fyp2012 / wall_modeling

Development of OpenFOAM wall functions for turbulent flows

Development of wall functions for turbulent flows

The repository is structured as follows:

• test_cases: OpenFOAM simulation setups
• notebooks: Jupyter notebooks for post-processing of results and other visualizations

Getting started

Compiling the wall function and running the test cases requires an installation of OpenFOAM-v2012. Other releases might work as well but have not been tested.

To run a test case, create a run folder (ignored by version control), copy the case from test_cases to run, and execute the Allrun script.

mkdir -p run
cp -r test_cases/turbulentFlatPlate run/
cd run/turbulentFlatPlate
./Allrun

Singularity and SLURM

Singularity is a container tool that allows making results reproducible and performing simulations, to a large extent, platform independent. The only remaining dependencies are Singularity itself and Open-MPI (see next section for further comments). To build the image, run:

sudo singularity build of_v2012.sif docker://andreweiner/of_pytorch:of2012-py1.7.1-cpu

To run a simulation with Singularity, use the dedicated Allrun.singularity scripts. TU Braunschweig's HPC uses the SLURM scheduler. The repository contains an annotated example jobscript. The script expects the Singularity image in the top level directory of this repository and the simulation folder in run. To submit a job, run:

sbatch jobscript name_of_simulation

To show all running jobs of a user, use squeue -u $USER. Another helpful command is quota -s to check the available disk space.

References

The basic ideas of this work were first developed in the context of mass transfer at rising bubbles. Instead of the turbulent viscosity, the molecular diffusivity of a chemical species is corrected to mitigate the so-called high-Schmidt number problem. The profile function's parameter is determined by the species mass in an interface cell.

@article{weiner2017,
title = {Advanced subgrid-scale modeling for convection-dominated species transport at fluid interfaces with application to mass transfer from rising bubbles},
journal = {Journal of Computational Physics},
volume = {347},
pages = {261-289},
year = {2017},
issn = {0021-9991},
doi = {https://doi.org/10.1016/j.jcp.2017.06.040},
author = {Andre Weiner and Dieter Bothe}
}

In the following reference, the ideas above were first implemented in OpenFOAM and applied to surfactant adsorption rising bubbles.

@article{pesci2018,
title={Computational analysis of single rising bubbles influenced by soluble surfactant},
volume={856},
DOI={10.1017/jfm.2018.723},
journal={Journal of Fluid Mechanics},
publisher={Cambridge University Press},
author={Pesci, Chiara and Weiner, Andre and Marschall, Holger and Bothe, Dieter},
year={2018},
pages={709–763}
}

Instead of an analytical profile function, one can also use a machine learning model to correct diffusive and convective fluxes.

@article{weiner2019,
author = {Weiner, Andre and Hillenbrand, Dennis and Marschall, Holger and Bothe, Dieter},
title = {Data-Driven Subgrid-Scale Modeling for Convection-Dominated Concentration Boundary Layers},
journal = {Chemical Engineering \& Technology},
volume = {42},
number = {7},
pages = {1349-1356},
keywords = {Data-driven modeling, High Schmidt numbers, Machine learning, Reactive mass transfer, Subgrid-scale modeling},
doi = {https://doi.org/10.1002/ceat.201900044},
year = {2019}
}

The following two PhD theses contain more detailed descriptions as well as more extensive parameter studies and applications than the references above. pesci2019 focuses more on surfactants and mass transfer while weiner2020 addresses the modeling principles and extensions to reactive mass transfer by means of machine learning.

@phdthesis{weiner2020,
          school = {Technical University of Darmstadt, Mathematical Modeling and Analysis},
         address = {Darmstadt},
           month = {February},
           title = {Modeling and simulation of convection-dominated species transfer at rising bubbles},
          author = {Andre Weiner},
            year = {2020},
             url = {http://tuprints.ulb.tu-darmstadt.de/11405/}
}
@phdthesis{pesci2019,
            year = {2019},
          author = {Chiara Pesci},
         address = {Darmstadt},
           title = {Computational Analysis of Fluid Interfaces Influenced by Soluble Surfactant},
           month = {July},
          school = {Technische Universit{\"a}t},
             url = {http://tuprints.ulb.tu-darmstadt.de/9303/}
}

Get in touch

The easiest and quickest way to get in touch is to open an issue in this repository.