Large Eddy Simulation with tabulated chemistry of an experimental sidewall quenching burner

2018 ◽  
Vol 71 ◽  
pp. 95-110 ◽  
Author(s):  
A. Heinrich ◽  
F. Ries ◽  
G. Kuenne ◽  
S. Ganter ◽  
C. Hasse ◽  
...  
2021 ◽  
pp. 111730
Author(s):  
J. Benajes ◽  
J.M. García-Oliver ◽  
J.M. Pastor ◽  
I. Olmeda ◽  
A. Both ◽  
...  

Fluids ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 65 ◽  
Author(s):  
Arne Heinrich ◽  
Guido Kuenne ◽  
Sebastian Ganter ◽  
Christian Hasse ◽  
Johannes Janicka

Combustion will play a major part in fulfilling the world’s energy demand in the next 20 years. Therefore, it is necessary to understand the fundamentals of the flame–wall interaction (FWI), which takes place in internal combustion engines or gas turbines. The FWI can increase heat losses, increase pollutant formations and lowers efficiencies. In this work, a Large Eddy Simulation combined with a tabulated chemistry approach is used to investigate the transient near wall behavior of a turbulent premixed stoichiometric methane flame. This sidewall quenching configuration is based on an experimental burner with non-homogeneous turbulence and an actively cooled wall. The burner was used in a previous study for validation purposes. The transient behavior of the movement of the flame tip is analyzed by categorizing it into three different scenarios: an upstream, a downstream and a jump-like upstream movement. The distributions of the wall heat flux, the quenching distance or the detachment of the maximum heat flux and the quenching point are strongly dependent on this movement. The highest heat fluxes appear mostly at the jump-like movement because the flame behaves locally like a head-on quenching flame.


2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Alexander Avdonin ◽  
Alireza Javareshkian ◽  
Wolfgang Polifke

Abstract This paper demonstrates that a large Eddy simulation (LES) combustion model based on tabulated chemistry and Eulerian stochastic fields can successfully describe the flame dynamics of a premixed turbulent swirl flame. The combustion chemistry is tabulated from one-dimensional burner-stabilized flamelet computations in dependence on progress variable and enthalpy. The progress variable allows to efficiently include a detailed reaction scheme, while the dependence on enthalpy describes the effect of heat losses on the reaction rate. The turbulence-chemistry interaction is modeled by eight Eulerian stochastic fields. An LES of a premixed swirl burner with a broadband velocity excitation is performed to investigate the flame dynamics, i.e., the response of heat release rate to upstream velocity perturbations. In particular, the flame impulse response and the flame transfer function (FTF) are identified from LES time series data. Simulation results for a range of power ratings are in good agreement with the experimental data.


2019 ◽  
Author(s):  
Adrien Chatelier ◽  
Vincent R. Moureau ◽  
Nicolas Bertier ◽  
Benoit Fiorina

2019 ◽  
Vol 33 (5) ◽  
pp. 181-201 ◽  
Author(s):  
David Jesch ◽  
Alija Bevrnja ◽  
Francesca di Mare ◽  
Johannes Janicka ◽  
Amsini Sadiki

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Rohit Kulkarni ◽  
Wolfgang Polifke

The potential of a progress variable formulation for predicting autoignition and subsequent kernel development in a nonpremixed jet flame is explored in the LES (Large Eddy Simulation) context. The chemistry is tabulated as a function of mixture fraction and a composite progress variable, which is defined as a combination of an intermediate and a product species. Transport equations are solved for mixture fraction and progress variable. The filtered mean source term for the progress variable is closed using a probability density function of presumed shape for the mixture fraction. Subgrid fluctuations of the progress variable conditioned on the mixture fraction are neglected. A diluted hydrogen jet issuing into a turbulent coflow of preheated air is chosen as a test case. The model predicts ignition lengths and subsequent kernel growth in good agreement with experiment without any adjustment of model parameters. The autoignition length predicted by the model depends noticeably on the chemical mechanism which the tabulated chemistry is based on. Compared to models using detailed chemistry, significant reduction in computational costs can be realized with the progress variable formulation.


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