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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Materials Map under construction

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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1.080 Topics available

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977 Locations available

693.932 PEOPLE
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University of Bristol

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 2021A route to sustainable aviation28citations
  • 2017Test Characterization of a High Performance Fault Tolerant Permanent Magnet Machine2citations
  • 2015STRUCTURAL MAGNETIC COMPOSITES FOR USE IN ELECTRO-MECHANICAL APPLICATIONScitations
  • 2015STRUCTURAL MAGNETIC COMPOSITES FOR USE IN ELECTRO-MECHANICAL APPLICATIONScitations

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Allegri, Giuliano
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2017
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Co-Authors (by relevance)

  • Allegri, Giuliano
  • Norman, Patrick
  • Jones, Catherine
  • Trask, Richard S.
  • Hamerton, Ian
  • Burt, Graeme
  • Hill, Callum
  • Baker, James
  • Wrobel, Rafal
  • Mellor, Phil
  • Williamson, Sam
  • Edwards, Laura
  • Bond, Ip
  • Bond, Ian
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document

Test Characterization of a High Performance Fault Tolerant Permanent Magnet Machine

  • Baker, James
  • Wrobel, Rafal
  • Mellor, Phil
  • Williamson, Sam
  • Yon, Jason
Abstract

It is well understood that an electric machine’s output performance is limited by its losses and thermal behavior. For novel prototype machines, hardware testing processes are an important part of quantifying these parameters. For some machines, effective characterization may be accomplished using a series of static and simple prime-mover tests. The resulting data permits calibration of loss- and thermal-models. These can then be used to predict on-load performance. Fault-tolerant machines based on single layer winding arrangements are designed to minimize interaction between windings or module-groups. This paper demonstrates that, for such a machine, the losses measured during simple DC and primer-mover tests may be used to infer performance during both ‘healthy’ and ‘faulted’ operating modes. Under faulted conditions the total machine loss is expected to be a combination of module-specific and common losses, which can be directly deduced from hardware tests. This paper discusses the accuracy of loss superposition when applied to a 180 kW multi-channel, fault-tolerant aerospace machine. From observations following faulted and healthy dynamometry tests, there exists close correlation between full-load performance and estimates made from the superposition of losses under discrete operating modes.

Topics
  • impedance spectroscopy