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Application of an Evolutionary Algorithm to LES Modelling of Turbulent Premixed Flames

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Data Analysis for Direct Numerical Simulations of Turbulent Combustion

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Abstract

Gene Expression Programming (GEP) has been used successfully for modelling the unclosed terms in the context of Reynolds Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES)-based turbulence modelling. In contrast to deep-learning-based methodologies, this approach has the advantage that the model can be documented in the form of a mathematical expression; it can be interpreted and easily implemented in existing solvers. Recently, application of GEP to a priori LES modelling has demonstrated the efficiency of the approach to find high fidelity LES closures. The present contribution explains the methodology, reviews recent work in the field and focuses on the robustness of the method and the scope for future efficiency improvements, by applying it to the modelling of the unclosed stress tensor in turbulent premixed statistically planar flames.

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Notes

  1. 1.

    The indices are omitted for better readability.

References

  1. M. Schoepplein, J. Weatheritt, R. Sandberg, M. Talei, M. Klein, Application of an evolutionary algorithm to LES modelling of turbulent transport in premixed flames. J. Comput. Phys. 374, 1166–1179 (2018)

    Article  MathSciNet  Google Scholar 

  2. J. Weatheritt, R. Sandberg, A novel evolutionary algorithm applied to algebraic modifications of the RANS stress strain relationship. J. Comput. Phys. 325, 22–37 (2016)

    Article  MathSciNet  Google Scholar 

  3. J. Weatheritt, R.D. Sandberg, The development of algebraic stress models using a novel evolutionary algorithm. Int. J. Heat Fluid Flow 68, 298–318 (2017)

    Article  Google Scholar 

  4. S.B. Pope, A more general effective-viscosity hypothesis. J. Fluid Mech. 75, 331–340 (1975)

    Article  Google Scholar 

  5. J.H. Holland, Adaptation in Natural and Artificial Systems (1975)

    Google Scholar 

  6. Genetic Algorithms, https://www.geeksforgeeks.org/genetic-algorithms/. Accessed 16 Jun 2019

  7. J.R. Koza, Genetic Programming II: Automatic Discovery of Reusable Programs (1994)

    Google Scholar 

  8. J.R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection (1992)

    Google Scholar 

  9. C. Ferreira, Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst. 13, 87–129 (2001)

    MathSciNet  MATH  Google Scholar 

  10. M. Klein, C. Kasten, N. Chakraborty, Y. Gao, A-priori direct numerical simulation assessment of sub-grid scale stress tensor closures for turbulent premixed combustion. Comput. Fluids 122, 1–11 (2015)

    Article  MathSciNet  Google Scholar 

  11. J. Weatheritt, R.D. Sandberg, Hybrid Reynolds-averaged/large-eddy simulation methodology from symbolic regression: formulation and application. AIAA J. (2017)

    Google Scholar 

  12. K. Jenkins, R. Cant, DNS of turbulent flame kernels, in Proceedings of 2nd AFOSR Conference on DNS and LES, ed. by C. Liu, L. Sakell, T. Beautner (Kluwer Academic Publishers, 1999), pp. 192–202

    Google Scholar 

  13. R.S. Rogallo, NASA Technical Memorandum 81315 (NASA Ames Research Center, 1981)

    Google Scholar 

  14. B.P. Pope, Turbulent Flows (Cambridge University Press, Cambridge, 2000)

    Google Scholar 

  15. M. Klein, N. Chakraborty, S. Ketterl, A comparison of strategies for direct numerical simulation of turbulence chemistry interaction in generic planar turbulent premixed flames. Flow Turbul. Combust. 1–17 (2017)

    Google Scholar 

  16. Y. Gao, N. Chakraborty, M. Klein, Assessment of sub-grid scalar flux modelling in premixed flames for large eddy simulations. Eur. J. Mech. - B/Fluids 52, 97–108 (2015)

    Article  Google Scholar 

  17. M. Klein, N. Chakraborty, Y. Gao, Scale similarity based models and their application to subgrid scale scalar flux modelling in the context of turbulent premixed flames. Int. J. Heat Fluid Flow 57, 91–108 (2016)

    Article  Google Scholar 

  18. A.J.M. Spencer, R.S. Rivlin, The theory of matrix polynomials and its application to the mechanics of isotropic continua, in Collected Papers of R.S. Rivlin (Springer, Berlin, 1997)

    Chapter  Google Scholar 

  19. M. Klein, C. Kasten, N. Chakraborty, A-priori direct numerical simulation assessment of models for generalized sub-grid scale turbulent kinetic energy in turbulent premixed flames. Comput. Fluids 154, 123–131 (2017)

    Article  MathSciNet  Google Scholar 

  20. D. Veynante, A. Trouve, K. Bray, T. Mantel, Gradient and counter-gradient scalar transport in turbulent premixed flames. J. Fluid Mech. 332, 263–293 (1997)

    Article  Google Scholar 

  21. R.A. Clark, J.H. Ferziger, W. Reynolds, Evaluation of subgrid-scale models using an accurately simulated turbulent flow. J. Fluid Mech. 91, 1–16 (2017)

    Article  Google Scholar 

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Acknowledgements

The stay abroad of M.S. was supported by the Federal Ministry of Defence.

Author information

Authors and Affiliations

  1. Department of Aerospace Engineering, Bundeswehr University Munich, Neubiberg, Germany

    M. Schöpplein & M. Klein

  2. Department of Mechanical Engineering, University of Melbourne, Parkville, VIC, 3010, Australia

    J. Weatheritt, M. Talei & R. D. Sandberg

Authors
  1. M. Schöpplein
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  2. J. Weatheritt
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  3. M. Talei
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  4. M. Klein
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  5. R. D. Sandberg
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Corresponding author

Correspondence to M. Klein .

Editor information

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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Schöpplein, M., Weatheritt, J., Talei, M., Klein, M., Sandberg, R.D. (2020). Application of an Evolutionary Algorithm to LES Modelling of Turbulent Premixed Flames. 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_13

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