7 results match your criteria Applied Numerical Mathematics[Journal]

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Comparison of reduced models for blood flow using Runge-Kutta discontinuous Galerkin methods.

Appl Numer Math 2017 May 11;115:114-141. Epub 2017 Jan 11.

Baylor College of Medicine, Department of Pediatric Cardiology.

One-dimensional blood flow models take the general form of nonlinear hyperbolic systems but differ in their formulation. One class of models considers the physically conserved quantities of mass and momentum, while another class describes mass and velocity. Further, the averaging process employed in the model derivation requires the specification of the axial velocity profile; this choice differentiates models within each class. Read More

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Simultaneous optical flow and source estimation: Space-time discretization and preconditioning.

Appl Numer Math 2015 Oct;96:72-81

Institute of Computational Mathematics, Johannes Kepler University, Altenberger Str. 69, 4040 Linz, Austria.

We consider the simultaneous estimation of an optical flow field and an illumination source term in a movie sequence. The particular optical flow equation is obtained by assuming that the image intensity is a conserved quantity up to possible sources and sinks which represent varying illumination. We formulate this problem as an energy minimization problem and propose a space-time simultaneous discretization for the optimality system in saddle-point form. Read More

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October 2015

Finite element solution of nonlinear eddy current problems with periodic excitation and its industrial applications.

Appl Numer Math 2014 May;79(100):3-17

Institute for Fundamentals and Theory in Electrical Engineering (IGTE), Graz University of Technology, Inffeldgasse 18, 8010 Graz, Austria.

An efficient finite element method to take account of the nonlinearity of the magnetic materials when analyzing three-dimensional eddy current problems is presented in this paper. The problem is formulated in terms of vector and scalar potentials approximated by edge and node based finite element basis functions. The application of Galerkin techniques leads to a large, nonlinear system of ordinary differential equations in the time domain. Read More

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A study of different modeling choices for simulating platelets within the immersed boundary method.

Appl Numer Math 2013 Jan;63:58-77

School of Computing, Univ. of Utah, Salt Lake City, UT, USA.

The Immersed Boundary (IB) method is a widely-used numerical methodology for the simulation of fluid-structure interaction problems. The IB method utilizes an Eulerian discretization for the fluid equations of motion while maintaining a Lagrangian representation of structural objects. Operators are defined for transmitting information (forces and velocities) between these two representations. Read More

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January 2013

Convergence of adaptive BEM for some mixed boundary value problem.

Appl Numer Math 2012 Apr;62(4):226-245

Institute for Analysis and Scientific Computing, Vienna University of Technology, Wiedner Hauptstraße 8-10, A-1040 Wien, Austria.

For a boundary integral formulation of the 2D Laplace equation with mixed boundary conditions, we consider an adaptive Galerkin BEM based on an [Formula: see text]-type error estimator. We include the resolution of the Dirichlet, Neumann, and volume data into the adaptive algorithm. In particular, an implementation of the developed algorithm has only to deal with discrete integral operators. Read More

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Estimator reduction and convergence of adaptive BEM.

Appl Numer Math 2012 Jun;62(6):787-801

Vienna University of Technology, Institute for Analysis and Scientific Computing, Wiedner Hauptstr. 8-10, 1040 Wien, Austria.

A posteriori error estimation and related adaptive mesh-refining algorithms have themselves proven to be powerful tools in nowadays scientific computing. Contrary to adaptive finite element methods, convergence of adaptive boundary element schemes is, however, widely open. We propose a relaxed notion of convergence of adaptive boundary element schemes. Read More

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Accuracy and run-time comparison for different potential approaches and iterative solvers in finite element method based EEG source analysis.

Appl Numer Math 2009 Aug;59(8):1970-1988

Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA.

Accuracy and run-time play an important role in medical diagnostics and research as well as in the field of neuroscience. In Electroencephalography (EEG) source reconstruction, a current distribution in the human brain is reconstructed noninvasively from measured potentials at the head surface (the EEG inverse problem). Numerical modeling techniques are used to simulate head surface potentials for dipolar current sources in the human cortex, the so-called EEG forward problem. Read More

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