The Experts below are selected from a list of 54 Experts worldwide ranked by ideXlab platform

Otto Von Estorff - One of the best experts on this subject based on the ideXlab platform.

  • assessment of finite and spectral element shape functions for efficient iterative simulations of interior acoustics
    Computer Methods in Applied Mechanics and Engineering, 2006
    Co-Authors: Steffen Petersen, Daniel Dreyer, Otto Von Estorff
    Abstract:

    Several shape function families currently used in the spectral element and the finite element method (FEM) are reviewed. Widely known shape functions such as the conventional Lagrange functions, various p-FEM shapes, and recent developments in the area of spectral methods are compared. Especially, shape functions derived from Bernstein polynomials are discussed, due to their ease of formulation for almost any Geometric Entity. Their applicability and efficiency for acoustic simulations are assessed. In particular, the efficiency is measured in terms of performance of current Krylov solvers.

Bohdan I Lev - One of the best experts on this subject based on the ideXlab platform.

  • wave function as Geometric Entity
    Journal of Modern Physics, 2012
    Co-Authors: Bohdan I Lev
    Abstract:

    A spacial approach to the geometrization the theory of the electron has been proposed. The particle wave function is represented by a Geometric Entity, i.e., Clifford number, with the translation rules possessing the structure of Dirac equation for any manifold. A solution of this equation is obtained in terms of Geometric treatment. New experiments concerning the Geometric nature wave function of electrons are proposed.

  • wave function as Geometric Entity
    arXiv: Quantum Physics, 2011
    Co-Authors: Bohdan I Lev
    Abstract:

    A new approach to the geometrization of the electron theory is proposed. The particle wave function is represented by a Geometric Entity, i.e., Clifford number, with the translation rules possessing the structure of Dirac equation for any manifold. A solution of this equation is obtained in terms of Geometric treatment. Interference of electrons whose wave functions are represented by Geometric entities is considered. New experiments concerning the Geometric nature of electrons are proposed.

Steffen Petersen - One of the best experts on this subject based on the ideXlab platform.

  • assessment of finite and spectral element shape functions for efficient iterative simulations of interior acoustics
    Computer Methods in Applied Mechanics and Engineering, 2006
    Co-Authors: Steffen Petersen, Daniel Dreyer, Otto Von Estorff
    Abstract:

    Several shape function families currently used in the spectral element and the finite element method (FEM) are reviewed. Widely known shape functions such as the conventional Lagrange functions, various p-FEM shapes, and recent developments in the area of spectral methods are compared. Especially, shape functions derived from Bernstein polynomials are discussed, due to their ease of formulation for almost any Geometric Entity. Their applicability and efficiency for acoustic simulations are assessed. In particular, the efficiency is measured in terms of performance of current Krylov solvers.

Neil D. Mckay - One of the best experts on this subject based on the ideXlab platform.

  • A Method for Registration of 3-D Shapes
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992
    Co-Authors: Paul J. Besl, Neil D. Mckay
    Abstract:

    This paper describes a general-purpose, representation-independent method for the accurate and computationally efficient registration of 3-D shapes including free-form curves and surfaces. The method handles the full six degrees of freedom and is based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a Geometric Entity to a given point. The ICP algorithm always converges monotonically to the nearest local minimum of a mean square distance metric, and experience shows that the rate of convergence is rapid during the first few iterations. Therefore, given an adequate set of initial rotations and translations for a particular class of objects with a certain level of "shape complexity," one can globally minimize the mean-square distance metric over all six degrees of freedom by testing each initial registration. For example, a given "model" shape and a sensed "data" shape that represents a major portion of the model shape can be registered in minutes by testing one initial translation and a relatively small set of rotations to allow for the given level of model complexity. One important application of this method is to register sensed data from unfixtured rigid objects with an ideal Geometric model prior to shape inspection. The described method is also useful for deciding fundamental issues such as the congruence (shape equivalence) of different Geometric representations as well as for estimating the motion between point sets where the correspondences are not known. Experimental results show the capabilities of the registration algorithm on point sets, curves, and surfaces.

H D Mckay - One of the best experts on this subject based on the ideXlab platform.

  • a method for registration of 3 d shapes
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992
    Co-Authors: Paul J Esl, H D Mckay
    Abstract:

    The authors describe a general-purpose, representation-independent method for the accurate and computationally efficient registration of 3-D shapes including free-form curves and surfaces. The method handles the full six degrees of freedom and is based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a Geometric Entity to a given point. The ICP algorithm always converges monotonically to the nearest local minimum of a mean-square distance metric, and the rate of convergence is rapid during the first few iterations. Therefore, given an adequate set of initial rotations and translations for a particular class of objects with a certain level of 'shape complexity', one can globally minimize the mean-square distance metric over all six degrees of freedom by testing each initial registration. One important application of this method is to register sensed data from unfixtured rigid objects with an ideal Geometric model, prior to shape inspection. Experimental results show the capabilities of the registration algorithm on point sets, curves, and surfaces. >