Thesis (M.S.)--Brigham Young University, Department of Mechanical Engineering, 2004. / Includes bibliographical references (p. 259-261).

X-ray fluorescence is a well-understood phenomenon in which irradiation of certain materials, such as gold, with x-rays causes the emission of secondary x-rays with characteristic energies. By performing computed tomography using these fluorescence x-rays, the material of interest can be imaged inside an object. Our research group has already demonstrated that x-ray fluorescence computed tomography (XFCT) imaging using a typical 110 kVp microfocus x-ray tube is feasible for a small animal-sized object containing a distribution of a solution of low concentration gold nanoparticles. The primary goal of this thesis work was to study the effect of source x-ray energy spectra on gold fluorescence detection using the XFCT system. A computational approach using the Monte Carlo method was used. First, a computational model was created using the Monte Carlo N-Particle (MCNP) transport code based on the experimental setup of the pre-existing XFCT system. Simulations were run to verify the validity of the MCNP model as an accurate representation of the actual system by means of comparison with experimentally-obtained data. Finally, the model was used for further purely computational work. In the MCNP model, the source spectrum was changed to reflect several theoretical and experimentally obtained options. The effect of these changes on gold fluorescence production was documented and quantified using the signal-to-background ratio and other qualitative measures. The results from this work provided clues on how to improve the detection of fluorescence photons from gold nanoparticle-loaded objects using the XFCT system. This will benefit future research on the development of the XFCT system in the context of making it more feasible for gold nanoparticle-based preclinical molecular imaging applications.

We consider the parallelization of Monte Carlo algorithms for analyzing numerical models of charge transport used in semiconductor device physics. Parallel algorithms for the standard k-space Monte Carlo simulation of a three band model of bulk GaAs on hypercube multicomputers are first presented. This Monte Carlo model includes scattering due to polar-optical, intervalley, and acoustic phonons, as well as electron-electron scattering. The k-space Monte Carlo program, excluding electron-electron scattering, is then extended to simulate a semiconductor device by the addition of the real space position of each simulated particle and the assignment of particle charge, using a cloud in cell scheme, to solve the Poisson's equation with particle dynamics. Techniques for effectively partitioning this device so as to balance the computational load while minimizing the communication overhead are discussed. Approaches for improving the efficiency of the parallel algorithm, either by dynamically balancing of load or by employing the usual techniques for enhancing rare events in Monte Carlo simulations are also considered. The parallel algorithms were implemented on a 64-node NCUBE multiprocessor and test results were generated to validate the parallel k-space, as well as the device simulation programs. Timing measurements were also made to study the variation of speedups as both the problem size and number of processors are varied. The effective exploitation of the computational power of message passing multiprocessors requires the efficient mapping of parallel programs onto processors so as to balance the computational load while minimizing the communication overhead between processors. A lower bound for this communication volume when mapping arbitrary task graphs onto distributed processor systems is derived. For a K processor system this lower bound can be computed from the K (possibly) largest eigenvalues of the adjacency matrix of the task graph and the eigenvalues of the adjacency matrix of the processor graph. We also derive the eigenvalues of the adjacency matrix of the processor graph for a hypercube and give test results comparing the lower bound for the communication volume with the values given by a heuristic algorithm for a number of task graphs. / Graduation date: 1992

