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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.

An advanced simulation code, LEEPS (Low Energy Electron Positron Simulation), has been adapted to simulation of electrons and positrons in liquid water for energies down to 50 eV. Different scattering parameters and results from simulations are compared with existing data in the literature.   Several programs including a subroutine package for simulation of secondary electrons created in binary like collisions have been developed in purpose of charting different characteristics of the energy deposition.   A toy model for DNA damage is presented as an example of how LEEPS possibly can be used for future investigation of cellular damage due to radiation.

Treatment–covariate interaction is often used in clinical trials to assess the homogeneity of treatment effects over these subgroups defined by a baseline covariate, which is frequently conducted after primary analysis including all patients is completed. When the endpoint is the time to an event, as in the cancer clinical trials, the Cox proportional hazard model with an interaction term has been used exclusively to test the significance of treatment-covariate interaction in oncology literature. But the proportional hazards assumption may not be satisfied by the data from clinical trials. Although there are several procedures proposed in statistical literature to assess the interaction based on a nonparametric measure of interaction or nonparametric models, some of these procedures do not take into the account of the nature of the data well, while some are very complicated which may have limited their applications in practice. In this thesis, a non-parametric procedure based on the smoothed estimate of Patel–Hoel measure is first derived to test the interaction between the treatment and a binary covariate with censored data. The theoretical distribution of the test statistic of the proposed procedure is derived. The proposed procedure is also evaluated through Monte-Carlo simulations and applications to data from a cancer clinical trial. Jackknifed versions of two test statistics based on nonparametric models are then derived by simplifying these test statistics and applying the jackknife method to estimate their variances. These jackknifed tests are also compared with the smoothed test and other related tests. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2011-09-27 11:09:28.449

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The LSO scintillator crystal commonly used in PET scanners contains a low level of intrinsic radioactivity due to a small amount of Lu-176. This is not usually a concern in routine scanning but can become an issue in small animal imaging, especially when imaging low tracer activity levels. Previously there had been no systematic validation of simulations of this activity; this thesis discusses the validation of a GATE model of intrinsic Lu-176 against results from a bench-top pair of detectors and a Siemens Inveon preclinical PET system. The simulation results matched those from the bench-top system very well, but did not agree as well with results from the complete Inveon system due to a drop-off in system sensitivity at low energies that was not modelled. With this validation the model can now be used with confidence to predict the effects of Lu-176 activity in future PET systems.