Modeling of Particle Radiation Interaction in Solid Fuel Combustion with Artificial Neural Networks

  • Tim Gronarz Institute of Heat and Mass Transfer, RWTH Aachen, Germany http://orcid.org/0000-0002-0714-3800
  • Martin Habermehl Institute of Heat and Mass Transfer, RWTH Aachen, Germany
  • Reinhold Kneer Institute of Heat and Mass Transfer, RWTH Aachen, Germany

Abstract

In the present investigation, artificial neural networks are applied to model scattering and absorption properties occurring inparticle radiation interaction for numerical simulation of pulverized coal combustion. To determine averaged scattering andabsorption properties, an averaging procedure over spectral incident radiation profile and particle size distribution is applied.These averaged properties then are approximated by means of an artificial neural network. A study to determine a suitablenetwork architecture is performed.

Author Biographies

Tim Gronarz, Institute of Heat and Mass Transfer, RWTH Aachen, Germany
Researcher at the Institute of Heat and Mass Transfer, RWTH Aachen, Germany.
Martin Habermehl, Institute of Heat and Mass Transfer, RWTH Aachen, Germany
Leader of the groud "solid fuel combustion" at the Institute of Heat and Mass Transfer, RWTH Aachen, Germany.
Reinhold Kneer, Institute of Heat and Mass Transfer, RWTH Aachen, Germany
Professor, head of the Institute of Heat and Mass Transfer, RWTH Aachen, Germany.

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Published
2016-10-29
How to Cite
GRONARZ, Tim; HABERMEHL, Martin; KNEER, Reinhold. Modeling of Particle Radiation Interaction in Solid Fuel Combustion with Artificial Neural Networks. Journal of Power Technologies, [S.l.], v. 96, n. 3, p. 206--211, oct. 2016. ISSN 2083-4195. Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/886>. Date accessed: 22 dec. 2024.
Citation Formats
Issue
Vol 96 No 3 (2016)
Section
ICCHMT 2016 Cracow

Keywords

Scattering, absorption, Mie theory, artificial neural networks, function approximation
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