Comparison of Flame Propagation Statistics Based on Direct Numerical Simulation of Simple and Detailed Chemistry. Part 2: Influence of Choice of Reaction Progress Variable

Flame propagation statistics for turbulent, statistically planar premixed flames obtained from 3D Direct Numerical Simulations using both simple and detailed chemistry have been evaluated and compared to each other. To achieve this, a new database has been established encompassing five different conditions on the turbulent combustion regime diagram, using nearly identical numerical methods and the same initial and boundary conditions. The discussion includes interdependencies of displacement speed and its individual components as well as surface density function (i.e., magnitude of the reaction progress variable) with tangential strain rate and curvature. For the analysis of detailed chemistry Direct Numerical Simulation data, three different definitions of reaction progress variable, based on CH4,H2O and O2 mass fractions will be used. While the displacement speed statistics remain qualitatively and to a large extent quantitatively similar for simple chemistry and detailed chemistry, there are pronounced differences for its individual contributions which to a large extent depend on the definition of reaction progress variable as well as on the chosen isosurface level. It is concluded that, while detailed chemistry simulations provide more detailed information about the flame structure, the choice of the reaction progress variable definition and the choice of the resulting isosurface give rise to considerable uncertainty in the interpretation of displacement speed statistics, sometimes even showing opposing trends. Simple chemistry simulations are shown to provide (a) the global flame propagation statistics which are qualitatively similar to the corresponding results from detailed chemistry simulations, (b) remove the uncertainties with respect to the choice of reaction progress variable, and (c) are more straightforward to compare with theoretical analysis or model assumptions that are mostly based on simple chemistry assumptions.

Generalization Capability of Convolutional Neural Networks for Progress Variable Variance and Reaction Rate Subgrid-Scale Modeling

Deep learning has recently emerged as a successful approach to produce accurate subgrid-scale (SGS) models for Large Eddy Simulations (LES) in combustion. However, the ability of these models to generalize to configurations far from their training distribution is still mainly unexplored, thus impeding their application to practical configurations. In this work, a convolutional neural network (CNN) model for the progress-variable SGS variance field is trained on a canonical premixed turbulent flame and evaluated a priori on a significantly more complex slot burner jet flame. Despite the extensive differences between the two configurations, the CNN generalizes well and outperforms existing algebraic models. Conditions for this successful generalization are discussed, including the effect of the filter size and flame–turbulence interaction parameters. The CNN is then integrated into an analytical reaction rate closure relying on a single-step chemical source term formulation and a presumed beta PDF (probability density function) approach. The proposed closure is able to accurately recover filtered reaction rate values on both training and generalization flames.

Assessment of Extrapolation Relations of Displacement Speed for Detailed Chemistry Direct Numerical Simulation Database of Statistically Planar Turbulent Premixed Flames

A three-dimensional Direct Numerical Simulation (DNS) database of statistically planar $$H_{2} -$$ H 2 - air turbulent premixed flames with an equivalence ratio of 0.7 spanning a large range of Karlovitz number has been utilised to assess the performances of the extrapolation relations, which approximate the stretch rate and curvature dependences of density-weighted displacement speed $$S_{d}^{*}$$ S d ∗ . It has been found that the correlation between $$S_{d}^{*}$$ S d ∗ and curvature remains negative and a significantly non-linear interrelation between $$S_{d}^{*}$$ S d ∗ and stretch rate has been observed for all cases considered here. Thus, an extrapolation relation, which assumes a linear stretch rate dependence of density-weighted displacement speed has been found to be inadequate. However, an alternative extrapolation relation, which assumes a linear curvature dependence of $$S_{d}^{*}$$ S d ∗ but allows for a non-linear stretch rate dependence of $$S_{d}^{*}$$ S d ∗ , has been found to be more successful in capturing local behaviour of the density-weighted displacement speed. The extrapolation relations, which express $$S_{d}^{*}$$ S d ∗ as non-linear functions of either curvature or stretch rate, have been found to capture qualitatively the non-linear curvature and stretch rate dependences of $$S_{d}^{*}$$ S d ∗ more satisfactorily than the linear extrapolation relations. However, the improvement comes at the cost of additional tuning parameter. The Markstein lengths LM for all the extrapolation relations show dependence on the choice of reaction progress variable definition and for some extrapolation relations LM also varies with the value of reaction progress variable. The predictions of an extrapolation relation which involve solving a non-linear equation in terms of stretch rate have been found to be sensitive to the initial guess value, whereas a high order polynomial-based extrapolation relation may lead to overshoots and undershoots. Thus, a recently proposed extrapolation relation based on the analysis of simple chemistry DNS data, which explicitly accounts for the non-linear curvature dependence of the combined reaction and normal diffusion components of $$S_{d}^{*}$$ S d ∗ , has been shown to exhibit promising predictions of $$S_{d}^{*}$$ S d ∗ for all cases considered here.

Comparison of Performance of Flamelet Generated Manifold Model With That of Finite Rate Combustion Model for Hydrogen Blended Flames

International Air Transport Association (IATA) sets a 50% reduction in 2005 CO2 emissions levels by 2050, with no increase in net emissions after 2020 [1]. The association also expects the global aviation demand to double to 8.2 billion passengers per year by 2037. These issues have prompted the aviation industry to focus intensely on adopting sustainable aviation fuels (SAF). Further, reduction in CO2 emission is also an active area of research for land-based power generation gas turbine engines. And fuels with high hydrogen content or hydrogen blends are regarded as an essential part of future power plants. Therefore, clean hydrogen and other hydrogen-based fuels are expected to play a critical role in reducing greenhouse gas emissions in the future. However, the massive difference in hydrogen’s physical properties compared to hydrocarbon fuels, ignition, and flashback issues are some of the major concerns, and a detailed understanding of hydrogen combustion characteristics for the conditions at which gas turbines operate is needed. Numerical combustion analyses can play an essential role in exploring the combustion performance of hydrogen as an alternative gas turbine engine fuel. While several combustion models are available in the literature, two of the most preferred models in recent times are the flamelet generated manifold (FGM) model and finite-rate (FR) combustion model. FGM combustion model is computationally economical compared to the detailed/reduced chemistry modeling using a finite-rate combustion model. Therefore, this paper aims to understand the performance of the FGM model compared to detailed chemistry modeling of turbulent flames with different levels of hydrogen blended fuels. In this paper, a detailed comparison of different combustion characteristics like temperature, species, flow, and NOx distribution using FGM and finite rate combustion models is presented for three flame configurations, including the DLR Stuttgart jet flame [2], Bluff body stabilized Sydney HM1 flame [3] and dry-low-NOx hydrogen micro-mix combustion chamber [4]. One of the FGM model’s essential parameters is to select a suitable definition of the reaction progress variable. The reaction progress variable should monotonically increase from the unburnt region to the burnt region. The definition is first studied using a 1D premixed flame with different blend ratios and then used for the actual cases. 2D/3D simulations for the identified flames are performed using FGM and finite rate combustion models. Numerical results from both these models are compared with the available experimental data to understand FGM’s applicability. The results show that the FGM model performs reasonably well for pure hydrogen and hydrogen blended flames.