This dissertation presents the development and validation of the One Dimensional Turbulence (ODT) multiphase model in the Lagrangian reference frame. ODT is a stochastic model that captures the full range of length and time scales and provides statistical information on fine-scale turbulent-particle mixing and transport at low computational cost. The flow evolution is governed by a deterministic solution of the viscous processes and a stochastic representation of advection through stochastic domain mapping processes. The three algorithms for Lagrangian particle transport are presented within the context of the ODT approach. The Type-I and -C models consider the particle-eddy interaction as instantaneous and continuous change of the particle position and velocity, respectively. The Type-IC model combines the features of the Type-I and -C models. The models are applied to the multiphase flows in the homogeneous decaying turbulence and turbulent round jet. Particle dispersion, dispersion coefficients, and velocity statistics are predicted and compared with experimental data. The models accurately reproduces the experimental data sets and capture particle inertial effects and trajectory crossing effect. A new adjustable particle parameter is introduced into the ODT model, and sensitivity analysis is performed to facilitate parameter estimation and selection. A novel algorithm of the two-way momentum coupling between the particle and carrier phases is developed in the ODT multiphase model. Momentum exchange between the phases is accounted for through particle source terms in the viscous diffusion. The source term is implemented in eddy events through a new kernel transformation and an iterative procedure is required for eddy selection. This model is applied to a particle-laden turbulent jet flow, and simulation results are compared with experimental measurements. The effect of particle addition on the velocities of the gas phase is investigated. The development of particle velocity and particle number distribution are illustrated. The simulation results indicate that the model qualitatively captures the turbulent modulation with the presence of difference particle classes with different solid loadings. The model is then extended to simulate temperature evolution of the particles in a nonisothermal hot jet, in which heat transfer between the particles and gas is considered. The flow is bounded by a wall on the one side of the domain. The simulations are performed over a range of particle inertia and thermal relaxation time scales and different initial particle locations. The present study investigates the post-blast-phase mixing between the particles, the environment that is intended to heat them up, and the ambient environment that dilutes the jet flow. The results indicate that the model can qualitatively predict the important particle statistics in jet flame.

For over 30 years, the Implicit Monte Carlo (IMC) method has been used to solve challenging problems in thermal radiative transfer. These problems are typically optically thick and di ffusive, as a consequence of the high degree of "pseudo-scattering" introduced to model the absorption and reemission of photons from a tightly-coupled, radiating material. IMC has several well-known features which could be improved: a) it can be prohibitively computationally expensive, b) it introduces statistical noise into the material and radiation temperatures, which may be problematic in multiphysics simulations, and c) under certain conditions, solutions can be unphysical and numerically unstable, in that they violate a maximum principle - IMC calculated temperatures can be greater than the maximum temperature used to drive the problem. We have developed a variant of IMC called "iterative thermal emission" IMC, which is designed to be more stable than IMC and have a reduced parameter space in which the maximum principle is violated. ITE IMC is a more implicit method version of the IMC in that it uses the information obtained from a series of IMC photon histories to improve the estimate for the end of time-step material temperature during a time step. A better estimate of the end of time-step material temperature allows for a more implicit estimate of other temperature dependent quantities: opacity, heat capacity, Fleck Factor (probability that a photon absorbed during a time step is not reemitted) and the Planckian emission source. The ITE IMC method is developed by using Taylor series expansions in material temperature in a similar manner as the IMC method. It can be implemented in a Monte Carlo computer code by running photon histories for several sub-steps in a given time-step and combining the resulting data in a thoughtful way. The ITE IMC method is then validated against 0-D and 1-D analytic solutions and compared with traditional IMC. We perform an in finite medium stability analysis of ITE IMC and show that it is slightly more numerically stable than traditional IMC. We find that significantly larger time-steps can be used with ITE IMC without violating the maximum principle, especially in problems with non-linear material properties. We also compare ITE IMC to IMC on a two-dimensional, orthogonal mesh, x-y geometry problem called the "crooked pipe" and show that our new method reproduces the IMC solution. The ITE IMC method yields results with larger variances; however, the accuracy of the solution is improved in comparison with IMC, for a given choice of spatial and temporal grid. / Graduation date: 2013

No description available.

