Rather than emitting pulses, passive radar systems rely on illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, further scaling the RCS. A Rician likelihood model compares the scaled RCS of the illuminated aircraft with those of the potential targets. To improve the robustness of the result, the algorithm jointly optimizes over feasible orientation profiles and target types via dynamic programming.

An accurate and computationally fast method to generate nodal cross sections for the Pebble Bed Reactor (PBR) was presented. In this method, named Spectral History Correction (SHC), a set of fine group microscopic cross section libraries, pre-computed at specified depletion and moderation states, was coupled with the nodal nuclide densities and group bucklings to compute the new fine group spectrum for each node. The relevant fine group cross-section library was then recollapsed to the local broad group cross-section structure with this new fine group spectrum. This library set was tracked in terms of fuel isotopic densities. Fine group modulation factors (to correct the homogeneous flux for heterogeneous effects) and fission spectra were also stored with the cross section library. As the PBR simulation converges to a steady state fuel cycle, the initial nodal cross section library becomes inaccurate due to the burnup of the fuel and the neutron leakage into and out of the node. Because of the recirculation of discharged fuel pebbles with fresh fuel pebbles, a node can consist of a collection of pebbles at various burnup stages. To account for the nodal burnup, the microscopic cross sections were combined with nodal averaged atom densities to approximate the fine group macroscopic cross-sections for that node. These constructed, homogeneous macroscopic cross sections within the node were used to calculate a numerical solution for the fine group spectrum with B1 theory. This new fine spectrum was used to collapse the pre-computed microscopic cross section library to the broad group structure employed by the fuel cycle code. This SHC technique was developed and practically implemented as a subroutine within the PBR fuel cycle code PEBBED. The SHC subroutine was called to recalculate the broad group cross sections during the code convergence. The result was a fast method that compared favorably to the benchmark scheme of cross section calculation with the lattice cross-section generator for two PBR reactor designs.

IM-MS is a 2-D technique which provides separations based on ion shape (ion-neutral collision cross-section, Ω) and mass (m/z ratio). Ion structures can be deduced from the measured collision cross-section (Ωmeas) by calculating the collision cross-sections (Ωcalc) of candidates generated by molecular dynamics (MD) and compared with the experiment results. A database of Ωs for singly-charged peptide ions is presented. Standard proteins are digested using different enzymes (trypsin, chymotrypsin and pepsin), resulting in peptides that differ in amino acid composition. The majority (63%) of the peptide ion correlates well with the globular structures, but some exhibit Ωs that are significantly larger or smaller than the average correlation. Of the peptide ions having larger Ωs, approximately 71% are derived from trypsin digestion and most of the peptide ions that have smaller Ωs are derived from pepsin digestion (90%). We use computational simulations and clustering methods to assign backbone conformations for singly-protonated ions of the model peptide (NH2-Met-Ile-Phe-Ala-Gly-Ile-Lys-COOH) formed by both MALDI and ESI and compare the structures of MIFAGIK derivatives to test the ‘sensitivity’ of the cluster analysis method. Cluster analysis suggests that [MIFAGIK + H]+ ions formed by MALDI have a predominantly turn structure even though the low energy ions prefer partial helical conformers. Although the ions formed by ESI have Ωs that are different from those formed by MALDI, the results of cluster analysis indicate that the ions backbone structures are similar. Chemical modifications (N-acetyl, methylester, as well as addition of Boc or Fmoc groups) of MIFAGIK alter the distribution of various conformers, the most dramatic changes are observed for the [M + Na]+ ion, which show a strong preference for random coil conformers owing to the strong solvation by the backbone amide groups. Ωmeas of oligodeoxynucleotides in different length have been measured in both positive and negative modes. For a given molecular weight and charge state, Ωmeas of the oligodeoxynucleotide ions are smaller than those of the peptides, indicating their different packing efficiency. A novel generalized non-Boltzman sampling MD has been utilized to investigate the gas-phase ion conformations of dGGATC based on the free energy values. Theory predicts only one low-energy conformer for the zwitterionic form of dGGATC- while dGGATC+ ions have several stable conformers in both canonical and zwitterionic form in the gas phase, in good agreement with the experiment.

Thesis (M.S.)--East Carolina University, 2009. / Presented to the faculty of the Department of Physics. Advisor: Michael Dingfelder. Title from PDF t.p. (viewed Apr. 23, 2010). Includes bibliographical references.

