Journal Article

FZJ-2020-02122

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Hybrid datasets: Incorporating experimental data into Lattice-Boltzmann simulations

Morrison, H. E. ; Lintermann, A.FZJ* ; Grundmann, S. (Corresponding author)

2020
Wiley Hoboken, NJ

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Please use a persistent id in citations: http://hdl.handle.net/2128/25148  doi:10.1002/eng2.12177

Abstract: A novel method, which combines both fluid-mechanical experimental and numerical data from magnetic resonance velocimetry and Lattice-Boltzmann (LB) simulations is presented. The LB method offers a unique and simple way of integrating the experimental data into the simulation by means of its equilibrium term. The simulation is guided by the experimental data, while at the same time potential outliers or noisy data are physically smoothed. In addition, the simulation allows to increase the resolution and to obtain further physical quantities, which are not measurable in the experiment. For a benchmark case, temporally averaged velocity data is included into the simulation. The proposed model creates a hybrid dataset, which satisfies the Reynolds-averaged Navier-Stokes equations, including the correctly deduced contribution from the Reynolds stress tensor.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)

Appears in the scientific report 2020

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