Thermochemical Variables Research Articles

Thermodiffusively unstable laminar hydrogen flame in a sufficiently large 3D computational domain – Part I: Characteristic patterns

Thermodiffusive instabilities can have a leading order effect on flame propagation for lean premixed hydrogen flames. Many simulation studies have been performed to study this effect, but almost exclusively in two-dimensional (2D) or domain sizes too small to support the characteristic large-scale features of the instability. The main purpose of this study is to quantify the differences of 3D and 2D flames using simulations on sufficiently large domains. To this end, direct numerical simulations (DNS) of thermodiffusively unstable laminar premixed hydrogen flames stabilized in 3D domains were performed. The effects of confinement on the flame dynamics are rigorously investigated by varying the domain size. The flame burning velocity shows a strong dependence on the domain size when the lateral domain width is less than 50 laminar flame thicknesses. The characteristic patterns of the thermodiffusively unstable flame are analyzed in detail, including the instantaneous flame structure, global burning velocity, flame surface area, stretch factor, curvature distribution, and the cell size. The effects of the computational setup (2D vs. 3D) on the local flame front curvature and the distributions of the thermo-chemical quantities are quantified through a conditional analysis. The formation and destruction mechanisms of the distinct cellular structures observed in the 3D domain are analyzed focusing on the interactions between the flame dynamics and the flow field, and the contributions of the production of flame surface density, kinematic restoration, and curvature dissipation are quantified. Compared with the corresponding 2D simulation, the flame surface area in the cut plane of the 3D configuration is similar, yet the burning velocity and the stretch factor are increased. The reason for this is the difference in curvature statistics in 2D and 3D. In 3D, larger extreme curvature values are obtained, leading to quantitatively different distributions of the thermo-chemical variables. For example, the peak H radical concentration in the 3D simulation is about twice higher than in the 2D simulation.Novelty and significance statementThe novelty of the present work includes the following aspects:(i) First large-scale 3D DNS of laminar lean premixed hydrogen flame on domain large enough to obtain domain-independent results.(ii) First quantitative assessment of characteristic patterns of 3D thermodiffusively unstable premixed hydrogen flames.(iii) First quantitative assessment of differences between 2D and 3D thermodiffusively unstable premixed hydrogen flames for domain-independent results.

Skeletal reaction models for methane combustion

A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). The sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.

Investigation of the oxy-fuel combustion process in the full-loop circulating fluidized bed

Oxy-fuel combustion of fossil fuels in circulating fluidized bed (CFB) reactors has been widely implemented in various industries. However, the knowledge of complex gas thermal characteristics (e.g., gas temperature, viscosity, density, conductivity and specific heat capacity) is still in lack. Understanding the distribution of these gas thermal properties within the oxy-fuel combustion CFB reactor is crucial for predicting particle behavior, optimizing operating conditions, and performing design optimizations. In this study, the hydrodynamics and thermochemical characteristics of dense reactive flow in a 0.1 MWth pilot-scale CFB are simulated via a developed multi-phase particle-in-cell (MP-PIC) reactive model. The impacts of some key operating parameters on the gas thermal properties, gas species distribution and gas-solid flux are studied. The results show that the dynamics and thermochemical variables of gas-solid flow show non-uniform distributions in the riser due to the segregation mechanism and lateral injection of solid fuels. Combustible gases (e.g., CH4, CO, H2, and H2S) mainly concentrate in the left area of the riser. Enlarging the oxygen concentration increases gas viscosity while decreases gas density. The density of gas phase ranges from 0.35 kg/m3 to 0.50 kg/m3 while gas turbulent viscosity ranges from 4.2 × 10−5 m2/s to 4.8 × 10−5 m2/s.

