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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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2005A genetic algorithm evolving charging programs in the ironmaking blast furnace17citations

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Pettersson, Frank
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Saxén, Henrik
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2005

Co-Authors (by relevance)

  • Pettersson, Frank
  • Saxén, Henrik
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article

A genetic algorithm evolving charging programs in the ironmaking blast furnace

  • Hinnelä, Jan
  • Pettersson, Frank
  • Saxén, Henrik
Abstract

<p>In the ironmaking blast furnace, the distribution of the charged burden plays an important role because it influences the gas distribution in the shaft and the shape and the position of the cohesive zone. Because of enormous mechanical wear and high temperatures and pressure, the possibilities to reliably measure the distribution in real time are severely limited. Even though devices that provide information about the burden surface level have been developed, the high investment and maintenance costs make them economically infeasible in small or medium-size blast furnaces. A simplified first-principles model of the burden distribution forms the basis of the work presented in this article. A method is proposed by which a desired radial ore-to-coke distribution can be achieved by developing charging programs by a genetic algorithm, which was found to be a technique that can tackle this complex and nondifferentiable optimization problem. The algorithm evolves different charging programs subject to practical constraints of the charging (such as maximum skip size and movable armor spans), with the goal to find a charging program that minimizes the differences between the desired and calculated burden distribution. The article describes the method and presents a few illustrative examples on charging programs evolved by it.</p>

Topics
  • impedance spectroscopy
  • surface