| 1. |
- Fiorina, B., et al.
(author)
-
Challenging modeling strategies for LES of non-adiabatic turbulent stratified combustion
- 2015
-
In: Combustion and Flame. - : Elsevier BV. - 0010-2180 .- 1556-2921. ; 162:11, s. 4264-4282
-
Journal article (peer-reviewed)abstract
- Five different low-Mach large eddy simulations are compared to the turbulent stratified flame experiments conducted at the Technical University of Darmstadt (TUD). The simulations were contributed by TUD, the Institute for Combustion Technology (ITV) at Aachen, Lund University (LUND), the EM2C laboratory at Ecole Centrale Paris, and the University of Duisburg-Essen (UDE). Combustion is modeled by a premixed flamelet tabulation with local flame thickening (TUD), a premixed flamelet progress variable approach coupled to a level set method (ITV), a 4-steps mechanism combined with implicit LES (LUND), the F-TACLES model that is based on filtered premixed flamelet tabulation (EM2C), and a flame surface density approach (UDE). An extensive comparison of simulation and experimental data is presented for the first two moments of velocity, temperature, mixture fraction, and major species mass fractions. The importance of heat-losses was assessed by comparing simulations for adiabatic and isothermal boundary conditions at the burner walls. The adiabatic computations predict a flame anchored on the burner lip, while the non-adiabatic simulations show a flame lift-off of one half pilot diameter and a better agreement with experimental evidence for temperature and species concentrations. Most simulations agree on the mean flame brush position, but it is evident that subgrid turbulence must be considered to achieve the correct turbulent flame speed. Qualitative comparisons of instantaneous snapshots of the flame show differences in the size of the resolved flame wrinkling patterns. These differences are (a) caused by the influence of the LES combustion model on the flame dynamics and (b) by the different simulation strategies in terms of grid, inlet condition and numerics. The simulations were conducted with approaches optimized for different objectives, for example low computational cost, or in another case, short turn around. (C) 2015 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
|
|