Physics informed machine learning for chemistry tabulation

Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent transport. Solving both systems simultaneously is computationally prohibitive. Instead, given the difference in scales at which the two sub-systems evolve, the two sub-systems are typically (re)solved separately. Popular approaches such as the Flamelet Generated Manifolds (FGM) use a two-step strategy where the governing reaction kinetics are pre-computed and mapped to a low-dimensional manifold, characterized by a few reaction progress variables (model reduction) and the manifold is then “looked-up” during the run-time to estimate the high-dimensional system state by the turbulent transport system. While existing works have focused on these two steps independently, in this work we show that joint learning of the progress variables and the look-up model, can yield more accurate results. We build on the base formulation and implementation (Salunkhe et al., 2022) to include the dynamically generated Thermochemical State Variables (Lower Dimensional Dynamic Source Terms). We discuss the challenges in the implementation of this deep neural network architecture and experimentally demonstrate its superior performance.

Effects of non-thermal termolecular reactions on wedge-induced oblique detonation waves

The shock-induced combustion ramjet (Shcramjet) based on oblique detonation waves (ODWs) is among the promising choices for hypersonic propulsion systems. An understanding of the ignition, propagation, and stability of ODWs is critical to harnessing their propulsive potential. In such high speed reacting flows, there is a high probability of occurrence of non-thermal reactions due to the presence of non-trivial amounts of highly reactive radicals including H, O and OH apart from O2 as demonstrated recently [M. P. Burke, S. J. Klippenstein, Nat. Chem. 9 (2017) 1078–1082, Y. Tao, A. W. Jasper, Y. Georgievskii, S. J. Klippenstein, R. Sivaramakrishnan, Proc. Combust. Inst. 38 (2021) 515–522]. The present work focuses on examining the initiation, propagation and structure of oblique detonation waves in stoichiometric H2-air mixtures through numerical simulations with and without non-thermal reactivity on a two-dimensional adaptive grid. Non-thermal reactions were included in the macroscopic kinetic model as chemically termolecular reactions facilitated by the H + OH radical-radical recombination and the H + O2 radical-molecule association reactions. Since, the non-thermal reactions result in a corresponding decrease in the reaction fluxes of the incipient recombination/association reactions, an additional simulation was performed by applying corrections to the respective incipient recombination/association rate constants using the methodology demonstrated by Tao et al. [Y. Tao, A. W. Jasper, Y. Georgievskii, S. J. Klippenstein, R. Sivaramakrishnan, Proc. Combust. Inst. 38 (2021) 515–522]. Results show that, under ODWE relevant conditions, non-thermal reactivity fundamentally alters the induction length, intensity as well as the structure of the ODW. Specifically, it is found that non-thermal reactivity leads to a noticeable reduction in initiation length and a simultaneous increase in instantaneous peak heat release rate and the degree of unsteadiness of the ODW. Statistical analysis of key thermo-chemical variables is performed to elucidate the important species as well as reactions responsible for the observed variations.

Application of dense neural networks for manifold-based modeling of flame-wall interactions

Artifical neural networks (ANNs) are universal approximators capable of learning any correlation between arbitrary input data with corresponding outputs, which can also be exploited to represent a low-dimensional chemistry manifold in the field of combustion. In this work, a procedure is developed to simulate a premixed methane-air flame undergoing side-wall quenching utilizing an ANN chemistry manifold. In the investigated case, the flame characteristics are governed by two canonical problems: the adiabatic flame propagation in the core flow and the non-adiabatic flame- wall interaction governed by enthalpy losses to the wall. Similar to the tabulation of a Quenching Flamelet-Generated Manifold (QFM), the neural network is trained on a 1D head-on quenching flame database to learn the intrinsic chemistry manifold. The control parameters (i.e. the inputs) of the ANN are identified from thermo-chemical state variables by a sparse principal component analysis (PCA) without using prior knowledge about the flame physics. These input quantities are then transported in the coupled CFD solver and used for manifold access during simulation runtime. The chemical source terms are corrected at the manifold boundaries to ensure bounded- ness of the thermo-chemical state at all times. Finally, the ANN model is assessed by comparison to simulation results of the 2D side-wall quenching (SWQ) configuration with detailed chemistry and with a flamelet-based manifold (QFM).