The implicit Monte Carlo (IMC) method [16] for radiative transfer, developed in 1971, provides numerical solutions to the tightly-coupled, highly-nonlinear radiative heat transfer equations in many physical situations. Despite its popularity, there are instances of overheating in the solution for particular choices of time steps and spatial grid sizes. To prevent overheating, conditions on teh time step size Δt have been sought to ensure that the implicit Monte Carlo (IMC) equations satisfy a maximum principle. Most recently, a discrete maximum principle (DMP) for teh IMC equations has been developed [32] that predicts the necessary time step size for boundedness given the spatial grid size. Predictions given by this DMP assumed equilibrium thermal initial conditions, was developed using pseudo-analytic and symbolic algebra tools that are computationally expensive, has only been applied to one-dimensional Marshak wave problems, and has not considered the evolution of the DMP predictions over multiple time steps. These limitations restrict the utility of the DMP predictions. We extend the DMP derivation to overcome these limitations and provide an algorithm that can be introduced into IMC codes with minimal impact on simulation CPU time. This extended DMP effectively treats non-equilibrium thermal initial conditions, decreases calculation time by using multigroup approximations in frequency, considers multiple spatial dimensions with an arbitrary number of neighboring sources, and overcomes inherent difficulties for the DMP in time-dependent problems. Disequilibrium in the initial conditions is introduced through a redefinition of existing terms from [32] to different radiation and material temperatures on the first time step. This results in a limiting DMP inequality similar in form to the original. Multifrequency approximations are then applied by assuming separation of variables. Energy deposition from multiple sources is assumed to follow linear superposition and the DMP from [32] is re-derived to incorporate multiple incident sources of energy in multiple dimensions. Lastly, an inherent flaw in the DMP resulting in poor predictions when temperature varies slowly over a region is overcome by developing a threshold temperature difference, above which the DMP operates. We have numerically implemented these improvements and validated the results against IMC solutions, showing the predictive capacity of the more general DMP algorithm. We find the disequlibrium conditions to be properly incorporated into the DMP, and multifrequency approximations to be accurate over a large range of time step and spatial grid sizes. The linear superposition assumption is generally very accurate, but infrequently leads to DMP predictions which are not conservative. We also demonstrate that the temperature difference threshold prevents inaccurate predictions by the DMP while preserving its functionality. / Graduation date: 2013

University of Macau / Faculty of Science and Technology / Department of Mathematics

Of great benefit, but not limited to seafloor mineral exploration, is a technique that fairly rapidly determines the composition of a drilled vibracore (in a time comparable to the time involved in obtaining the core). The rapid assessment is desired to predict whether a given region warrants further exploration by coring. A proposed monitoring system, based on neutron capture gamma ray analysis, consists of a container tank filled with water and tubular extensions that house a Cf-252 neutron source and a detector positioned within the tank. The core sample is passed through the system in stop and count steps. The net count rates, due to "signature" capture gamma rays from neutron capture in elements in the core sample, are proportional to the amount of the element responsible for emitting the capture gamma ray. The proposed system was modeled and simulated by the Monte Carlo method to predict the relationship between the response of the detector and the elemental concentrations within the sample. Accurate and detailed treatment of neutron transport and gamma ray production and attenuation within the system were employed not only to predict the relationship of the photopeak responses with respect to elemental concentrations, but also to permit investigation of the design parameters and structural material changes in the system. The developed Monte Carlo code utilizes a variety of variance reduction techniques, such as implicit absorption with Russian Roulette and deterministic production of the gamma rays of interest, along with a form of correlated sampling to predict simultaneously the responses over a range of interest of the elemental concentrations. The predicted results were compared with predictions obtained from a well established general purpose Monte Carlo code (MCNP). / Graduation date: 1990

