Purpose
This study aims to deal with the large eddy simulation (LES) of an ignition sequence and the resulting steady combustion in a swirl-stabilized liquid-fueled combustor. Particular attention is paid to the ease of handling the numerical tool, the accuracy of the results and the reasonable computational cost involved. The primary aim of the study is to appraise the ability of the newly developed computational fluid dynamics (CFD) methodology to retrieve the spark-based flame kernel initiation, its propagation until the full ignition of the combustion chamber, the flame stabilization and the combustion processes governing the steady combustion regime.
Design/methodology/approach
The CFD model consists of an LES-based spray module coupled to a subgrid-scale ignition model to capture the flame kernel initiation and the early stage of the flame kernel growth, and a combustion model based on the mixture fraction-progress variable formulation in the line of the flamelet generated manifold (FGM) method to retrieve the subsequent flame propagation and combustion properties. The LES-spray module is based on an Eulerian-Lagrangian approach and includes a fully two-way coupling at each time step to account for the interactions between the liquid and the gaseous phases. The Wall-Adapting Local Eddy-viscosity (WALE) model is used for the flow field while the eddy diffusivity model is used for the scalar fluxes. The fuel is liquid kerosene, injected in the form of a polydisperse spray of droplets. The spray dynamics are tracked using the Lagrangian procedure, and the phase transition of droplets is calculated using a non-equilibrium evaporation model. The oxidation mechanism of the Jet A-1 surrogate is described through a reduced reaction mechanism derived from a detailed mechanism using a species sensitivity method.
Findings
By comparing the numerical results with a set of published data for a swirl-stabilized spray flame, the proposed CFD methodology is found capable of capturing the whole spark-based ignition sequence in a liquid-fueled combustion chamber and the main flame characteristics in the steady combustion regime with reasonable computing costs.
Research limitations/implications
The proposed CFD methodology simulates the whole ignition sequence, namely, the flame kernel initiation, its propagation to fully ignite the combustion chamber, and the global flame stabilization. Due to the lack of experimental ignition data on this liquid-fueled configuration, the ability of the proposed CFD methodology to accurately predict ignition timing was not quantitatively assessed. It would, therefore, be interesting to apply this CFD methodology to other configurations that have experimental ignition data, to quantitatively assess its ability to predict the ignition timing and the flame characteristics during the ignition sequence. Such further investigations will not only provide further validation of the proposed methodology but also will potentially identify its shortfalls for better improvement.
Practical implications
This CFD methodology is developed by customizing a commercial CFD code widely used in the industry. It is, therefore, directly applicable to practical configurations, and provides not only a relatively straightforward approach to predict an ignition sequence in liquid-fueled combustion chambers but also a robust way to predict the flame characteristics in the steady combustion regime as significant improvements are noticed on the prediction of slow species.
Originality/value
The incorporation of the subgrid ignition model paired with a combustion model based on tabulated chemistry allows reducing computational costs involved in the simulation of the ignition phase. The incorporation of the FGM-based tabulated chemistry provides a drastic reduction of computing resources with reasonable accuracy. The CFD methodology is developed using the platform of a commercial CFD code widely used in the industry for relatively straightforward applicability.
Large Eddy Simulation of Autoignition in a Turbulent Hydrogen Jet Flame Using a Progress Variable Approach
