A numerical simulation of steady and unsteady two-dimensional flows past cylinder with dimples based on highly accurate pseudospectral method is the subject of the present thesis. The vorticity-streamfunction formulation of two-dimensional incompressible Navier-Stokes equations with no-slip boundary conditions is used. The system is formulated on a unit disk using curvilinear body fitted coordinate system. Key issues of the curvilinear coordinate transformation are discussed, to show its importance in properly defined node distribution. For the space discretization of the governing system the Fourier-Chebyshev pseudospectral approximation on a unit disk is implemented. To handle the singularity at the pole of the unit disk the approach of defining the computational grid proposed by Fornberg was implemented. Two algorithms for solving steady and unsteady problems are presented. For steady flow simulations the non-linear time-independent Navier-Stokes problem is solved using the Newton's method. For the time-dependent problem the semi-implicit third order Adams-Bashforth/Backward Differentiation scheme is used. In both algorithms the fully coupled system with two no-slip boundary conditions is solved. Finally numerical result for both steady and unsteady solvers are presented. A comparison of results for the smooth cylinder with those from other authors shows good agreement. Spectral accuracy is demonstrated using the steady solver. / February 2007

A numerical simulation of steady and unsteady two-dimensional flows past cylinder with dimples based on highly accurate pseudospectral method is the subject of the present thesis. The vorticity-streamfunction formulation of two-dimensional incompressible Navier-Stokes equations with no-slip boundary conditions is used. The system is formulated on a unit disk using curvilinear body fitted coordinate system. Key issues of the curvilinear coordinate transformation are discussed, to show its importance in properly defined node distribution. For the space discretization of the governing system the Fourier-Chebyshev pseudospectral approximation on a unit disk is implemented. To handle the singularity at the pole of the unit disk the approach of defining the computational grid proposed by Fornberg was implemented. Two algorithms for solving steady and unsteady problems are presented. For steady flow simulations the non-linear time-independent Navier-Stokes problem is solved using the Newton's method. For the time-dependent problem the semi-implicit third order Adams-Bashforth/Backward Differentiation scheme is used. In both algorithms the fully coupled system with two no-slip boundary conditions is solved. Finally numerical result for both steady and unsteady solvers are presented. A comparison of results for the smooth cylinder with those from other authors shows good agreement. Spectral accuracy is demonstrated using the steady solver.

A numerical simulation of steady and unsteady two-dimensional flows past cylinder with dimples based on highly accurate pseudospectral method is the subject of the present thesis. The vorticity-streamfunction formulation of two-dimensional incompressible Navier-Stokes equations with no-slip boundary conditions is used. The system is formulated on a unit disk using curvilinear body fitted coordinate system. Key issues of the curvilinear coordinate transformation are discussed, to show its importance in properly defined node distribution. For the space discretization of the governing system the Fourier-Chebyshev pseudospectral approximation on a unit disk is implemented. To handle the singularity at the pole of the unit disk the approach of defining the computational grid proposed by Fornberg was implemented. Two algorithms for solving steady and unsteady problems are presented. For steady flow simulations the non-linear time-independent Navier-Stokes problem is solved using the Newton's method. For the time-dependent problem the semi-implicit third order Adams-Bashforth/Backward Differentiation scheme is used. In both algorithms the fully coupled system with two no-slip boundary conditions is solved. Finally numerical result for both steady and unsteady solvers are presented. A comparison of results for the smooth cylinder with those from other authors shows good agreement. Spectral accuracy is demonstrated using the steady solver.

In the past three decades, numerous methods have been proposed to transcribe optimal control problems (OCP) into nonlinear programming problems (NLP). In this dissertation work, a unifying weighted residual framework is developed under which most of the existing transcription methods can be derived by judiciously choosing test and trial functions. This greatly simplifies the derivation of optimality conditions and costate estimation results for direct transcription methods. Under the same framework, three new transcription methods are devised which are particularly suitable for implementation in an adaptive refinement setting. The method of Hilbert space projection, the least square method for optimal control and generalized moment method for optimal control are developed and their optimality conditions are derived. It is shown that under a set of equivalence conditions, costates can be estimated from the Lagrange multipliers of the associated NLP for all three methods. Numerical implementation of these methods is described using B-Splines and global interpolating polynomials as approximating functions. It is shown that the existing pseudospectral methods for optimal control can be formulated and analyzed under the proposed weighted residual framework. Performance of Legendre, Gauss and Radau pseudospectral methods is compared with the methods proposed in this research. Based on the variational analysis of first-order optimality conditions for the optimal control problem, an posteriori error estimation procedure is developed. Using these error estimates, an h-adaptive scheme is outlined for the implementation of least square method in an adaptive manner. A time-scaling technique is described to handle problems with discontinuous control or multiple phases. Several real-life examples were solved to show the efficacy of the h-adaptive and time-scaling algorithm.

