Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Nair, Bindu Gopinathan

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in Cooperation with on an Cooperation-Score of 37%

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  • 2009An analysis of the use of magnetic source tomography to measure the spatial distribution of electric current during vacuum arc remelting8citations

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Ward, Mark
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2009

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  • Ward, Mark
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article

An analysis of the use of magnetic source tomography to measure the spatial distribution of electric current during vacuum arc remelting

  • Nair, Bindu Gopinathan
  • Ward, Mark
Abstract

Magnetic source tomography is explored to analyse the distribution of electric current during vacuum arc remelting (VAR). The goal is to use sensors outside the process to deduce the behaviour within. VAR systems having non-axisymmetric distributions of arc current were modelled using a commercial finite element electromagnetic code (Opera 3d), and a database was created from the resulting patterns of magnetic flux predicted to occur outside the crucible. A reconstruction algorithm was developed using constrained nonlinear optimization to estimate the arc current distribution within the process from the magnetic field data outside. The capabilities of this algorithm were studied, and it was found that given sufficiently low noise in the measurement data it was possible to accurately deduce important features of the spatial distribution of the arc current.

Topics
  • impedance spectroscopy
  • tomography