This repository provides advanced tutorial cases which demonstrate the scaling capability and computational efficiency of the DLBFoam library, a radically fast detailed chemistry solver for OpenFOAM.
The detailed discussion and validation of the provided tutorial cases are openly available in Ref. [1]
The provided tutorial cases represent the following:
As there are many more experimental benchmarks of various combustion phenomena that have not been tested, we would be happy to receive your contribution using the DLBFoam and reporting the speed-up and scaling effects against standard solvers.
If you use our tutorial cases, please cite the paper discussing these test cases [1], together with the original DLBFoam paper, also noted in Ref. [2].
[1] I. Morev, B. Tekgül, M. Gadalla, A. Shahanaghi, J. Kannan, S. Karimkashi, O. Kaario, V. Vuorinen, Fast reactive flow simulations using analytical Jacobian and dynamic load balancing in OpenFOAM, Physics of Fluids 34, 021801, doi:10.1063/5.0077437 (2022).
``` @article{Morev2022, doi = {10.1063/5.0077437}, url = {https://doi.org/10.1063/5.0077437}, year = {2022}, month = feb, publisher = {{AIP} Publishing}, volume = {34}, number = {2}, pages = {021801}, author = {Ilya Morev and Bulut Tekg\"{u}l and Mahmoud Gadalla and Ali Shahanaghi and Jeevananthan Kannan and Shervin Karimkashi and Ossi Kaario and Ville Vuorinen}, title = {Fast reactive flow simulations using analytical Jacobian and dynamic load balancing in {OpenFOAM}}, journal = {Physics of Fluids} } ```
[2] B. Tekgül, P. Peltonen, H. Kahila, O. Kaario, V. Vuorinen, DLBFoam: An open-source dynamic load balancing model for fast reacting flow simulations in OpenFOAM, Computer Physics Communications, Volume 267, doi:10.1016/j.cpc.2021.108073 (2021).
``` @article{tekgul2021dlbfoam, title={DLBFoam: An open-source dynamic load balancing model for fast reacting flow simulations in OpenFOAM}, author={Tekg{\"u}l, Bulut and Peltonen, Petteri and Kahila, Heikki and Kaario, Ossi and Vuorinen, Ville}, journal={Computer Physics Communications}, pages={108073}, year={2021}, publisher={Elsevier} } ```