A Clustering Method for Identifying Regions of Interest in Turbulent Combustion Tensor Fields

  • Adrian Maries
  • Timothy Luciani
  • P. H. Pisciuneri
  • Mehdi B. Nik
  • S. Levent Yilmaz
  • Peyman Givi
  • G. Elisabeta MaraiEmail author
Part of the Mathematics and Visualization book series (MATHVISUAL)


Production of electricity and propulsion systems involve turbulent combustion. Computational modeling of turbulent combustion can improve the efficiency of these processes. However, large tensor datasets are the result of such simulations; these datasets are difficult to visualize and analyze. In this work we present an unsupervised statistical approach for the segmentation, visualization and potentially the tracking of regions of interest in large tensor data. The approach employs a machine learning clustering algorithm to locate and identify areas of interest based on specified parameters such as strain tensor value. Evaluation on two combustion datasets shows this approach can assist in the visual analysis of the combustion tensor field.


Mach Number Large Eddy Simulation Direct Numerical Simulation Tensor Field Turbulent Combustion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by NSF CBET-1250171 and NSF CAREER IIS-0952720.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Adrian Maries
    • 1
  • Timothy Luciani
    • 2
  • P. H. Pisciuneri
    • 3
  • Mehdi B. Nik
    • 4
  • S. Levent Yilmaz
    • 5
  • Peyman Givi
    • 4
  • G. Elisabeta Marai
    • 6
    Email author
  1. 1.Learning Research and Development CenterUniversity of PittsburghPittsburghUSA
  2. 2.Department of Computer ScienceBrown UniversityProvidenceUSA
  3. 3.Center for Simulation and ModelingUniversity of PittsburghPittsburghUSA
  4. 4.Department of Mechanical Engineering and Materials ScienceUniversity of PittsburghPittsburghUSA
  5. 5.MathworksNatickUSA
  6. 6.Department of Computer ScienceUniversity of Illinois at ChicagoChicagoUSA

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