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institution

Siemens Energy

Germany

6 papers here45 citations across 6
fields
  • physics.chem-ph3
  • cs.AI1
  • eess.SY1
  • stat.AP1
ROR 01eccwj82OpenAlex

affiliations via OpenAlex

output
20132026
most citedToward Development of Machine Learned Techniques for Production of Compact Kinetic Models

22 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

  • G. Bourque3 · h 25
  • S. Dooley3 · h 36
  • Mark Kelly2 · h 4
  • Dominik Scheinert1 · h 11
  • Florian Schmidt1 · h 8
  • G. Rollmann1 · h 14
  • Harry Dunne1 · h 3
  • Helena Ebel1 · h 2
  • H. Gottschalk1 · h 20
  • Houkun Zhu1 · h 4
  • I. Tyuryukanov1 · h 7
  • J. Bos1 · h 9
collaborating institutions
  • Siemens (Canada)CA3 papers
  • Trinity College DublinIE3 papers
  • McGill UniversityCA2 papers
  • Siemens (Germany)DE2 papers
  • Delft University of TechnologyNL1 paper
  • Forschungszentrum JülichDE1 paper
  • Shandong UniversityCN1 paper
  • Technische Universität BerlinDE1 paper
  • Tennet (Netherlands)NL1 paper
  • Università della Svizzera italianaCH1 paper
  • University of WuppertalDE1 paper
Showing 2021 · physics.chem-phShow all

1 paper · 2 filters

physics.chem-ph2021★ 5 cited

Toward Machine Learned Highly Reduce Kinetic Models For Methane/Air Combustion

Mark Kelly, Gilles Bourque, Stephen Dooley

Accurate low dimension chemical kinetic models for methane are an essential component in the design of efficient gas turbine combustors. Kinetic models coupled to computational flu…

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