At many American colleges and universities, efforts to enhance the retention of a diverse group of students have become a priority. This study represents part of this effort at the University of Central Florida, a large public suburban state university in the South. Specifically, this investigation evaluated Pegasus '95 and the Academic Mentoring Program offered in the Summer and Fall Semesters of 1995 to specially-admitted students who fell short of regular admissions requirements. During the summer, Pegasus '95 provided testing, orientation, guided course work, study skills workshops, and mentoring, both individually and in the context of cohesive socialization groups of approximately 15 students each. In the Fall 1995 Semester, students were highly encouraged to participate in one-on-one mentoring in the Academic Mentoring Program (AMP) available through the Student Academic Resource Center (SARC), a university-based office which provides a variety of academic assistance services. A multiple regression analysis was conducted using the following independent predictor variables: gender, SAT/ACT scores, Pegasus participation, use of the AMP in the Fall 1995 semester, four summary scores from the College Student Inventory (CSI), and eight scaled scores from the Noncognitive Questionnaire (NCQ). Dependent variables were individual student GPA in the Summer and Fall 1995 semesters, cumulative GPA after two semesters, and enrolled credit hours into the Spring 1996 academic term. Overall, it was expected that a combination of predictor variables, including both traditional cognitive factors (SAT/ACT scores and high school GPA) and noncognitive factors (NCQ scores and CSI scores, Pegasus participation, and mentoring by the SARC) would significantly predict GP A and retention. The study found that a regression equation including gender, high school GPA, overall SAT scores and the eight NCQ scale scores significantly predicted Fall 1995 and cumulative GPA after two semesters but not Summer 1995 GPA or credit hours enrolled in Spring 1996. Attendance at Pegasus meetings was also shown to be significantly and positively associated with Fall 1995 GPA and cumulative GPA after two semesters but not of Summer 1995 GPA or credit hours enrolled in Spring 1996. Gender, high school GP A, the ACT score and the CSI Dropout Proneness scale significantly predicted credit hours enrolled in Spring 1996, as did use of the AMP program provided by the SARC. Of particular interest was the finding that including noncognitive factors in significant equations led to a greater explanation of the variance than could be obtained with any of the traditional cognitive measurements alone, suggesting that with academically disadvantaged students noncognitive measures must be considered in predicting who can succeed and persist in college.

A coupled solution approach is presented for numerically simulating a near-field underwater explosion (UNDEX). An UNDEX consists of a complicated sequence of events over a wide range of time scales. Due to the complex physics, separate simulations for near/far-field and early/late-time are common in practice. This work focuses on near-field early-time UNDEX simulations. Using the assumption of compressible, inviscid and adiabatic flow, the fluid flow is governed by a set of Euler fluid equations. In practical simulations, we often encounter computational difficulties that include large displacements, shocks, multi-fluid flows with cavitation, spurious waves reflecting from boundaries and fluid-structure coupling. Existing methods and codes are not able to simultaneously consider all of these characteristics. A robust numerical method that is capable of treating large displacements, capturing shocks, handling two-fluid flows with cavitation, imposing non-reflecting boundary conditions (NRBC) and allowing the movement of fluid grids is required. This method is developed by combining numerical techniques that include a high-order accurate numerical method with a shock capturing scheme, a multi-fluid method to handle explosive gas-water flows and cavitating flows, and an Arbitrary Lagrangian Eulerian (ALE) deformable fluid mesh. These combined approaches are unique for numerically simulating various near-field UNDEX phenomena within a robust single framework. A review of the literature indicates that a fully coupled methodology with all of these characteristics for near-field UNDEX phenomena has not yet been developed. A set of governing equations in the ALE description is discretized by a Runge Kutta Discontinuous Galerkin (RKDG) method. For multi-fluid flows, a Direct Ghost Fluid (DGF) Method coupled with the Level Set (LS) interface method is incorporated in the RKDG framework. The combination of RKDG and DGF methods (RKDG-DGF) is the main contribution of this work which improves the quality and stability of near-field UNDEX flow simulations. Unlike other methods, this method is simpler to apply for various UNDEX applications and easier to extend to multi-dimensions. / Ph. D.

