Hydrodynamic instability and shear layer effect on the sound emission of a turbulent jet flame

Turbulent jet ignition technology can significantly improve lean combustion stability and suppress engine knocking. However, the narrow jet channel between the pre-chamber and the main chamber leads to some difficulties in heat exchange, which significantly affects combustion performance and mechanical component lifetime. To clarify the effect of temperature conditions on combustion evolutions of turbulent jet ignition, direct numerical simulations with detailed chemical kinetics were employed under engine-relevant conditions. The flame propagation in the pre-chamber and the early-stage turbulent jet ignition in the main chamber were investigated. The results show that depending on temperature conditions, two types of flame configuration can be identified in the main chamber, i.e., the normal turbulent jet flame propagation and the spherical flame propagation, and the latter is closely associated with pressure wave disturbance. Under low-temperature conditions, the cold jet stoichiometric mixtures and the vortexes induced by the jet flow determine the early-stage flame development in the main chamber. Under intermediate temperature conditions, pre-flame heat release and leading pressure waves are induced in the jet channel, which can be regarded as a transition of different combustion modes. Whereas under high-temperature conditions, irregular auto-ignition events start to occur, and spherical flame fronts are induced in the main chamber, behaving faster flame propagation.

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Cinema particle imaging velocimetry time history of the propagation velocity of the base of a lifted turbulent jet flame

Proceedings of the Combustion Institute ◽

10.1016/s1540-7489(02)80230-9 ◽

2002 ◽

Vol 29 (2) ◽

pp. 1897-1903 ◽

Cited By ~ 33

Author(s):

Ansis Upatnieks ◽

James F. Driscoll ◽

Steven L. Ceccio

Keyword(s):

Propagation Velocity ◽

Time History ◽

Turbulent Jet ◽

Particle Imaging Velocimetry ◽

Jet Flame ◽

History Of ◽

Particle Imaging

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Evaluation of a Turbulent Jet Flame Flashback Correlation Applied to Annular Flow Configurations With and Without Swirl

10.1115/1.0002905v ◽

2021 ◽

Author(s):

Vincent McDonell ◽

Elliot Sullivan-Lewis ◽

Alireza Kalantari ◽

Priyank Saxena

Keyword(s):

Annular Flow ◽

Turbulent Jet ◽

Jet Flame ◽

Flow Configurations ◽

Flame Flashback

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A theoretical model of a wake of a body towed in a stratified fluid at large Reynolds and Froude numbers

Nonlinear Processes in Geophysics ◽

10.5194/npg-13-247-2006 ◽

2006 ◽

Vol 13 (3) ◽

pp. 247-253 ◽

Cited By ~ 2

Author(s):

Y. I. Troitskaya ◽

O. A. Druzhinin ◽

D. A. Sergeev ◽

V. V. Papko ◽

G. N. Balandina

Keyword(s):

Experimental Data ◽

Theoretical Model ◽

Momentum Transfer ◽

Hydrodynamic Instability ◽

Jet Flow ◽

Stratified Fluid ◽

Turbulent Jet ◽

Wake Flow ◽

Mean Flow ◽

Turbulent Jet Flow

Abstract. The objective of the present paper is to develop a theoretical model describing the evolution of a turbulent wake behind a towed sphere in a stably stratified fluid at large Froude and Reynolds numbers. The wake flow is considered as a quasi two-dimensional (2-D) turbulent jet flow whose dynamics is governed by the momentum transfer from the mean flow to a quasi-2-D sinuous mode growing due to hydrodynamic instability. The model employs a quasi-linear approximation to describe this momentum transfer. The model scaling coefficients are defined with the use of available experimental data, and the performance of the model is verified by comparison with the results of a direct numerical simulation of a 2-D turbulent jet flow. The model prediction for the temporal development of the wake axis mean velocity is found to be in good agreement with the experimental data obtained by Spedding (1997).

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Simulation of Methanol-Air Two-Phase Flames Using Various Turbulent Combustion Models

Volume 2: Combustion, Fuels and Emissions ◽

10.1115/gt2009-59344 ◽

2009 ◽

Author(s):

F. Wang ◽

Y. Huang ◽

Y. Z. Wu

Keyword(s):

Experimental Data ◽

Turbulent Combustion ◽

Turbulent Jet ◽

Combustion Model ◽

Air Flow Rate ◽

Two Phase ◽

Jet Flame ◽

Combustion Simulation ◽

Turbulent Combustion Model ◽

Turbulent Models

Though fossil fuel is running out, liquid fuels nowadays still provide the most energy used by industrial furnaces, automotive and aero engines. How to predict a two-phase turbulent combustion flame is still a big problem to designers. Generally, the liquid fuel is sprayed and mixed with oxygen, and the flame characteristics depends on the fuel atomization, the fuel droplet spatial distribution, and its interaction with the turbulent oxidizer flow field: turbulent heat, mass and momentum transfer, complicated chemical kinetics, and turbulent-chemistry interaction. Turbulent combustion model is a key point for the two phase combustion simulation. For its short time consuming, Reynolds Averaged Navier Stokes (RANS) method nowadays still is the major tool for gas turbine chamber (GTC) designers, but there is not a universal method in RANS GTC spray combustion simulation at present especially for the two-phase turbulent combustion. The Eddy-Break-Up turbulent combustion model (EBU), Eddy Dissipation Concept turbulent combustion model (EDC), steady Laminar Flame-let turbulent combustion Model (LFM) and the Composition PDF transport turbulent combustion model (CPDF) are all widely used models. In this paper, these four turbulent models are used to simulate a methane-air turbulent jet flame measured by Sandia Lab first, then three methanol-air two-phase turbulent flames, in order to know the ability of these turbulent models. In the gas turbulent jet flame simulation, the result of LFM model and CPDF model are in better agreement with the experimental data than those of the EBU and the EDC models’ results. The reason is that the EBU model and EDC model are overestimated the effect of turbulent. In the three different cases of the two phase combustion simulation, CPDF is the best. The prediction ability of the other three models is different in different cases. The EDC predictions are closer to the experimental data when the air flow rate value is lower, whereas the LFM predictions are better when the air flow rate value is higher.

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