63,422 research outputs found
Generating numerical algorithms using a computer algebra system
An useful application of computer algebra systems is the generation of algorithms for numerical computations. We have shown in Gander and Gruntz (SIAM Rev., 1999) how computer algebra can be used in teaching to derive numerical methods. In this paper we extend this work, using essentially the capability of computer algebra system to construct and manipulate the interpolating polynomial and to compute a series expansion of a function. We will automatically generate formulas for integration and differentiation with error terms and also generate multistep methods for integrating differential equation
Symbolic-numeric interface: A review
A survey of the use of a combination of symbolic and numerical calculations is presented. Symbolic calculations primarily refer to the computer processing of procedures from classical algebra, analysis, and calculus. Numerical calculations refer to both numerical mathematics research and scientific computation. This survey is intended to point out a large number of problem areas where a cooperation of symbolic and numerical methods is likely to bear many fruits. These areas include such classical operations as differentiation and integration, such diverse activities as function approximations and qualitative analysis, and such contemporary topics as finite element calculations and computation complexity. It is contended that other less obvious topics such as the fast Fourier transform, linear algebra, nonlinear analysis and error analysis would also benefit from a synergistic approach
Formation of structural matrices for finite elements of piezoceramic structures
This paper deals with the description of a theoretical background of systematic computer algebra methods for the formation of structural matrices of piezoceramic finite elements. Piezoceramic actuators are widely used for high-precision mechanical systems such as positioning devices, manipulating systems, control equipment, etc. In this paper, the efficiency of computer algebra application was compared with the numerical integration methods of formation of the structural matrices of the finite elements. Two popular finite elements are discussed for modeling piezoceramic actuators: sector type and the triangular one. All structural matrices of the elements were derived using the computer algebra technique with the following automatic program code generation. Due to smaller floating point operations, the computer time economy is followed by an increased accuracy of computations, which is the most important gain achieved in many cases
Kranc: a Mathematica application to generate numerical codes for tensorial evolution equations
We present a suite of Mathematica-based computer-algebra packages, termed
"Kranc", which comprise a toolbox to convert (tensorial) systems of partial
differential evolution equations to parallelized C or Fortran code. Kranc can
be used as a "rapid prototyping" system for physicists or mathematicians
handling very complicated systems of partial differential equations, but
through integration into the Cactus computational toolkit we can also produce
efficient parallelized production codes. Our work is motivated by the field of
numerical relativity, where Kranc is used as a research tool by the authors. In
this paper we describe the design and implementation of both the Mathematica
packages and the resulting code, we discuss some example applications, and
provide results on the performance of an example numerical code for the
Einstein equations.Comment: 24 pages, 1 figure. Corresponds to journal versio
How AD Can Help Solve Differential-Algebraic Equations
A characteristic feature of differential-algebraic equations is that one
needs to find derivatives of some of their equations with respect to time, as
part of so called index reduction or regularisation, to prepare them for
numerical solution. This is often done with the help of a computer algebra
system. We show in two significant cases that it can be done efficiently by
pure algorithmic differentiation. The first is the Dummy Derivatives method,
here we give a mainly theoretical description, with tutorial examples. The
second is the solution of a mechanical system directly from its Lagrangian
formulation. Here we outline the theory and show several non-trivial examples
of using the "Lagrangian facility" of the Nedialkov-Pryce initial-value solver
DAETS, namely: a spring-mass-multipendulum system, a prescribed-trajectory
control problem, and long-time integration of a model of the outer planets of
the solar system, taken from the DETEST testing package for ODE solvers
Gr\"obner Bases and Generation of Difference Schemes for Partial Differential Equations
In this paper we present an algorithmic approach to the generation of fully
conservative difference schemes for linear partial differential equations. The
approach is based on enlargement of the equations in their integral
conservation law form by extra integral relations between unknown functions and
their derivatives, and on discretization of the obtained system. The structure
of the discrete system depends on numerical approximation methods for the
integrals occurring in the enlarged system. As a result of the discretization,
a system of linear polynomial difference equations is derived for the unknown
functions and their partial derivatives. A difference scheme is constructed by
elimination of all the partial derivatives. The elimination can be achieved by
selecting a proper elimination ranking and by computing a Gr\"obner basis of
the linear difference ideal generated by the polynomials in the discrete
system. For these purposes we use the difference form of Janet-like Gr\"obner
bases and their implementation in Maple. As illustration of the described
methods and algorithms, we construct a number of difference schemes for Burgers
and Falkowich-Karman equations and discuss their numerical properties.Comment: Published in SIGMA (Symmetry, Integrability and Geometry: Methods and
Applications) at http://www.emis.de/journals/SIGMA
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