This paper investigates the competitiveness of semi-implicit Runge-Kutta (RK) and spectral deferred correction (SDC) time-integration methods up to order six for incompressible Navier-Stokes problems in conjunction with a high-order discontinuous Galerkin method for space discretization. It is proposed to harness the implicit and explicit RK parts as a partitioned scheme, which provides a natural basis for the underlying projection scheme and yields a straight-forward approach for accommodating nonlinear viscosity. Numerical experiments on laminar flow, variable viscosity and transition to turbulence are carried out to assess accuracy, convergence and computational efficiency. Although the methods of order 3 or higher are susceptible to order reduction due to time-dependent boundary conditions, two third-order RK methods are identified that perform well in all test cases and clearly surpass all second-order schemes including the popular extrapolated backward difference method. The considered SDC methods are more accurate than the RK methods, but become competitive only for relative errors smaller than ca .

abstract: Rabies is an infectious viral disease. It is usually fatal if a victim reaches the rabid stage, which starts after the appearance of disease symptoms. The disease virus attacks the central nervous system, and then it migrates from peripheral nerves to the spinal cord and brain. At the time when the rabies virus reaches the brain, the incubation period is over and the symptoms of clinical disease appear on the victim. From the brain, the virus travels via nerves to the salivary glands and saliva. A mathematical model is developed for the spread of rabies in a spatially distributed fox population to model the spread of the rabies epizootic through middle Europe that occurred in the second half of the 20th century. The model considers both territorial and wandering rabid foxes and includes a latent period for the infection. Since the model assumes these two kinds of rabid foxes, it is a system of both partial differential and integral equations (with integration over space and, occasionally, also over time). To study the spreading speeds of the rabies epidemic, the model is reduced to a scalar Volterra-Hammerstein integral equation, and space-time Laplace transform of the integral equation is used to derive implicit formulas for the spreading speed. The spreading speeds are discussed and implicit formulas are given for latent periods of fixed length, exponentially distributed length, Gamma distributed length, and log-normally distributed length. A number of analytic and numerical results are shown pertaining to the spreading speeds. Further, a numerical algorithm is described for the simulation of the spread of rabies in a spatially distributed fox population on a bounded domain with Dirichlet boundary conditions. I propose the following methods for the numerical approximation of solutions. The partial differential and integral equations are discretized in the space variable by central differences of second order and by the composite trapezoidal rule. Next, the ordinary or delay differential equations that are obtained this way are discretized in time by explicit continuous Runge-Kutta methods of fourth order for ordinary and delay differential systems. My particular interest is in how the partition of rabid foxes into territorial and diffusing rabid foxes influences the spreading speed, a question that can be answered by purely analytic means only for small basic reproduction numbers. I will restrict the numerical analysis to latent periods of fixed length and to exponentially distributed latent periods. The results of the numerical calculations are compared for latent periods of fixed and exponentially distributed length and for various proportions of territorial and wandering rabid foxes. The speeds of spread observed in the simulations are compared to spreading speeds obtained by numerically solving the analytic formulas and to observed speeds of epizootic frontlines in the European rabies outbreak 1940 to 1980. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2018

A numerical method (SIMPLE DIRK Method) for unsteady incompressible viscous flow simulation is presented. The proposed method can be used to achieve arbitrarily high order of accuracy in time-discretization which is otherwise limited to second order in majority of the currently used simulation techniques. A special class of implicit Runge-Kutta methods is used for time discretization in conjunction with finite volume based SIMPLE algorithm. The algorithm was tested by solving for velocity field in a lid-driven square cavity. In the test case calculations, power law scheme was used in spatial discretization and time discretization was performed using a second-order implicit Runge-Kutta method. Time evolution of velocity profile along the cavity centerline was obtained from the proposed method and compared with that obtained from a commercial computational fluid dynamics software program, FLUENT 6.2.16. Also, steady state solution from the present method was compared with the numerical solution of Ghia, Ghia, and Shin and that of Erturk, Corke, and Goökçöl. Good agreement of the solution of the proposed method with the solutions of FLUENT; Ghia, Ghia, and Shin; and Erturk, Corke, and Goökçöl establishes the feasibility of the proposed method.

A numerical method (SIMPLE DIRK Method) for unsteady incompressible viscous flow simulation is presented. The proposed method can be used to achieve arbitrarily high order of accuracy in time-discretization which is otherwise limited to second order in majority of the currently used simulation techniques. A special class of implicit Runge-Kutta methods is used for time discretization in conjunction with finite volume based SIMPLE algorithm. The algorithm was tested by solving for velocity field in a lid-driven square cavity. In the test case calculations, power law scheme was used in spatial discretization and time discretization was performed using a second-order implicit Runge-Kutta method. Time evolution of velocity profile along the cavity centerline was obtained from the proposed method and compared with that obtained from a commercial computational fluid dynamics software program, FLUENT 6.2.16. Also, steady state solution from the present method was compared with the numerical solution of Ghia, Ghia, and Shin and that of Erturk, Corke, and Goökçöl. Good agreement of the solution of the proposed method with the solutions of FLUENT; Ghia, Ghia, and Shin; and Erturk, Corke, and Goökçöl establishes the feasibility of the proposed method.

