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Parallel-in-space-and-time finite-element analysis of electric machines using time step overlapping in a massively parallel computing environment

Parallel-in-space-and-time finite-element analysis of electric machines using time step... This study aims to enhance the parallel performance of a parallel-in-space-and-time (PinST) finite-element method (FEM) using time step overlapping. The effectiveness of the developed method is clarified in a magnet eddy-current loss analysis of a practical interior permanent magnet synchronous motor (IPMSM) using a massively parallel computing environment.Design/methodology/approachThe developed PinST FEM is a combination of the domain decomposition method as a parallel-in-space (PinS) method and a parallel time-periodic explicit error correction (PTP-EEC) method, which is one of the parallel-in-time (PinT) approaches. The parallel performance of the PinST FEM is further improved by overlapping the time steps with different processes in the PTP-EEC method.FindingsBy applying the overlapping PTP-EEC method, the convergence of the transient solution to its steady state can be accelerated drastically. Consequently, the good parallel performance of the PinST FEM is achieved in magnetic field analyses of the practical IPMSM using a massively parallel computing environment, in which over 10,000 processes are used.Originality/valueIn this study, the PinST FEM based on time step overlapping is newly developed and its effectiveness is demonstrated in a massively parallel computing environment, in which using either the PinS or PinT method alone cannot achieve sufficient parallel performance. This finding implies a new direction of parallel computing approaches for electromagnetic field computation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering Emerald Publishing

Parallel-in-space-and-time finite-element analysis of electric machines using time step overlapping in a massively parallel computing environment

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References (24)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0332-1649
eISSN
0332-1649
DOI
10.1108/compel-04-2022-0161
Publisher site
See Article on Publisher Site

Abstract

This study aims to enhance the parallel performance of a parallel-in-space-and-time (PinST) finite-element method (FEM) using time step overlapping. The effectiveness of the developed method is clarified in a magnet eddy-current loss analysis of a practical interior permanent magnet synchronous motor (IPMSM) using a massively parallel computing environment.Design/methodology/approachThe developed PinST FEM is a combination of the domain decomposition method as a parallel-in-space (PinS) method and a parallel time-periodic explicit error correction (PTP-EEC) method, which is one of the parallel-in-time (PinT) approaches. The parallel performance of the PinST FEM is further improved by overlapping the time steps with different processes in the PTP-EEC method.FindingsBy applying the overlapping PTP-EEC method, the convergence of the transient solution to its steady state can be accelerated drastically. Consequently, the good parallel performance of the PinST FEM is achieved in magnetic field analyses of the practical IPMSM using a massively parallel computing environment, in which over 10,000 processes are used.Originality/valueIn this study, the PinST FEM based on time step overlapping is newly developed and its effectiveness is demonstrated in a massively parallel computing environment, in which using either the PinS or PinT method alone cannot achieve sufficient parallel performance. This finding implies a new direction of parallel computing approaches for electromagnetic field computation.

Journal

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering – Emerald Publishing

Published: Jan 20, 2023

Keywords: Electrical machine; Iron losses; Finite element method; Computational electromagnetics; Domain decomposition method

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