Given a known signal and perfect knowledge of the environment there exist few detection and estimation problems that cannot be solved. Detection performance is limited by uncertainty in the signal, an imperfect model, uncertainty in environmental parameters, or noise. Complex environments such as the ocean acoustic waveguide and the human anatomy are difficult to model exactly as they can differ, change with time, or are difficult to measure. We address the uncertainty in the model or parameters by incorporating their possibilities in our detection algorithm. Noise in the signal is not so easily dismissed and we set out to provide cases in which what is frequently termed a nuisance parameter might increase detection performance. If the signal and the noise component originate from the same system then it might be reasonable to assume that the noise contains information about the system as well. Because of the negative effects of ionizing radiation it is of interest to maximize the amount of diagnostic information obtained from a single exposure. Scattered radiation is typically considered image degrading noise. However it is also dependent on the structure of the medium and can be estimated using stochastic simulation. We describe a novel Bayesian approach to signal detection that increases performance by including some of the characteristics of the scattered signal. This dissertation examines medical imaging problems specific to mammography. In order to model environmental uncertainty we have written software to produce realistic voxel phantoms of the breast. The software includes a novel algorithm for producing three dimensional distributions of fat and glandular tissue as well as a stochastic ductal branching model. The image produced by a radiographic system cannot be determined analytically since the interactions of particles are a random process. We have developed a particle transport software package to model a complete radiographic system including a realistic x-ray spectrum model, an arbitrary voxel-based medium, and an accurate material library. Novel features include an efficient voxel ray tracing algorithm that reflects the true statistics of the system as well as the ability to produce separable images of scattered and direct radiation. Similarly, the ocean environment includes a high degree of uncertainty. A pressure wave propagating through a channel produces a measurable collection of multipath arrivals. By modeling changes in the pressure wave front we can estimate the expected pattern that appears at a given location. For this purpose we have created an ocean acoustic ray tracing code that produces time-domain multipath arrival patterns for arbitrary 3-dimensional environments. This iterative algorithm is based on a generalized recursive ray acoustics algorithm. To produce a significant gain in computation speed we model the ocean channel as a linear, time invariant system. It differs from other ocean propagation codes in that it uses time as the dependent variable and can compute sound pressure levels along a ray path effectively measuring the spatial impulse response of the ocean medium. This dissertation also investigates Bayesian approaches to source localization in a 3-D uncertain ocean environment. A time-domain-based optimal a posteriori probability bistatic source localization method is presented. This algorithm uses a collection of acoustic time arrival patterns that have been propagated through a 3-D acoustic model as the observable data. These replica patterns are collected for a possible range of unknown environmental parameters. Receiver operating characteristics for a bistatic detection problem are presented using both simulated and measured data. / Dissertation

Beam dumps are installed at the experimental areas of the ELBE facility. Their purpose is to absorb the primary electron beam and the secondary radiation. The beam dump consists of a purified graphite core inside a water cooled stainless steel vessel. The radiation shield surrounding the beam dump will be designed individually for each experimental area. In this context, dose rate calculations were carried out to estimate the dose rate source term around the stainless steel vessel of the beam dump. Detailed Monte Carlo simulations were carried out using the code FLUKA. The energy dependent photon and neutron fluences and the equivalent dose rates were obtained near the surface of the cylindrical steel vessel for a beam current of 1 mA and energies of 20 MeV and 50 MeV.

No description available.

Doctor of Philosophy / Biological & Agricultural Engineering / Mark E. Casada / Ronaldo G. Maghirang / Wind erosion is an important problem in many locations, including the Great Plains, that needs to be controlled to protect soil and land resources. This research was conducted to assess the effectiveness of vegetation (specifically, standing vegetation and tree barriers) as controls for wind erosion. Specific objectives were to: (1) measure sand transport and abrasion on artificial standing vegetation, (2) determine porosity and drag of a single row of Osage orange (Maclura pomifera) barrier, (3) assess effectiveness of Osage orange barriers in reducing dust, (4) predict airflow through standing vegetation, and (5) predict airflow and particle collection through Osage orange barriers. Wind tunnel tests were conducted to measure wind speed profiles, relative abrasion energies, and sand discharge rates for bare sand and for two vegetation heights (150 and 220 mm) at various densities of vegetation. Results showed that vegetation density was directly related to threshold velocity and inversely related to sand discharge. The coefficient of abrasion was adversely affected by saltation discharge but did not depend on wind speed. Field tests measured the aerodynamic and optical porosities of Osage orange trees using wind profiles and image analysis, respectively, and an empirical relationship between the two porosities was derived. Vertical wind profiles were also used to estimate drag coefficients. Optical porosity correlated well with the drag coefficient. Field measurements also showed a row of Osage orange barrier resulted in particulate concentration reduction of 15 to 54% for PM2.5 and 23 to 65% for PM10. A computational fluid dynamics (CFD) software (OpenFOAM) was used to predict airflow in a wind tunnel with artificial standing vegetation. Predicted wind speeds differed slightly from the measured values, possibly due to oscillatory motions of the standing vegetation not accounted for in the CFD simulation. OpenFOAM was also used to simulate airflow and particle transport through a row of Osage orange barrier. Predicted and measured wind speeds agreed well. Measured dust concentration reduction at two points (upwind and downwind) were also similar to the predicted results.