The validity of transfer matrix method (TMM) employed in a nonlinear gear cam system is studied in this thesis. The nonlinear dynamic responses of each part in the nonlinear system are estimated by applying the 4th-order Runge-Kutta method. A high speed gear cam drive automatic die cutter was analyzed in this study. A 25 horsepower AC induction motor is designed to drive the system. To complete the cutting work, a sequential process of the harmonic motion and the intermittent motion are generated by the elbow mechanism and the gear cam mechanism, respectively. A simplified branched multi-rotor system is modeled to approximate the motion of the system. The variation of the dynamic parameters of the system in a loading cycle is estimated under a branched torsional system. The Holzer¡¦s transfer matrix method is used to study the variation of the system parameters during the intermittent movement. Moreover, the effect of time-varied speed introduced from the torque variation of the induction motor and gear cam mechanism on the nonlinear dynamic response of the system has also been investigated. To explore the dynamic effect of different cam designs, three different cam motion curves and seven operating rates have been analyzed in this work. The residual vibration of the last sprocket has also been discussed. Numerical results indicate that the proposed model is available to simulate the dynamic responses of a nonlinear gear cam drive system.

M. Tech. : Mathematical Technology. / Attempts will be made to extend the elementary quarter-mass models (for instance Gillepse, 1992, [5]; Kiecke & Nielsen, 2000, [6] and Singiresu, 2004, [7]) of a motor vehicle suspension system to include the radial vibrations of a rubber tyre in the model. Tangential vibrations of the tyre surface were investigated by Bekker (2009, [8]) and the possible incorporation of such vibrations into a suspension model invites the possibility of future study.

Multisymplectic integration is a relatively new addition to the field of geometric integration, which is a modern approach to the numerical integration of systems of differential equations. Multisymplectic integration is carried out by numerical integrators known as multisymplectic integrators, which preserve a discrete analogue of a multisymplectic conservation law. In recent years, it has been shown that various discretisations of a multi-Hamiltonian PDE satisfy a discrete analogue of a multisymplectic conservation law. In particular, discretisation in time and space by the popular symplectic Runge–Kutta methods has been shown to be multisymplectic. However, a multisymplectic integrator not only needs to satisfy a discrete multisymplectic conservation law, but it must also form a well-defined numerical method. One of the main questions considered in this thesis is that of when a multi-Hamiltonian PDE discretised by Runge–Kutta or partitioned Runge–Kutta methods gives rise to a well-defined multisymplectic integrator. In particular, multisymplectic integrators that are explicit are sought, since an integrator that is explicit will, in general, be well defined. The first class of discretisation methods that I consider are the popular symplectic Runge–Kutta methods. These have previously been shown to satisfy a discrete analogue of the multisymplectic conservation law. However, these previous studies typically fail to consider whether or not the system of equations resulting from such a discretisation is well defined. By considering the semi-discretisation and the full discretisation of a multi-Hamiltonian PDE by such methods, I show the following: • For Runge–Kutta (and for partitioned Runge–Kutta methods), the active variables in the spatial discretisation are the stage variables of the method, not the node variables (as is typical in the time integration of ODEs). • The equations resulting from a semi-discretisation with periodic boundary conditions are only well defined when both the number of stages in the Runge–Kutta method and the number of cells in the spatial discretisation are odd. For other types of boundary conditions, these equations are not well defined in general. • For a full discretisation, the numerical method appears to be well defined at first, but for some boundary conditions, the numerical method fails to accurately represent the PDE, while for other boundary conditions, the numerical method is highly implicit, ill-conditioned and impractical for all but the simplest of applications. An exception to this is the Preissman box scheme, whose simplicity avoids the difficulties of higher order methods. • For a multisymplectic integrator, boundary conditions are treated differently in time and in space. This breaks the symmetry between time and space that is inherent in multisymplectic geometry. The second class of discretisation methods that I consider are partitioned Runge– Kutta methods. Discretisation of a multi-Hamiltonian PDE by such methods has lead to the following two major results: 1. There is a simple set of conditions on the coefficients of a general partitioned Runge– Kutta method (which includes Runge–Kutta methods) such that a general multi- Hamiltonian PDE, discretised (either fully or partially) by such methods, satisfies a natural discrete analogue of the multisymplectic conservation law associated with that multi-Hamiltonian PDE. 2. I have defined a class of multi-Hamiltonian PDEs that, when discretised in space by a member of the Lobatto IIIA–IIIB class of partitioned Runge–Kutta methods, give rise to a system of explicit ODEs in time by means of a construction algorithm. These ODEs are well defined (since they are explicit), local, high order, multisymplectic and handle boundary conditions in a simple manner without the need for any extra requirements. Furthermore, by analysing the dispersion relation for these explicit ODEs, it is found that such spatial discretisations are stable. From these explicit ODEs in time, well-defined multisymplectic integrators can be constructed by applying an explicit discretisation in time that satisfies a fully discrete analogue of the semi-discrete multisymplectic conservation law satisfied by the ODEs. Three examples of explicit multisymplectic integrators are given for the nonlinear Schr¨odinger equation, whereby the explicit ODEs in time are discretised by the 2-stage Lobatto IIIA– IIIB, linear–nonlinear splitting and real–imaginary–nonlinear splitting methods. These are all shown to satisfy discrete analogues of the multisymplectic conservation law, however, only the discrete multisymplectic conservation laws satisfied by the first and third multisymplectic integrators are local. Since it is the stage variables that are active in a Runge–Kutta or partitioned Runge– Kutta discretisation in space of a multi-Hamiltonian PDE, the order of such a spatial discretisation is limited by the order of the stage variables. Moreover, the spatial discretisation contains an approximation of the spatial derivatives, and thus, the order of the spatial discretisation may be further limited by the order of this approximation. For the explicit ODEs resulting from an r-stage Lobatto IIIA–IIIB discretisation in space of an appropriate multi-Hamiltonian PDE, the order of this spatial discretisation is r - 1 for r = 10; this is conjectured to hold for higher values of r. For r = 3, I show that a modification to the initial conditions improves the order of this spatial discretisation. It is expected that a similar modification to the initial conditions will improve the order of such spatial discretisations for higher values of r.