Thesis--Ph. D., University of Hong Kong, 1983.

Not available / text

published_or_final_version / Physics / Doctoral / Doctor of Philosophy

<p>The objective of this project is to study the production of Li, Be and B isotopes emitted in the interaction of 12C with 12C at incident energies of 200 and 400 MeV.<br /> The energies of these produced fragments were measured with a detector telescope consisting of two silicon detectors at the incident energy of 200 MeV while a third silicon detector was added for the measurements at 400 MeV.</p>

This thesis addresses the problem of representing few group, homogenised neutron cross sections as a function of state parameters (e.g. burn-up, fuel and moderator temperature, etc.) that describe the conditions in the reactor. The problem is multi-dimensional and the cross section samples, required for building the representation, are the result of expensive transport calculations. At the same time, practical applications require high accuracy. The representation method must therefore be efficient in terms of the number of samples needed for constructing the representation, storage requirements and cross section reconstruction time. Sparse grid methods are proposed for constructing such an efficient representation. Approximation through quasi-regression as well as polynomial interpolation, both based on sparse grids, were investigated. These methods have built-in error estimation capabilities and methods for optimising the representation, and scale well with the number of state parameters. An anisotropic sparse grid integrator based on Clenshaw-Curtis quadrature was implemented, verified and coupled to a pre-existing cross section representation system. Some ways to improve the integrator’s performance were also explored. The sparse grid methods were used to construct cross section representations for various Light Water Reactor fuel assemblies. These reactors have different operating conditions, enrichments and state parameters and therefore pose different challenges to a representation method. Additionally, an example where the cross sections have a different group structure, and were calculated using a different transport code, was used to test the representation method. The built-in error measures were tested on independent, uniformly distributed, quasi-random sample points. In all the cases studied, interpolation proved to be more accurate than approximation for the same number of samples. The primary source of error was found to be the Xenon transient at the beginning of an element’s life (BOL). To address this, the domain was split along the burn-up dimension into “start-up” and “operating” representations. As an alternative, the Xenon concentration was set to its equilibrium value for the whole burn-up range. The representations were also improved by applying anisotropic sampling. It was concluded that interpolation on a sparse grid shows promise as a method for building a cross section representation of sufficient accuracy to be used for practical reactor calculations with a reasonable number of samples. / Thesis (MSc Engineering Sciences (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2013.

This thesis addresses the problem of representing few group, homogenised neutron cross sections as a function of state parameters (e.g. burn-up, fuel and moderator temperature, etc.) that describe the conditions in the reactor. The problem is multi-dimensional and the cross section samples, required for building the representation, are the result of expensive transport calculations. At the same time, practical applications require high accuracy. The representation method must therefore be efficient in terms of the number of samples needed for constructing the representation, storage requirements and cross section reconstruction time. Sparse grid methods are proposed for constructing such an efficient representation. Approximation through quasi-regression as well as polynomial interpolation, both based on sparse grids, were investigated. These methods have built-in error estimation capabilities and methods for optimising the representation, and scale well with the number of state parameters. An anisotropic sparse grid integrator based on Clenshaw-Curtis quadrature was implemented, verified and coupled to a pre-existing cross section representation system. Some ways to improve the integrator’s performance were also explored. The sparse grid methods were used to construct cross section representations for various Light Water Reactor fuel assemblies. These reactors have different operating conditions, enrichments and state parameters and therefore pose different challenges to a representation method. Additionally, an example where the cross sections have a different group structure, and were calculated using a different transport code, was used to test the representation method. The built-in error measures were tested on independent, uniformly distributed, quasi-random sample points. In all the cases studied, interpolation proved to be more accurate than approximation for the same number of samples. The primary source of error was found to be the Xenon transient at the beginning of an element’s life (BOL). To address this, the domain was split along the burn-up dimension into “start-up” and “operating” representations. As an alternative, the Xenon concentration was set to its equilibrium value for the whole burn-up range. The representations were also improved by applying anisotropic sampling. It was concluded that interpolation on a sparse grid shows promise as a method for building a cross section representation of sufficient accuracy to be used for practical reactor calculations with a reasonable number of samples. / Thesis (MSc Engineering Sciences (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2013.