Combustion at extreme conditions, such as a turbulent flame at high Karlovitz and Reynolds numbers, is still a vast and an uncertain field for researchers. Direct numerical simulation of a turbulent flame is a superior tool to unravel detailed information that is not accessible to most sophisticated state-of-the-art experiments. However, the computational cost of such simulations remains a challenge even for modern supercomputers, as the physical size, the level of turbulence intensity, and chemical complexities of the problems continue to increase. As a result, there is a strong demand for computational cost reduction methods as well as in acceleration of existing methods. The main scope of this work was the development of computational and numerical tools for high-fidelity direct numerical simulations of premixed planar flames interacting with turbulence. The first part of this work was KAUST Adaptive Reacting Flow Solver (KARFS) development. KARFS is a high order compressible reacting flow solver using detailed chemical kinetics mechanism; it is capable to run on various types of heterogeneous computational architectures. In this work, it was shown that KARFS is capable of running efficiently on both CPU and GPU. The second part of this work was numerical tools for direct numerical simulations of planar premixed flames: such as linear turbulence forcing and dynamic inlet control. DNS of premixed turbulent flames conducted previously injected velocity fluctuations at an inlet. Turbulence injected at the inlet decayed significantly while reaching the flame, which created a necessity to inject higher than needed fluctuations. A solution for this issue was to maintain turbulence strength on the way to the flame using turbulence forcing. Therefore, a linear turbulence forcing was implemented into KARFS to enhance turbulence intensity. Linear turbulence forcing developed previously by other groups was corrected with net added momentum removal mechanism to prevent mean velocity drift. Also, dynamic inlet control was implemented which retained flame inside of a domain even at very high fuel consumption fluctuations. Last part of this work was to implement pseudospectral method into KARFS. Direct numerical simulations performed previously are targeting real engines and turbines conditions as an ultimate goal. These targeted simulations are prohibitively computationally expensive. This work suggested and implemented into KARFS a pseudospectral method for reacting turbulent flows, as an attempt to decrease computational cost. Approximately four times computational CPU hours savings were achieved.

Large eddy simulation (LES) suffers from two primary sources of error: the numerical discretization scheme and the subgrid stress model (SGS). An attempt has been made to determine optimum combinations of SGS models and numerical schemes for use in performing practical LES for engineering-relevant problems. A formal quantification of numerical error present in finite-volume/finite-difference simulations was conducted. The effect of this error was explicitly added to a pseudospectral LES solver, and the modified pseudospectral solver was used to compute LES of decaying turbulence. In this way SGS modeling error and numerical error could be separately assessed. Verification of results was carried out using a commercially available finite-volume solver (FLUENT). Results showed that some combinations of SGS model and discretization scheme are more suitable for performing LES than others. Favorable combinations from the above findings were tested for an axisymmetric jet at Mach number 0.2. Results indicate good agreement with prior findings.

The finite-difference time-domain (FDTD) method is one of the most popular numerical electromagnetic analysis tools. This method has been applied to a wide variety of problems such as antennas, electronic packaging, waveguides, etc. However, it is not suitable for large scale structures. The enormous memory requirement prohibits the use of FDTD to a large electrical size. Recently, the pseudospectral time-domain (PSTD) method has been introduced for solution of Maxwell¡¦s equation. This method adopts the Fourier transform algorithm to perform the spatial derivatives. According to Nyquist sampling theorem, it requires only 2 cells per wavelength, so that it is possible to efficiently model larger scale problems. This thesis describes a combination of PSTD and FDTD method applied in different directions. The FDTD be applied to directions along fine structures and the PSTD be applied in direction along large structures.

The pseudospectral method is a family of numerical methods for the solution of differential equations based on the expansion of basis functions defined on a set of grid points. In this thesis, the relationship between the distribution of grid points and the accuracy and convergence of the solution is emphasized. The polynomial and sinc pseudospectral methods are extensively studied along with many applications to quantum and statistical mechanics involving the Fokker-Planck and Schroedinger equations. The grid points used in the polynomial methods coincide with the points of quadrature, which are defined by a set of polynomials orthogonal with respect to a weight function. The choice of the weight function plays an important role in the convergence of the solution. It is observed that rapid convergence is usually achieved when the weight function is chosen to be the square of the ground-state eigenfunction of the problem. The sinc method usually provides a slow convergence as the grid points are uniformly distributed regardless of the behaviour of the solution. For both polynomial and sinc methods, the convergence rate can be improved by redistributing the grid points to more appropriate positions through a transformation of coordinates. The transformation method discussed in this thesis preserves the orthogonality of the basis functions and provides simple expressions for the construction of discretized matrix operators. The convergence rate can be improved by several times in the evaluation of loosely bound eigenstates with an exponential or hyperbolic sine transformation. The transformation can be defined explicitly or implicitly. An explicit transformation is based on a predefined mapping function, while an implicit transformation is constructed by an appropriate set of grid points determined by the behaviour of the solution. The methodologies of these transformations are discussed with some applications to 1D and 2D problems. The implicit transformation is also used as a moving mesh method for the time-dependent Smoluchowski equation when a function with localized behaviour is used as the initial condition.

No description available.

The pseudospectral method is a family of numerical methods for the solution of differential equations based on the expansion of basis functions defined on a set of grid points. In this thesis, the relationship between the distribution of grid points and the accuracy and convergence of the solution is emphasized. The polynomial and sinc pseudospectral methods are extensively studied along with many applications to quantum and statistical mechanics involving the Fokker-Planck and Schroedinger equations. The grid points used in the polynomial methods coincide with the points of quadrature, which are defined by a set of polynomials orthogonal with respect to a weight function. The choice of the weight function plays an important role in the convergence of the solution. It is observed that rapid convergence is usually achieved when the weight function is chosen to be the square of the ground-state eigenfunction of the problem. The sinc method usually provides a slow convergence as the grid points are uniformly distributed regardless of the behaviour of the solution. For both polynomial and sinc methods, the convergence rate can be improved by redistributing the grid points to more appropriate positions through a transformation of coordinates. The transformation method discussed in this thesis preserves the orthogonality of the basis functions and provides simple expressions for the construction of discretized matrix operators. The convergence rate can be improved by several times in the evaluation of loosely bound eigenstates with an exponential or hyperbolic sine transformation. The transformation can be defined explicitly or implicitly. An explicit transformation is based on a predefined mapping function, while an implicit transformation is constructed by an appropriate set of grid points determined by the behaviour of the solution. The methodologies of these transformations are discussed with some applications to 1D and 2D problems. The implicit transformation is also used as a moving mesh method for the time-dependent Smoluchowski equation when a function with localized behaviour is used as the initial condition.