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.

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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.

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.

No / This paper proposes that the changes which occur in composition of the bed load during the transport of mixed-grain-size sediments are largely controlled by the distributions of critical entrainment shear stress for the various size fractions. This hypothesis is examined for a unimodal sediment mixture by calculating these distributions with a discrete particle model and using them in a probabilistic calculation of bed-load composition. The estimates of bed-load composition compare favorably with observations of fractional transport rates made in a laboratory flume for the same sediment, suggesting that the hypothesis is reasonable. The analysis provides additional insight, in terms of grain mechanics, into the processes that determine bed-load composition. These insights strongly suggest that better prediction methods will result from taking account of the variation of threshold within size fractions, something that most previous studies have neglected.

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