Submitted by ANA KARLA PEREIRA RODRIGUES (anakarla_@hotmail.com) on 2017-09-01T13:56:46Z No. of bitstreams: 1 arquivototal.pdf: 3239292 bytes, checksum: 8279cebbf86db2bb4db05f382688e5c4 (MD5) / Approved for entry into archive by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2017-09-01T15:59:49Z (GMT) No. of bitstreams: 1 arquivototal.pdf: 3239292 bytes, checksum: 8279cebbf86db2bb4db05f382688e5c4 (MD5) / Made available in DSpace on 2017-09-01T15:59:49Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3239292 bytes, checksum: 8279cebbf86db2bb4db05f382688e5c4 (MD5) Previous issue date: 2017-06-19 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Is evident the importance of ordinary differential equations in modeling problems in several areas of science. Coupled with this, is increasing the use of numerical methods to solve such equations. Computers have become an extremely useful tool in the study of differential equations, since through them it is possible to execute algorithms that construct numerical approximations for solutions of these equati- ons. This work introduces the study of numerical methods for ordinary differential equations presenting the numerical Eulerºs method, improved Eulerºs method and the class of Runge-Kuttaºs methods. In addition, in order to collaborate with the teaching and learning of such methods, we propose and show the construction of an applet created from the use of Geogebm software tools. The applet provides approximate numerical solutions to an initial value problem, as well as displays the graphs of the solutions that are obtained from the numerical Eulerºs method, im- proved Eulerºs method, and fourth-order Runge-Kuttaºs method. / É evidente a importancia das equações diferenciais ordinarias na modelagem de problemas em diversas áreas da ciência, bem como o uso de métodos numéricos para resolver tais equações. Os computadores são uma ferramenta extremamente útil no estudo de equações diferenciais, uma vez que através deles é possível executar algo- ritmos que constroem aproximações numéricas para soluções destas equações. Este trabalho é uma introdução ao estudo de métodos numéricos para equações diferen- ciais ordinarias. Apresentamos os métodos numéricos de Euler, Euler melhorado e a classe de métodos de Runge-Kutta. Além disso, com o propósito de colaborar com o ensino e aprendizagem de tais métodos, propomos e mostramos a construção de um applet criado a partir do uso de ferramentas do software Geogebra. O applet fornece soluções numéricas aproximadas para um problema de valor inicial, bem como eXibe os graficos das soluções que são obtidas a partir dos métodos numéricos de Euler, Euler melhorado e Runge-Kutta de quarta ordem.