A self-consistent, full-band, electrothermal ensemble Monte Carlo device simulation tool has been developed. It is used to study charge transport in bulk GaN, and to design, analyze, and improve the performance of AlGaN/GaN high electron mobility transistors (HEMTs) and avalanche photodiodes (APDs). Studies of electron transport in bulk GaN show that both peak electron velocity and saturated electron velocity are higher for transport in the basal plane than along the c-axis. Study of the transient electron velocity also shows a clear transit-time advantage for electron devices exploiting charge transport perpendicular to the c-axis. The Monte Carlo simulator also enables unique studies of transport under the influence of high free carrier densities but with low doping density, which is the mode of transport in AlGaN/GaN HEMTs. Studies of isothermal charge transport in AlGaN/GaN HEMTs operating at high gate bias show a drain current droop with increasing drain-source bias. The cause of the droop is investigated and a design utilizing source- or gate-connected field plate is demonstrated to eliminate the drain current droop. Electrothermal aspects of charge transport in AlGaN/GaN HEMTs are also investigated, and the influence of non-equilibrium acoustic and optical phonons is quantified. The calculated spatial distribution of non-equilibrium phonon population reveals a hot spot in the channel that is localized at low drain-source bias, but expands towards the drain at higher bias, significantly degrading channel mobility. Next, Geiger mode operation of wurtzite GaN-based homojunction APDs is investigated. The influences of dopant profile, active region thickness, and optical absorption profile on single photon detection efficiency (SPDE) are quantified. Simulations of linear mode gain as a function of multiplication region thickness and doping profile reveal that weakly n-type active regions may be exploited to achieve higher avalanche gain, without penalty to either applied bias or active region thickness. A separate absorption and multiplication APD (SAM-APD) utilizing a AlGaN/GaN heterojunction is also investigated. The presence of strong piezo-electric and spontaneous polarization charges at the heterojunction enables favorable electric field profile in the device to reduce dark current, improve excess noise factor, improve quantum efficiency, and improve breakdown probability. To maximize SPDE, a new device structure with a buried absorber is proposed and improved SPDE is demonstrated. Lastly, a new approach for the direct generation of self-sustaining millimeter-wave oscillations is proposed. In contrast to Gunn diodes, which exploit a bulk-like active region, periodic oscillation is achieved in the proposed structures through the creation, propagation and collection of traveling dipole domains supported by fixed polarization charge and the associated two-dimensional electron gas along the plane of a polar heterojunction. Numerical simulation of induced oscillations in a simple triode structure commonly used for AlGaN/GaN HEMTs reveals two distinct modes of self-sustaining millimeter-wave oscillation.

Since the advent of nanoscale material based electronic devices, there has been a considerable interest in exploring carbon nanotubes from fundamental science and technological perspectives. In carbon nanotubes, the atoms form a cylindrical structure with a diameter of the order 1nm. The length of the nanotubes can extend up to several hundred micrometers. Carbon nanotubes exhibit a variety of intriguing electronic properties such as semiconducting and metallic behaviour, due to the quantum confinement of the electrons in the circumferential direction. Much of the study dedicated to describe the behaviour of carbon nanotube-based devices assumes for simplicity the nanotube to be a ballistic material. However, in reality the phonon scattering mechanism exists also in nanotubes, of course, and can generally not be neglected, except in very short nanotubes. In this work, we focus attention on exploring the steady-state electron transport properties of semiconducting single-walled carbon nanotubes, including both phonon scattering and defect (vacancy) scattering, using the semi-classical bulk single electron Monte Carlo method.   The electron energy dispersion relations are obtained by applying the zone folding technique to the dispersion relations of graphene, which are calculated using the tight-binding description. The vibrational modes in the carbon nanotubes are studied using a fourth nearest-neighbour force constant model. Both the electron-phonon and the electron-defect interactions are formulated within the tight-binding framework, and their corresponding scattering rates are computed and analyzed. In particular, the dependence of the phonon scattering rate and the defect scattering rate on the diameter of the nanotube, on temperature and on electron energy is studied. It is shown that the differences observed in the scattering rate between different nanotubes mainly stem from the differences in their band structure.   A bulk single electron Monte Carlo simulator was developed to study the electron transport in semiconducting zigzag carbon nanotubes. As a first step, we included only electron-phonon scattering, neglecting all other possible scattering mechanisms. With this scattering mechanism, the steady-state drift velocity and the mobility for the nanotubes (8,0), (10,0), (11,0), (13,0) and (25,0) were calculated as functions of the electric-field strength and lattice temperature, and the results are presented and analysed here. The dependence of the mobility on the lattice temperature can be clearly seen at low electric-field strengths. At such electric-field strengths, the scattering is almost entirely due to acoustic phonons, whereas at high electric-field strengths optical phonon emission processes dominate. It is shown that the saturation of the steady-state drift velocity at high electric-field strengths is due to the emission of high-energy optical phonons. The results indicate the presence of Negative differential resistance for some of the nanotubes considered in this work. The discrepancy found in the literature concerning the physical reason for the appearance of negative differential resistance is clarified, and a new explanation is proposed. It is also observed that the backward scattering is dominant over the forward scattering at high electric-field strengths.                                                                                   We then included also defect scattering, actually electron-vacancy scattering, for the nanotubes (10,0) and (13,0). The steady-state drift velocities for these nanotubes are calculated as functions of the density of vacancies, electric-field strength and the lattice temperature, using three different vacancy concentrations. The results indicate the presence of Negative differential resistance at very low concentration of defects, and how this feature may depend on the concentration of defects. The dependence of the steady-state drift velocity on the concentration of defect and the lattice temperature is discussed. The electron distribution functions for different temperatures and electric field strengths are also calculated and investigated for all the semiconducting nanotubes considered here. In particular, a steep barrier found in the electron distribution function is attributed to the emission of high energy optical phonons.

