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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Lomonova, Elena A.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (5/5 displayed)

  • 2023Physics-informed neural networks for modelling anisotropic and bi-anisotropic electromagnetic constitutive laws through indirect data3citations
  • 2021Vector hysteresis modeling coupled with a loop-based magnetic equivalent circuit3citations
  • 2020Hysteresis and loss prediction for high-permeability grain-oriented electrical Steel by Material Characterization1citations
  • 2020Coupled statistical and dynamic loss prediction of high-permeability grain-oriented electrical steel4citations
  • 2012Analytical field calculations of skewed magnetscitations

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Chart of shared publication
Tiels, Koen
1 / 2 shared
Chandra, Abhishek
1 / 2 shared
Curti, Mitrofan
1 / 1 shared
Tartakovsky, Daniel M.
1 / 1 shared
Boynov, Konstantin O.
1 / 1 shared
Zeinali, Reza
1 / 2 shared
Daniels, Bram
3 / 3 shared
Ceylan, Doğa
1 / 1 shared
Overboom, Timo
2 / 2 shared
Kremers, M. F. J.
1 / 1 shared
Paulides, Johannes
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Janssen, J. L. G.
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Ilhan Caarls, Esin
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Co-Authors (by relevance)

  • Tiels, Koen
  • Chandra, Abhishek
  • Curti, Mitrofan
  • Tartakovsky, Daniel M.
  • Boynov, Konstantin O.
  • Zeinali, Reza
  • Daniels, Bram
  • Ceylan, Doğa
  • Overboom, Timo
  • Kremers, M. F. J.
  • Paulides, Johannes
  • Janssen, J. L. G.
  • Ilhan Caarls, Esin
OrganizationsLocationPeople

document

Hysteresis and loss prediction for high-permeability grain-oriented electrical Steel by Material Characterization

  • Overboom, Timo
  • Lomonova, Elena A.
  • Daniels, Bram
Abstract

For loss prediction of a transformer it is required to model the loss of its core, constructed out of high-permeability grain-oriented electrical steel (HiB GOES). This work predicts the magnetic loss in the rolling direction (RD) of a sheet of H105-30 HiB GOES for flux densities up to 1.9 T, and frequencies up to 300 Hz. Material characterization parameters, obtained by statistical loss separation for sinusoidal excitation, are applied in a hysteresis model to predict dynamic behavior, from which the loss is determined. This dynamic behavior is solely determined by material characterization. The maximum error for the predicted loss is 4.74%, the RMS error is 2.22% ({B}.5T, f=50 Hz).

Topics
  • impedance spectroscopy
  • grain
  • steel
  • permeability
  • iron