In recent years there have been many efforts to develop and expand the ability of mathematical models capable of describing polymerization systems. Models can provide a key competitive advantage for the industry and research in terms of production and technology development. As new resins are continuously produced to meet the requirement of final applications and processability, it is imperative to pursue strong polymer characterization with special attention to detailed analysis of polymer microstructure. The microstructure of polyolefin is defined by its distribution of molecular weight, chemical composition, branching topology, and stereoregularity. <br /><br /> In this work, a Monte Carlo simulation model was developed to describe the polymerization mechanisms of olefin homopolymerization and copolymerization using single-site coordination catalyst. The mathematical model is meant to describe molecular weight and chemical composition distribution in copolymerization system. More specifically, this research work gives a detailed study of the molecular structure for ethylene- alfa-olefin copolymer. <br /><br /> The chemical and physical properties of copolymers are influenced not only by their average composition, but also by the monomer sequence distribution along the polymer chains. Predicting the molecular weight and comonomer distributions can lead to a better understanding of the possible morphology in solid stated because they are considered to be the main structural parameters that affect the crystallinity of polymeric materials. As a consequence, final physical properties such as the tensile properties of a copolymer could be controlled by the ratio of crystalline species in the polymer. <br /><br /> This work is considered to be a useful tool that enables us to understand and explore specific polymerization catalytic system. Being able to describe the short chain branching and the monomer sequence distribution as a function of chain length enables us to have a better control over semi-batch polymerization reactors.

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Abstract In this study, we employed the Monte Carlo simulation method to investigate the q-state coupled XY model based on the Landau free energy of couple hexatic order and herringbone order proposed by Bruinsma and Aeppli. On two-dimensional triangular lattices simulation results reveal that the q-state coupled XY model will generate a q-state clock phase transition and a XY transition. The unique generated q-state clock phase transition and XY transition will couple in some coupling parameter domain. The novel coupled transitions behavior agree with the phase transition of some kinds of liquid crystal. For example, the three-state Potts phase transition generated by a 3-state coupled XY model and the Sm-A ¡÷Hex-B transition of free ¡V standing two layers liquid crystal are matched. Their heat capacity anomaly is similar and the heat capacity exponent is both closed to £\¡Ü0.3. We also investigated the system of coupled ferromagnetic order and antiferromagnetic order. Adapted the positive coupling parameter on the Hamiltonian of 3-state coupled XY model, the simulation results reveal that the system generate an antiferromagnetic three-state Potts transition. In some parameter domain the antiferromagnetic three-state Potts transition and XY transition are coupled, and become a novel transition. The novel transition may explain the Sm-A ¡÷Hex-B transition of some kinds of liquid crystal which lack herringbone order.

Quantum well infrared photodetectors (QWIPs) have recently emerged as a potential alternative to the conventional detectors utilizing low bandgap semiconductors for infrared applications. There has been a considerable amount of experimental and theoretical work towards a better understanding of QWIP operation, whereas there is a lack of knowledge on the underlying physics. This work provides a better understanding of QWIP operation and underlying physics through particle simulations using the ensemble Monte Carlo method. The simulator incorporates Gamma, L, and X valleys of conduction band as well as the size quantization in the quantum wells. In the course of this work, the dependence of QWIP performance on different device parameters is investigated for the optimization of the QWIP structure. The simulations on AlGaAs/GaAs QWIPs with the typical Al mole fraction of 0.3 have shown that the L valley of the conduction band plays an important role in the electron capture. A detailed investigation of the important scattering mechanisms indicates that the capture of the electrons through the L valley quantum well (L-QW) affects the device performance significantly when Gamma and L valley separation is small. The characteristics of electron capture have been further investigated by repeating the simulations on QWIPs for quantum well widths of 36 and 44 &Aring / . The results suggest that the gain in the shorter well width device is considerably higher, which is attributed to the much longer lifetime of the photoexcited electrons as a result of lower capture probability (pc) in the device. The effects of the L-QW height on the QWIP characteristics have also been studied by artificially increasing this height from 63 to 95 meV in Al0.3Ga0.7As/GaAs QWIPs. The increase in the L valley (L-QW) height resulted in higher pc and lower gain due to high rate of capturing of these electrons when Gamma and L valley separation is small.

