Isogeometric Analysis in advection-diffusion problems: tension splines approximation

We present a novel approach, within the new paradigm of isogeometric analysis introduced by Hughes et al., to deal with advection dominated advection-diffusion problems. The key ingredient is the use of Galerkin approximating spaces of functions with high smoothness, as in IgA based on classical B-splines, but particularly well suited to describe sharp layers involving very strong gradients

Spline-based Rayleigh-Ritz methods for the approximation of the natural modes of vibration for flexible beams with tip bodies

Rayleigh-Ritz methods for the approximation of the natural modes for a class of vibration problems involving flexible beams with tip bodies using subspaces of piecewise polynomial spline functions are developed. An abstract operator theoretic formulation of the eigenvalue problem is derived and spectral properties investigated. The existing theory for spline-based Rayleigh-Ritz methods applied to elliptic differential operators and the approximation properties of interpolatory splines are useed to argue convergence and establish rates of convergence. An example and numerical results are discussed

Investigation of smoothness-increasing accuracy-conserving filters for improving streamline integration through discontinuous fields

Journal ArticleStreamline integration of fields produced by computational fluid mechanics simulations is a commonly used tool for the investigation and analysis of fluid flow phenomena. Integration is often accomplished through the application of ordinary differential equation (ODE) integrators - integrators whose error characteristics are predicated on the smoothness of the field through which the streamline is being integrated, which is not available at the interelement level of finite volume and finite element data. Adaptive error control techniques are often used to ameliorate the challenge posed by interelement discontinuities

Numerical solution of singularly perturbed convection–diffusion problem using parameter uniform B-spline collocation method

AbstractThis paper is concerned with a numerical scheme to solve a singularly perturbed convection–diffusion problem. The solution of this problem exhibits the boundary layer on the right-hand side of the domain due to the presence of singular perturbation parameter ɛ. The scheme involves B-spline collocation method and appropriate piecewise-uniform Shishkin mesh. Bounds are established for the derivative of the analytical solution. Moreover, the present method is boundary layer resolving as well as second-order uniformly convergent in the maximum norm. A comprehensive analysis has been given to prove the uniform convergence with respect to singular perturbation parameter. Several numerical examples are also given to demonstrate the efficiency of B-spline collocation method and to validate the theoretical aspects

Scalable GPU acceleration of b-spline signal processing operations

B-Splines are a useful tool in signal processing, and are widely used in the analysis of two and three-dimensional images. B-Splines provide a continuous representation of the signal, image, or volume, which is useful for interpolation, resampling, noise removal, and differentiation - all important steps in many signal processing algorithms. These splines are defined entirely by an array of coefficients that is roughly the same size as the original signal and of values in the same order of magnitude, making storage and representation trivial. What is not trivial, however, is the quick calculation and processing of those coefficients, especially for very large data. As technology improves in fields such as medical imaging, algorithms that use B-Splines will need to process increasingly higher resolution images and voxel volumes. New implementations are needed to make use of modern parallel architectures to keep these algorithms practical. This thesis presents a library for performing many common B-Splines operations in CUDA, the parallel programming framework for NVIDIA GPUs, and analyzes the considerations necessary when implementing a large-scale parallel version of such a well-established sequential algorithm. This library is meant to be used both by C++ programs as well as algorithms implemented in MATLAB without requiring significant changes. Significant speedups are obtained using this library to perform various common B-Spline image processing operations (as much as 30x for some), and the scalability limitations of the GPU implementation are addressed