Large eddy simulation/dynamic thickened flame modeling of a high Karlovitz number turbulent premixed jet flame
Abstract
Due to the complex multiscale interaction between intense turbulence and relatively weak flames, turbulent premixed flames in the thin and broken reaction zones regimes exhibit strong finite-rate chemistry and strain effects and are hence challenging to model. Here, in this paper, a laboratory premixed jet flame in the broken reaction zone, which has recently been studied using direct numerical simulation (DNS), is modeled using a large eddy simulation (LES)/dynamic thickened flame (DTF) approach with detailed chemistry. The presence of substantial flame thickening due to strong turbulence-chemistry interactions, which can be characterized by a high Karlovitz number (Ka), requires the DTF model to thicken the flame in an adaptive way based on the local resolution of flame scales. Here, an appropriate flame sensor and strain-sensitive flame thickness are used to automatically determine the thickening location and thickening factor, respectively. To account for finite-rate chemistry and strain effects, the chemistry is described in two different ways: (1) detailed chemistry denoted as full transport and chemistry (FTC), and (2) tabulated chemistry based on a strained premixed flamelet (SPF) model. The performance of the augmented LES/DTF approach for modeling the high Ka premixed flame is assessed through detailed a posteriori comparisons with DNS ofmore »
- Authors:
-
- Institute for Simulation of reactive Thermo-Fluid Systems, TU Darmstadt (Germany)
- The University of New South Wales, NSW (Australia)
- Institute for Energy and Power Plant Technology, TU Darmstadt (Germany)
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences, and Biosciences Division; USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1497652
- Report Number(s):
- SAND-2017-13325J
Journal ID: ISSN 1540-7489; 672181
- Grant/Contract Number:
- AC04-94AL85000; NA0003525
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Proceedings of the Combustion Institute
- Additional Journal Information:
- Journal Volume: 37; Journal Issue: 2; Journal ID: ISSN 1540-7489
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42 ENGINEERING; High Karlovitz number; Large eddy simulation; Dynamic thickened flame; Strained premixed flamelet model; Pollutant emissions
Citation Formats
Han, Wang, Wang, Haiou, Kuenne, Guido, Hawkes, Evatt R., Chen, Jacqueline H., Janicka, Johannes, and Hasse, Christian. Large eddy simulation/dynamic thickened flame modeling of a high Karlovitz number turbulent premixed jet flame. United States: N. p., 2018.
Web. doi:10.1016/j.proci.2018.06.228.
Han, Wang, Wang, Haiou, Kuenne, Guido, Hawkes, Evatt R., Chen, Jacqueline H., Janicka, Johannes, & Hasse, Christian. Large eddy simulation/dynamic thickened flame modeling of a high Karlovitz number turbulent premixed jet flame. United States. https://doi.org/10.1016/j.proci.2018.06.228
Han, Wang, Wang, Haiou, Kuenne, Guido, Hawkes, Evatt R., Chen, Jacqueline H., Janicka, Johannes, and Hasse, Christian. Tue .
"Large eddy simulation/dynamic thickened flame modeling of a high Karlovitz number turbulent premixed jet flame". United States. https://doi.org/10.1016/j.proci.2018.06.228. https://www.osti.gov/servlets/purl/1497652.
@article{osti_1497652,
title = {Large eddy simulation/dynamic thickened flame modeling of a high Karlovitz number turbulent premixed jet flame},
author = {Han, Wang and Wang, Haiou and Kuenne, Guido and Hawkes, Evatt R. and Chen, Jacqueline H. and Janicka, Johannes and Hasse, Christian},
abstractNote = {Due to the complex multiscale interaction between intense turbulence and relatively weak flames, turbulent premixed flames in the thin and broken reaction zones regimes exhibit strong finite-rate chemistry and strain effects and are hence challenging to model. Here, in this paper, a laboratory premixed jet flame in the broken reaction zone, which has recently been studied using direct numerical simulation (DNS), is modeled using a large eddy simulation (LES)/dynamic thickened flame (DTF) approach with detailed chemistry. The presence of substantial flame thickening due to strong turbulence-chemistry interactions, which can be characterized by a high Karlovitz number (Ka), requires the DTF model to thicken the flame in an adaptive way based on the local resolution of flame scales. Here, an appropriate flame sensor and strain-sensitive flame thickness are used to automatically determine the thickening location and thickening factor, respectively. To account for finite-rate chemistry and strain effects, the chemistry is described in two different ways: (1) detailed chemistry denoted as full transport and chemistry (FTC), and (2) tabulated chemistry based on a strained premixed flamelet (SPF) model. The performance of the augmented LES/DTF approach for modeling the high Ka premixed flame is assessed through detailed a posteriori comparisons with DNS of the same flame. It is found that the LES/DTF/FTC model is capable of reproducing most features of the high Ka turbulent premixed flame including accurate CO and NO prediction. The LES/DTF/SPF model has the potential to capture the impact of strong turbulence on the flame structure and provides reasonable prediction of pollutant emissions at a reasonable computational cost. In order to identify the impact of aerodynamic strain, the turbulent flame structure is analyzed and compared with unstrained and strained premixed flamelet solutions. Lastly, the results indicate that detailed strain effects should be considered when using tabulated methods to model high Ka premixed flames.},
doi = {10.1016/j.proci.2018.06.228},
journal = {Proceedings of the Combustion Institute},
number = 2,
volume = 37,
place = {United States},
year = {Tue Jul 17 00:00:00 EDT 2018},
month = {Tue Jul 17 00:00:00 EDT 2018}
}
Web of Science
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