A novel multiscale approach is introduced for determining the thermal conductivity of polymer nanocomposites (PNCs) reinforced with single-walled carbon nanotubes (SWCNTs), which accounts for their intrinsic uncertainties associated with dispersion, distribution, and morphology. Heterogeneities in PNCs on nanoscale are identified and quantified in a statistical sense, for the calculation of effective local properties. A finite element method computes the overall macroscale properties of PNCs in conjunction with the Monte Carlo simulations. This Monte Carlo Finite Element Approach (MCFEA) allows for acquiring the randomness in spatial distribution of the nanotubes throughout the composite. Furthermore, the proposed MCFEA utilizes the nanotube content, orientation, aspect ratio and diameter inferred from their statistical information. Local SWCNT volume or weight fractions are assigned to the finite elements (FEs), based on various spatial probability distributions. Multi-phase homogenization techniques are applied to each FE to calculate the local thermal conductivities. Then, the Monte Carlo simulations provide the statistics on the overall thermal conductivity of the PNCs. Subsequently, dispersion characteristics of the nanotubes are assessed by incorporating nanotube agglomerates. In this regard, a multi-phase homogenization method is developed for enhanced accuracy and effectiveness. The effect of the nanotube orientation in a polymer is studied for the cases where the SWCNTs are randomly oriented as well as longitudinally aligned. The influence of voids existing in the polymer is investigated on the thermal conductivity, to capture the uncertainties in PNCs more extensively. Further, a unique damage evaluation model is proposed to assess the degradation of PNCs when subjected to thermal cycling. The growth in void content is represented with a Weibull-based equation, to quantify the deterioration of the thermal and mechanical properties of PNCs under thermal fatigue. In addition, the MCFEA considers the interface resistance of the carbon nanotubes as one of the key factors in the thermal conductivity of nanocomposites. Parametric studies are performed comprehensively. The numerical results obtained are compared with available analytical techniques at hand and with the data from pertinent independent experimental studies. It is found that the proposed MCFEA is capable of estimating the thermal conductivity with good accuracy.

Target tracking is a broad subject area extensively studied in many engineering disciplines. In this thesis, target tracking implies the temporal estimation of target features such as the target's direction-of-arrival (DOA), the target's boundary pixels in a sequence of images, and/or the target's position in space. For multiple target tracking, we have introduced a new motion model that incorporates an acceleration component along the heading direction of the target. We have also shown that the target motion parameters can be considered part of a more general feature set for target tracking, e.g., target frequencies, which may be unrelated to the target motion, can be used to improve the tracking performance. We have introduced an acoustic multiple-target tracker using a flexible observation model based on an image tracking approach by assuming that the DOA observations might be spurious and that some of the DOAs might be missing in the observation set. We have also addressed the acoustic calibration problem from sources of opportunity such as beacons or a moving source. We have derived and compared several calibration methods for the case where the node can hear a moving source whose position can be reported back to the node. The particle filter, as a recursive algorithm, requires an initialization phase prior to tracking a state vector. The Metropolis-Hastings (MH) algorithm has been used for sampling from intractable multivariate target distributions and is well suited for the initialization problem. Since the particle filter only needs samples around the mode, we have modified the MH algorithm to generate samples distributed around the modes of the target posterior. By simulations, we show that this mode hungry algorithm converges an order of magnitude faster than the original MH scheme. Finally, we have developed a general framework for the joint state-space tracking problem. A proposal strategy for joint state-space tracking using the particle filters is defined by carefully placing the random support of the joint filter in the region where the final posterior is likely to lie. Computer simulations demonstrate improved performance and robustness of the joint state-space when using the new particle proposal strategy.