Anregungsinduzierte Ladungstransferprozesse gemischtvalenter Verbindungen in einem, bzw. zwei Vibrationsfreiheitsgraden werden mithilfe vibronischer Modellsysteme untersucht. Anhand transienter und linearer Absorptionsspektren werden die berechneten mit experimentell bestimmten Daten verglichen. Eine detailliertere theoretische Analyse erfolgt unter den Gesichtspunkten der Populations- und Wellenpaketdynamik. Darüber hinaus wird der Prozess der Exziton-Exziton-Annihilierung mithilfe eines elektronischen Modellsystems untersucht. Zu diesem Zweck werden, zusätzlich zu den oben genannten Methoden, spektroskopische Signale unterschiedlicher Emissionsrichtungen zum Vergleich herangezogen. / Optically induced charge transfer processes of mixed-valence compounds in one or two vibrational degrees of freedom respectively are studied using vibronic model systems. Calculated and experimentally determined data are compared based on transient as well as linear absorptions spectra. By means of population and wave-packet dynamics a more detailed theoretical analysis is performed. Furthermore, the process of exciton-exciton annihilation is studied using an electronic model system. Therefore, in addition to the methods mentioned above, spectroscopic signals in different directions of emission are compared.

A Monte Carlo model is developed for predicting electrical conductivity of carbon nanofiber composite materials. The conductive nanofibers are models as both 2D and 3D network of finite sites that are randomly distributed. The percolation behavior of the network is studied using the Monte Carlo method, which leads to the determination of the percolation threshold. The effect of the nanofiber aspect ratio on the critical nanofiber volume rate is investigated in the current model, each of the nanofibers needs five independent geometrical parameters (i.e., three coordinates in space and two orientation angles) for its identification. There are three controlling parameters for each nanofiber, which includes the nanofiber length, the nanofiber diameter, and the nanofiber aspect ratio. The simulation results reveal a relationship between the fiber aspect ratio and the percolation threshold: the higher the aspect ratio, the lower the threshold. With the simulation results obtained from the Monte Carlo model, the effective electrical conductivity of the composite is then determined by assuming the conductivity is proportional to the ratio of the number of nanofibers forming the largest cluster to the total number of nanofibers. The numerical results indicate that as the volume rate reaches a critical value, the conductivity starts to rise sharply. These obtained simulation results agree fairly with experimental and numerical data published earlier by others. In addition, we investigate the convergence of the current percolation model. We also find the tunneling effect does not affect the critical volume rate greatly. We propose that the percolation model is not scalable as well.

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Page iii not included in the thesis and therefore, not included in the page count. / <p> In recent years, some efficient methods have been developed for calculating derivative price sensitivities, or the Greeks, using Monte Carlo simulation. However, the slow convergence, especially for discontinuous payoff functions, is well known for Monte Carlo simulation. In this project, we investigate the Malliavin calculus and its application in computation of the Greeks. Malliavin calculus and Wiener Chaos theory are introduced. The theoretical framework of the Malliavin weighted scheme of computation of the Greeks is explored in details, and the numerical implementation of the one-dimensional case and an example of the two-dimensional case are presented. Finally, the results are compared with those of finite difference scheme.</p> / Thesis / Master of Science (MSc)

We study the phase diagram of an interacting lattice gas of two species of particles and holes, driven out of equilibrium by a local hopping bias (denoted by `E'). Particles interact by excluded volume and nearest-neighbor attractions. We present a detailed Monte Carlo investigation of the phase diagram. Three phases are found, with a homogenous phase at high temperatures and two distinct ordered phases at lower temperatures. Which ordered phase is observed depends on the parameter f, which controls the ratio of the two types of particles. At small f, there is nearly a single species, and a transition is observed into a KLS-type ordered phase. At larger f, the minority species are sufficiently dense to form a transverse blockage, and a sequence of two transitions are observed as the temperature is lowered. First, a continuous boundary is crossed into an SHZ-type ordered phase, then at a lower temperature a first-order boundary is crossed into the KLS-type ordered phase. At some critical value of f is a bicritical point, where the first-order line branches from the two continuous boundaries. We also consider correlations in the homogenous phase, by constructing a continuum description and comparing to the results of simulations. Long range correlations are present in both the theoretical results and the simulations, though certain details of the theory do not fit the observations very well. Finally, we examine the beahvior of three-point correlations in the single-species (KLS) limit. Nontrivial three-point correlations are directly related to the nonzero bias E. We therefore consider the behavior of the three-point correlations as a function of E. We find that the three-point signal saturates very rapidly with E. There are some difficulties interpreting the data at small E. / Ph. D.

The purpose of this study is to modify an existing static analytical model developed for a Re-circulating Aquaculture Systems through incorporation of risk considerations to evaluate the economic viability of the system. In addition the objective of this analysis is to provide a well documented risk based analytical system so that individuals (investors/lenders) can use it to tailor the analysis to their own investment decisions—that is to collect the input data, run the model, and interpret the results. The Aquaculture Economic Cost Model (AECM) was developed by Dr. Charles Coale, Jr. and others from the department of Agricultural and Applied Economics at Virginia Tech. The AECM is a spreadsheet model that was developed to help re-circulating aquaculture producers make strategic business decisions. The model can be used by potential producers interested in investing in re-circulating aquaculture through development of a financial analysis that in turn will help them obtain funding for the enterprise. The model is also useful for current producers who want to isolate inefficient aspects of their operation. AECM model consists of three major sections which include the Data Entry, Calculations and Analysis. The first section requires that the producer conducts background research about their operation to ensure accurate calculation and analysis. The calculation section provides a great deal of information about the operation's finances, while the analysis section provides information about the operation's financial stability. While the AECM is a powerful model, it is based on single, usually mean, values for prices, costs, and input and output quantities. However, market, financial and production uncertainties result in fluctuating prices, costs and yields. An individual who is making management decisions for a re-circulating aquaculture system will be faced with some or all of these uncertainties. By adding simulation to the AECM model to account for these uncertainties individuals will be able to make better management decisions. Information of the varying likelihoods or probabilities of achieving profits will be of crucial interest to individuals who plan on entering into or modifying an existing aquaculture system. Risks associated with six variables were examined in this paper: feed cost, feed conversion, mortality rate, capital interest rate, final weight, and output price. Data for the Interest Rate and output price were obtained from the Federal Reserve System and NMFS website respectively. Expert opinion was the source of data for the other variables. After probability distributions were applied to the random variables to account for the uncertainty the model was simulated for ten thousand iterations to obtain expected returns for three years in advance that the model calculates an income statement. In addition to that, sensitivity analyses were carried out in order to inform the producer which factors are contributing the most to the profitability of the operation. In this way the producer will have a better idea as to which aspects of the operation to monitor closely and consider modifying. The analysis shows that the mean income for the three years will be negative and thus the business would be losing money. The simulated mean net incomes were: -$216,905, -$53,689, -$53,111 for year1 through year3 respectively. Sensitivity analysis confirmed that output price is by far the most significant input that makes the overall bottom line to fluctuate most. Output price was on top of the list for all the three years analyzed in this study. Feed cost and Feed conversion were the next most significant inputs. The other inputs were also significant in explaining the fluctuation of the bottom line; however both their regression and correlation coefficients were small. / Master of Science