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Die Beschaffenheit metallischer Legierungsschmelzen hat einen entscheidenden Einfluss auf die Qualität der festen Legierung. Im Rahmen dieser Diplomarbeit wurde sich gezielt mit der Nahordnung in ternären Ag-Cu-Ge Legierungsschmelzen sowie der binären Randlegierungen beschäftigt. Dazu wurden die Legierungen mithilfe der Röntgendiffraktion untersucht. Zusätzlich wurden die erhaltenen experimentellen Ergebnisse durch Computersimulationen ergänzt und mit Modellrechnungen verglichen.

This dissertation focuses on the development of computational models and algorithms related to diffuse reflectance spectroscopy. Specifically, this work aims to advance diffuse reflectance spectroscopy to a technique that is capable of measuring depth dependent properties in tissue. First, we introduce the Monte Carlo lookup table (MCLUT) method for extracting optical properties from diffuse reflectance spectra. Next, we extend this method to a two-layer tissue geometry so that it can extract depth dependent properties in tissue. We then develop a computational model that relates photon sampling depth to optical properties and probe geometry. This model can be used to aid in design of application specific diffuse reflectance probes. In order to provide justification for using a two-layer model for extracting tissue properties, we show that the use of a one-layer model can lead to significant errors in the extracted optical properties. Lastly, we use our two-layer MCLUT model and a probe that was designed based on our sampling depth model to extract tissue properties from the skin of 80 subjects at 5 anatomical locations. The results agree with previously published values for skin properties and show that can diffuse reflectance spectroscopy can be used to measured depth dependent properties in tissue. / text

Water distribution system modeling can be used as a basis of planning and operation decisions. However, model accuracy and uncertainty will impact the model based decisions. Model prediction uncertainty results from uncertainty in model parameters that are determined through calibration or are based upon modeler judgment. The focus of this dissertation is the effect of uncertainties on water quality model estimates and calibration. The dissertation is centered around three journal articles and a technical note.In the first paper, the effect of parameter uncertainty on water quality in a distribution system under steady and unsteady conditions was analyzed by Monte Carlo simulation (MCS). Sources of uncertainties for water quality include decay coefficients, pipe diameter and roughness, and nodal spatial and temporal demands. The effect of individual parameter is discussed, as well as the combined effect of the parameters. It also describes the effect of flow patterns.A general calibration model is developed in the second paper for identifying wall decay coefficients. The problem is solved using the SFLA optimization algorithm that is coupled with hydraulic and water quality simulation models using the EPANET toolkit. The methodology is applied on two application networks. The study presents the effect of different field conditions such as the network with or without tanks, altering disinfectant injection policies, changing measurement locations, and varying the number of global wall decay coefficient on the estimated parameters. The numerical study also discusses whether the complexity of the system can be captured with fewer than the actual number of field parameters and if the number of the measurement locations is sufficient.The third paper conducts a study that considers a full calibration assessment for a water quality model in the distribution systems. The calibration process begins with estimating the the best fit wall decay coefficients. Next, the uncertainties involved with estimated parameters are calculated. Finally, the study assesses the model prediction uncertainties for critical demand conditions due to the parameter uncertainties. Various conditions are evaluated including the effects of different measurement errors and different measurement conditions on the uncertainty levels of estimated parameters as well as on the model predictions.Fourth paper presents study in which a booster disinfectant is introduced within a distribution system to maintain disinfectant residuals and avoid high dosages at water sources. Assuming that first order reaction kinetics apply to chlorine decay, an integer linear programming optimization problem is posed to booster locations and their injection rates. The formulation avoids long water quality simulations by adding constraints requiring the concentrations at the beginning and end of the design period to be the same. The optimization problem is divided into two levels. The upper level selects the booster locations using a genetic algorithm, if more than a few boosters are included, or enumeration, if the number of boosters and/or potential locations is relatively small. Given a set of boosters from the upper level, the lower level minimizes the chlorine mass to be injected to maintain required residuals. The approach is applied to the Brushy Plains system for alternative numbers of allowable boosters.