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Data-Driven Modal Decomposition Techniques for High-Dimensional Flow Fields

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Data Analysis for Direct Numerical Simulations of Turbulent Combustion

Abstract

Data-driven decomposition techniques are presented for the analysis and development of reduced-order models of complex flow dynamics. The Proper Orthogonal Decomposition (POD) produces optimal representations of the dynamics in the sense of the energy norm. Alternatively, Dynamic Mode Decomposition (DMD) efficiently extracts coherent dynamics based on eigendecompositions of linearized dynamics. An extension to the latter, the Higher Order Dynamic Mode Decomposition (HODMD) method uses time delays to develop efficient reduced models to represent complex dynamics in a nonintrusive manner. High-fidelity simulation results of a laboratory-scale single-element gas turbine combustor are used to demonstrate and evaluate the capabilities of the aforementioned decomposition techniques.

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Acknowledgements

This work is supported by funding from the National Science Foundation(NSF) Grant #1634709. Computational resources were provided by the Air Force Research Laboratories (AFRL). The authors would also like to acknowledge Shawou Pan for help with HODMD methodology.

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Authors and Affiliations

  1. Department of Aerospace Engineering, University of Michigan, 1320 Beal Ave, Ann Arbor, MI, 48109, USA

    Nicholas Arnold-Medabalimi, Cheng Huang & Karthik Duraisamy

Authors
  1. Nicholas Arnold-Medabalimi
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  2. Cheng Huang
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  3. Karthik Duraisamy
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Correspondence to Karthik Duraisamy .

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Editors and Affiliations

  1. Institute for Combustion Technology, RWTH Aachen University, Aachen, Germany

    Heinz Pitsch

  2. Institute for Combustion Technology, RWTH Aachen University, Aachen, Germany

    Antonio Attili

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Arnold-Medabalimi, N., Huang, C., Duraisamy, K. (2020). Data-Driven Modal Decomposition Techniques for High-Dimensional Flow Fields. In: Pitsch, H., Attili, A. (eds) Data Analysis for Direct Numerical Simulations of Turbulent Combustion. Springer, Cham. https://doi.org/10.1007/978-3-030-44718-2_7

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