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Towards Solving Fluid Flow Domain Identification Problems with Adjoint Lattice Boltzmann Methods

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High Performance Computing in Science and Engineering ´16

Abstract

A novel strategy towards solving fluid flow domain identification problems for incompressible Newtonian fluids is proposed and investigated in this paper. The resulting numerical approach is of great importance for academic studies as well as for medical and industrial applications. For example, it can be used in combination with Phase Contrast MRI measurements to characterise flow dynamics as well as flow domains highly accurately. The problem is formulated as a optimisation problem which minimised the distance between a given and a simulated flow field, whereby the latter one is the solution of a parameterised porous media BGK-Boltzmann model. The parameter represents the porosity distributed in the domain and its distribution is obtained as the final result of the optimisation problem. The proposed gradient-based solution strategy makes use of an adjoint lattice Boltzmann method (ALBM). Due to their similar structure to lattice Boltzmann methods (LBM), they also show excellent parallelisation behaviour. In this preliminary work, first validation results are presented as well as performance results and improvements for both single core and parallel implementation. In particular, with a simple domain identification test case a cube is being identified by position and shape inside a wind tunnel in only few optimisation steps, even with only partial flow data being available.

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Notes

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    www.openlb.net

  2. 2.

    https://www.scc.kit.edu/dienste/forhlr.php/

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Authors and Affiliations

  1. Institute for Mechanical Process Engineering and Mechanics, Institute for Applied and Numerical Mathematics, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Mathias J. Krause & Benjamin Förster

  2. Institute for Mechanical Process Engineering and Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Albert Mink & Hermann Nirschl

Authors
  1. Mathias J. Krause
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  2. Benjamin Förster
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  3. Albert Mink
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  4. Hermann Nirschl
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Correspondence to Mathias J. Krause .

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Editors and Affiliations

  1. Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universität Dresden, Dresden, Germany

    Wolfgang E. Nagel

  2. Abteilung für Angewandte Mathematik, Universität Freiburg, Freiburg, Germany

    Dietmar H. Kröner

  3. Höchstleistungsrechenzentrum Stuttgart (HLRS), Universität Stuttgart, Stuttgart, Germany

    Michael M. Resch

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Krause, M.J., Förster, B., Mink, A., Nirschl, H. (2016). Towards Solving Fluid Flow Domain Identification Problems with Adjoint Lattice Boltzmann Methods. In: Nagel, W.E., Kröner, D.H., Resch, M.M. (eds) High Performance Computing in Science and Engineering ´16. Springer, Cham. https://doi.org/10.1007/978-3-319-47066-5_23

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