolution of small animal PET imaging systems is improving with advances in radiation detector development. However the trend towards higher resolution systems has come with an increase in price and system complexity. Recent developments in the area of solid-state photomultiplication devices like silicon photomultiplier arrays (SPMA) are creating opportunities for new high performance tools for PET scanner design. Imaging of excised small animal organs and tissues has been used as part of post-mortem studies in order to gain detailed, high-resolution anatomical information on sacrificed animals. However, this kind of ex-vivo specimen imaging has largely been limited to ultra-high resolution μCT. The inherent limitations to PET resolution have, to date, excluded PET imaging from these ex-vivo imaging studies. In this work, we leverage the diminishing physical size of current generation SPMA designs to create a very small, simple, and high-resolution prototype detector system targeting ex-vivo tomographic imaging of small animal organs and tissues. We investigate sensitivity, spatial resolution, and the reconstructed image quality of a prototype small animal PET scanner designed specifically for imaging of excised murine tissue and organs. We aim to demonstrate that a cost-effective silicon photomultiplier (SiPM) array based design with thin crystals (2 mm) to minimize depth of interaction errors might be able to achieve sub-millimeter resolution. We hypothesize that the substantial decrease in sensitivity associated with the thin crystals can be compensated for with increased solid angle detection, longer acquisitions, higher activity and wider acceptance energy windows (due to minimal scatter from excised organs). The constructed system has a functional field of view (FoV) of 40 mm diameter, which is adequate for most small animal specimen studies. We perform both analytical (3D-FBP) and iterative (ML-EM) methods in order to reconstruct tomographic images. Results demonstrate good agreement between the simulation and the prototype. Our detector system with pixelated crystals is able to separate small objects as close as 1.25 mm apart, whereas spatial resolution converges to the theoretical limit of 1.6 mm (half the size of the smallest detecting element), which is to comparable to the spatial resolution of the existing commercial small animal PET systems. Better system spatial resolution is achievable with new generation SiPM detector boards with 1 mm x 1 mm cell dimensions. We demonstrate through Monte Carlo simulations that it is possible to achieve sub-millimeter spatial image resolution (0.7 mm for our scanner) in complex objects using monolithic crystals and exploiting the light-sharing mechanism among the neighboring detector cells. Results also suggest that scanner (or object) rotation minimizes artifacts arising from poor angular sampling, which is even more significant in smaller PET designs as the gaps between the sensitive regions of the detector have a more exaggerated effect on the overall reconstructed image quality when the design is more compact. Sensitivity of the system, on the other hand, can be doubled by adding two additional detector heads resulting in a, fully closed, 4π geometry.

This study serves as a first step towards a comprehensive hazard assessment for the San Francisco volcanic field in northern Arizona, which can be applied to local response plans and educational initiatives. The primary goal of this thesis is to resolve the conditional probability that, given a lava flow effusing from a new vent in the San Francisco volcanic field, it will inundate the city limits of Flagstaff. The spatial distribution of vents within the San Francisco volcanic field was analyzed in order to execute a lava flow simulation to determine the inundation hazard to Flagstaff. The Gaussian kernel function for estimating spatial density showed that there is a 99% chance that a future vent will be located within a 3.6 x 109 m2 area about 20 kilometers north of Flagstaff. This area contains the location of the most recent eruption at Sunset Crater, suggesting that the model is a good predictor of future vent locations. A Monte Carlo analysis of potential vent locations (N = 7,769) showed that 3.5% of simulated vents generated lava flows that inundated Flagstaff, and 1.1% of simulated vents were located within the city limits. Based on the average recurrence rate of vents formed during the Brunhes chronozone, the aggregate probability of lava flow inundation in Flagstaff is 1.1 x 10-5 per year. This suggests that there is a need for the city to plan for lava flows and associated hazards, especially forest fires. Even though it is unlikely that the city will ever have to utilize such a plan, it is imperative that thorough mitigation and response plans are established now-- before the onset of renewed volcanic activity.

Despite nuclear fission prominence in nuclear physics, there are still several fundamental open questions about this process. One uncertainty is the energy distribution of neutrons emitted immediately after fission. In particular the relative energy distribution of neutrons above 8~MeV has been difficult to measure. This experiment measured the prompt neutron energy spectrum of n+235U from 3-10~MeV. The measurement took place at Los Alamos National Laboratory (LANL) and used a double time-of-flight technique to measure both the beam and fission neutron kinetic energies. Fission event timing was measured with a parallel plate avalanche counter. The fission neutron time-of-flight was measured with 2~m long plastic scintillation detectors. By combining the time-of-flight information with a known flight path the kinetic energy spectrum of neutrons was measured. To eliminate backgrounds various time-of-flight and energy cuts were imposed and an accidental coincidence background was subtracted. An MCNP simulation, including the 2~m neutron detector geometry, was done using the Madland and Nix model as the input energy distribution for the simulated neutrons. Finally, the measured energy spectrum was compared with the MCNP simulated n+235U fission neutron energy spectrum.

Living tissue consists primarily of cells and extracellular matrix. Cells perform functions, communicate, respire and remodel extracellular matrix. Likewise, diffusive chemical conditions and extracellular matrix exhibit their own effects on cellular and intracellular processes, depending on the consistency of the matrix and phenotype of the cell. These interactions produce the emergent phenomena of tissue function, repair and morphology. Computational modeling seeks to quantify these processes for the purposes of fundamental study and predictive capability in various applications, including wound healing, tumor vascularization and biofabrication of living tissue. Hybrid kinetic Monte Carlo models are well known to be capable of predicting observed behaviors like cell sorting and spheroid fusion due to differential adhesion and energy minimization. However, no hybrid model sufficiently provides a formal treatment of full cell, chemical and matrix interactivity in a dynamic environment, including heterogeneous matrix conditions, advecting materials, and intracellular processes. In this work, hybrid kinetic Monte Carlo models are developed to describe full interactivity of cells, soluble signals and insoluble signals in a complex, dynamic microenvironment at the cellular level. Modeling of intracellular chemical dynamics and effects on the cellular state is developed as stochastic processes, and cell perform metabolic and matrix remodeling activities. Computational models of select \textit{in vivo} and \textit{in vitro} phenomena are developed and simulated, showing the ability to simulate new phenomena concerning cell viability, growth dynamics, highly heterogeneous cellular distributions, and complex tissue structures resulting from phenomena like intercellular signaling, matrix remodeling, and cell polarity.