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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Omar, Anas Al

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2021Hot working behaviour and processing maps of duplex cast steel2citations
  • 2014Characterization of hot flow behaviour and deformation stability of medium carbon microalloyed steel using artificial neural networks and dynamic material model5citations

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Chart of shared publication
Peña, Esteban
1 / 1 shared
Alcelay, Ignacio
2 / 2 shared
Prado, José Manuel
1 / 2 shared
Chart of publication period
2021
2014

Co-Authors (by relevance)

  • Peña, Esteban
  • Alcelay, Ignacio
  • Prado, José Manuel
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article

Characterization of hot flow behaviour and deformation stability of medium carbon microalloyed steel using artificial neural networks and dynamic material model

  • Omar, Anas Al
  • Alcelay, Ignacio
  • Prado, José Manuel
Abstract

<jats:title>Abstract</jats:title><jats:p>Artificial neural network (ANN) and dynamic material model (DMM) are considered to be powerful methods to characterize the flow behaviour of metallic materials. The aim of this study is to analyze the performance of these two methods in the characterization of flow behaviour and deformation stability of medium-carbon microalloyed steel. Flow curves obtained from hot compression tests have been used to describe the flow behaviour of the studied steel using an ANN model. Good correlation between experimental and predicted data was observed. To characterize the deformation stability of the studied steel, experimental processing maps are generated using DMM. Finally, in order to verify the accuracy of ANN results, processing maps based on the DMM have been developed using ANN predicted data. It has been found that these maps agree closely with those obtained using experimental data.</jats:p>

Topics
  • impedance spectroscopy
  • Carbon
  • steel
  • compression test