Master of Science / Department of Mechanical and Nuclear Engineering / Mohammad H. Hosni / Millions of people travel by commercial aircraft each year. The close proximity of passengers aboard an airplane leads to one of the primary reasons that air quality in an aircraft cabin is of interest. In recent years there have been multiple reported instances of people contracting illnesses after being aboard an aircraft for an extended period of time. In order to better understand air quality in an aircraft cabin, an experimental study of particulate transport in a half cabin model of a Boeing 767 was performed. In the study, both 3[Mu]m and 10[Mu]m particles were tested separately by injecting them into the cabin through a vertical tube, 609.6 mm (24 in) above the floor, at a single location on the centerline of the half cabin test section. Resulting particulate concentrations were measured at five locations along the centerline of the half cabin test section. It was found that for the 3[Mu]m particles, the normalized concentration was about one for all of the locations except directly above the injection site. Therefore, the concentrations were approximately the same as the well-mixed concentration, where the well-mixed concentration is the concentration in the test cabin if the test cabin is uniformly mixed. For the same test conditions, the normalized concentrations for the 10[Mu]m particles were well below one, around 0.1. Several more concentration measurements using the 10[Mu]m particles were taken at the same five locations, both on and off the centerline, and for different particle injection and cabin pressure conditions. The concentration results using a diffuser cone to inject the 10[Mu]m particles into the test cabin and a neutral cabin pressure were higher than the results found using the straight injection tube, but they were not very repeatable. After pressurizing the cabin to slightly above ambient pressure and using the diffuser cone, the resulting average normalized particle concentrations along the centerline were found to be between 0.4 and 1.5 and repeatable within the estimated measurement uncertainty. Therefore, it appears that the 3[Mu]m particles follow the airflow in the test cabin well, but it is not clear if the 10[Mu]m particles do as well.

Beam dumps are installed at the experimental areas of the ELBE facility. Their purpose is to absorb the primary electron beam and the secondary radiation. The beam dump consists of a purified graphite core inside a water cooled stainless steel vessel. The radiation shield surrounding the beam dump will be designed individually for each experimental area. In this context, dose rate calculations were carried out to estimate the dose rate source term around the stainless steel vessel of the beam dump. Detailed Monte Carlo simulations were carried out using the code FLUKA. The energy dependent photon and neutron fluences and the equivalent dose rates were obtained near the surface of the cylindrical steel vessel for a beam current of 1 mA and energies of 20 MeV and 50 MeV.

Hazards associated with air pollution motivate the search for technologies capable of monitoring individual exposure to gaseous pollutants and particulate matter (PM). A Low-cost Optical Particle Counter (OPC), costing less than 50 USD, is an example of such technologies. Currently, OPCs are widely used to measure the concentration of particle matter in ambient air. While these low-cost air quality sensors are widely available, the accuracy and precision of these devices is highly uncertain. Consequently, the purpose of this thesis is to present an analytical model of two generic, low-cost OPCs based on the Laws of Conservation of Mass, Momentum, and Energy. These models utilize Mie scattering theory and Computational Fluid Dynamics models to quantify uncertainty and accuracy in low-cost OPCs based first principles. Modeling results indicate that the measurement of forward-scattered light may dramatically increase the accuracy of low-cost OPCs. These results also indicate that careful attention must be placed on the design of sensor flow passages so as to most efficiently transport particles to the scattering volume where they may be detected. A combination of careful attention to photodetector placement in the forward scattering regime as well as efficient transport to the scattering volume may increase low-cost OPC accuracy by magnitudes of order.