A GPU-Accelerated Semi-Implicit Method for Large-Scale Nonlinear Eddy-Current Problems Using Adaptive Time Step Control

A transient magnetic vector potential formulation for nonlinear eddy-current problems and spatial finite element discretization form a system of nonlinear algebraic differential equations. Using Rosenbrock-Wanner (ROW) time integration methods, the system of nonlinear functions is solved with a series of linear systems of equations where the Jacobian matrix is kept constant during the entire time step. This makes ROW methods error-prone to larger time step sizes, wherefore the time step size must be controlled adaptively. To improve accuracy and reliability, the Jacobian matrix is determined exactly during the time step. For highly efficient simulations of large-scale problems, the process is accelerated using parallel computing and graphic processing units (GPUs).

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Publication Details

Journal
IEEE Transactions on Magnetics
Published
2024-11-19
DOI
https://doi.org/10.1109/tmag.2024.3502313
Primary Topic
Electromagnetic Simulation and Numerical Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

A GPU-Accelerated Semi-Implicit Method for Large-Scale Nonlinear Eddy-Current Problems Using Adaptive Time Step Control

Markus Clemens, Bernhard Kähne
IEEE Transactions on Magnetics
Electromagnetic Simulation and Numerical Methods
article

A GPU-Accelerated Semi-Implicit Method for Large-Scale Nonlinear Eddy-Current Problems Using Adaptive Time Step Control

Markus Clemens, Bernhard Kähne
article en

Abstract

A transient magnetic vector potential formulation for nonlinear eddy-current problems and spatial finite element discretization form a system of nonlinear algebraic differential equations. Using Rosenbrock-Wanner (ROW) time integration methods, the system of nonlinear functions is solved with a series of linear systems of equations where the Jacobian matrix is kept constant during the entire time step. This makes ROW methods error-prone to larger time step sizes, wherefore the time step size must be controlled adaptively. To improve accuracy and reliability, the Jacobian matrix is determined exactly during the time step. For highly efficient simulations of large-scale problems, the process is accelerated using parallel computing and graphic processing units (GPUs).

IEEE Transactions on MagneticsVol. 61(1)
University of Wuppertal (DE)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 82%
Electromagnetic Simulation and Numerical Methods
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