Abstract
Direct simulation of all the length and time scales relevant to practical combustion processes is computationally prohibitive. When combustion processes are driven by reaction and transport phenomena occurring at the unresolved scales of a numerical simulation, one must introduce a dynamic subgrid model that accounts for the multiscale nature of the problem using information available on a resolvable grid. Here, we discuss a model that captures unsteady flow-flame interactions- including extinction, re-ignition, and history effects-via embedded simulations at the subgrid level. The model efficiently accounts for subgrid flame structure and incorporates detailed chemistry and transport, allowing more accurate prediction of the stretch effect and the heat release. In this chapter we first review the work done in the past thirty years to develop the flame embedding concept. Next we present a formulation for the same concept that is compatible with Large Eddy Simulation in the flamelet regimes. The unsteady flame embedding approach (UFE) treats the flame as an ensemble of locally one-dimensional flames, similar to the flamelet approach. However, a set of elemental one-dimensional flames is used to describe the turbulent flame structure directly at the subgrid level. The calculations employ a one-dimensional unsteady flame model that incorporates unsteady strain rate, curvature, and mixture boundary conditions imposed by the resolved scales. The model is used for closure of the subgrid terms in the context of large eddy simulation. Direct numerical simulation (DNS) data from a flame-vortex interaction problem is used for comparison. © Springer Science+Business Media B.V. 2011.
Original language | English (US) |
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Title of host publication | Fluid Mechanics and Its Applications |
Publisher | Springer Nature |
Pages | 277-300 |
Number of pages | 24 |
ISBN (Print) | 9789400704114 |
DOIs | |
State | Published - 2011 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUS-11-010-01
Acknowledgements: This work is supported by the King Abdullah University of Science and Technology (KAUST), Award No. KUS-11-010-01. The authors also gratefully acknowledge the inspiring discussions and valuable comments from Suresh Menon, Heinz Pitsch, Tarek Echekki, Evatt R. Hawkes, R. Stewart Cant, Christopher Rutland, Youssef Marzouk, and Jean-Christophe Nave.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.