Effect of soot model, moment method, and chemical kinetics on soot formation in a model aircraft combustor

Abstract

CitationChong ST, Raman V, Mueller ME, Selvaraj P, Im HG (2018 AbstractThe simulation of turbulent sooting flames requires a host of models, of which the two critical components are the chemical kinetics that describe soot precursor evolution and the description of the soot population. The purpose of this study is to understand the sensitivity of soot predictions in a realistic aircraft combustor to model choices for these components. Two different chemistry mechanisms, three different statistical approaches, and two different soot inception models are considered. The simulations show that acetylene-based soot inception produces very high soot volume fraction, with the soot particles present predominantly in the inner recirculation zone of the swirl-stabilized combustor. The PAH-based nucleation models lead to soot generation in the shear layers emanating from fuel injection. The two advanced statistical approaches (Hybrid and Conditional Quadrature Method of Moments) also show significant differences. While the Hybrid method produces lower soot number density, it also generates larger soot particles due to a faster predicted rate of coagulation. The Conditional Quadrature approach produces much higher soot number density, but its particle sizes are smaller compared to the Hybrid method for all kinetic mechanisms considered. This experimental combustor is strongly dominated by surface growth based soot mass addition. As a result, even if nucleation/condensation rates are different, the final soot mass yield is comparable for PAH-based soot models. These results indicate the importance of not only the chemical mechanism, which may be less important in this surface growth dominated combustor, but also the soot statistical model, to which coagulation and the soot surface area are relatively sensitive.

Incompletely Stirred Reactor Network Modeling of a Model Gas Turbine Combustor

“…Apart from an accurate knowledge of turbulent mixing and finite-rate chemistry effects, reliable predictions of particulate emissions necessitate the use of complex soot models able to describe the underlying chemistry and the morphology of particles [2]. Predictions are known to be very sensitive to the choice of the soot model [3,4]; therefore, sensitivity analysis and comparison between soot models are necessary to gain more insights into soot formation and oxidation. Nevertheless, newly appeared comprehensive soot models [5][6][7][8] cannot easily be used in conjunction with high-fidelity CFD simulations to perform parametric studies during the design phase of combustors, given their high dimensionality and computational cost.…”

Soot Emission Simulations of a Single Sector Model Combustor Using Incompletely Stirred Reactor Network Modeling

“…This is an inherent feature of the 2EQN model and the simplified soot chemistry used here. Therefore investigations with more detailed soot models, explicitly calibrated for kerosene, are expected to lead to lower levels of soot as also observed for simpler fuels (e.g., [6]). As discussed in the following for ISRN predictions, the mean LES-CMC soot location is also expected to differ with a fundamentally different soot model, but further work is required to quantify these effects.…”

“…Equations conditioned on the mixture fraction are solved for both of these quantities, similar to Eqn. (6). The soot model accounts for nucleation and surface growth via acetylene (C 2 H 2 ), surface oxidation via OH and O 2 , but also coagulation by employing a similarity solution for the coalescence of spherical particles in the free molecular regime.…”

“…Apart from an accurate knowledge of turbulent mixing and finiterate chemistry effects [2], reliable predictions of particulate emissions necessitate the use of complex soot models able to describe the underlying evolution processes [3] and the morphology of particles [4]. Predictions are known to be very sensitive to the choice of soot model [5,6]; therefore, sensitivity analysis and comparison between soot models are necessary to gain more insights into soot formation and oxidation.…”

Comprehensive soot particle size distribution modelling of a model Rich-Quench-Lean burner

“…An ethylene swirl flame at elevated pressure [12,13] has been developed with this in mind. A variety of combustion models ranging from tabulated [14,15,16,17,18,19] to quasi-laminar chemistry (i.e., neglecting sub-grid scale fluctuations) [20,21] have been used to simulate this burner.…”