Performance of low-rank QR approximation of the finite element Biot-Savart law

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We are concerned with the computation of magnetic fields from known electric currents in the finite element setting. In finite element eddy current simulations it is necessary to prescribe the magnetic field (or potential, depending upon the formulation) on the conductor boundary. In situations where the magnetic field is due to a distributed current density, the Biot-Savart law can be used, eliminating the need to mesh the nonconducting regions. Computation of the Biot-Savart law can be significantly accelerated using a low-rank QR approximation. We review the low-rank QR method and report performance on selected problems.

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White, D A & Fasenfest, B J January 12, 2006.

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We are concerned with the computation of magnetic fields from known electric currents in the finite element setting. In finite element eddy current simulations it is necessary to prescribe the magnetic field (or potential, depending upon the formulation) on the conductor boundary. In situations where the magnetic field is due to a distributed current density, the Biot-Savart law can be used, eliminating the need to mesh the nonconducting regions. Computation of the Biot-Savart law can be significantly accelerated using a low-rank QR approximation. We review the low-rank QR method and report performance on selected problems.

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PDF-file: 3 pages; size: 0 Kbytes

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  • Presented at: 12th Biennial IEEE Conference on Electromagnetic Field Computation, Miami, FL, United States, Apr 30 - May 03, 2006

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  • Report No.: UCRL-CONF-218238
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 885135
  • Archival Resource Key: ark:/67531/metadc874844

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Office of Scientific & Technical Information Technical Reports

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  • January 12, 2006

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  • Sept. 21, 2016, 2:29 a.m.

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  • Nov. 30, 2016, 4:20 p.m.

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White, D A & Fasenfest, B J. Performance of low-rank QR approximation of the finite element Biot-Savart law, article, January 12, 2006; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc874844/: accessed December 17, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.