Performance Assessment of Chemical Kinetics Neural Ordinary Differential Equations in Pairwise Mixing Stirred Reactor

Abstract The present study aims to assess the potential of the neural ordinary differential equations (NODE) network for reliable and computationally efficient implementation of chemistry in combustion simulations. Investigations are performed using a hydrogen-air pairwise mixing stirred reactor (PMSR). The PMSR is a zero-dimensional case affordable to study combustion chemistry entailing a similar numerical solution procedure as probability density function methods for turbulent combustion simulations. A systematic approach is presented to apply the NODE, solely trained on canonical constant pressure homogeneous reactor data, to predict complex chemistry and mixing interactions in PMSR. The reactor involves combustion of hydrogen in air described by a finite-rate mechanism with 9 chemical species and 21 reaction steps. The NODE network is shown to accurately capture the evolution of thermochemical variables for different mixing and chemical timescales. It also exhibits a significant reduction in numerical stiffness resulting in improving the computational efficiency and enabling the use of explicit solvers for the integration of chemical kinetics. The assessment results based on PMSR show that compared to direct integration of detailed kinetics, the NODE can achieve significant computational time speedup for a comparable accuracy.

Humboldt's enigma viewed through the lens of ecosystem theory. Explanation by simple principles.

The observation that mountain regions generally display higher diversity than tropical regions has recently been presented as a puzzle or “enigma”, since it seems to contradict the normal belief that the highest diversity on Earth occurs in the rain forest ecosystems around the equator. The observation seems to be well supported by data gathered for several animal and plant communities, and thus deserves further attention, including investigation of how it arises. However, re-interpretation of the enigma in the light of ecosystem theory serves to resolve the problem, explaining the increased diversity as the result of the presence of a larger set of thermodynamic and thermo-chemical variables, which vary in quantity, quality, time, and space, together with the forcing functions usually present. This permits a more intensive exploitation of the gradients in an oscillating environment as formulated for instance in the intermediate disturbance hypothesis combined with the niche construction concept. Put simply, mountain regions offer an environment with a greater and more variable set of gradients, in terms of both quantity and quality, than occur in the more stable environments found in relatively flat areas. This gives an extra stimulus to speciation processes, resulting in the elevated diversity observed. Highlights • Biodiversity in mountain regions is often found to be unexpectedly higher than in tropical regions. • Simple principles from ecosystem theory can explain this. • The application of theory allows for several new, testable hypotheses to be derived.

AUTOENCODER NEURAL NETWORK FOR CHEMICALLY REACTING SYSTEMS

Incorporating detailed chemical kinetic models is critical for accurate simulations of reacting flows. However, detailed models involve a large number of thermochemical (TC) state variables. Solving the governing equations to evolve these TC variables becomes impractical for real-world applications. In this work, we propose an autoencoder (AE) neural network (NN)-based reduced model to accelerate such simulations. The AE NN is first trained to find a low-dimensional latent representation of the TC states. Then, the evolving state of a chemical system can be tracked by solving the equations of the latent variables instead of the original TC equations. We demonstrate the reduced model in a syngas CO/H<sub>2</sub> combustion system, using training data collected from canonical perfectly stirred reactors (PSRs). It is found that the AE model can reduce the dimension of the combustion system from 12 to 2 while maintaining low reconstruction error and excellent elemental mass conservation for the test dataset. In the a posteriori test, the combustion states obtained from solving the two latent equations are compared to those from solving the 12 equations of the full model. The AE reduced method is found to be able to capture the diverse combustion states on the top two branches of the S-curve well including the extinction turning point, but with higher prediction errors for states near the ignition turning point.

Flame structure analysis and composition space modeling of thermodiffusively unstable premixed hydrogen flames — Part I: Atmospheric pressure

This work focuses on flame structure analysis and composition space modeling of a multidimensional premixed hydrogen flame transitioning from a laminar stable condition to a thermodiffusively unstable state. Specifically, budget and a priori analyses are conducted based on a detailed chemistry simulation of a 2D expanding, thermodiffusively unstable hydrogen flame, and the recurring issues for modeling differential diffusion, the strain rate and curvature in the thermodiffusively unstable flame are addressed in a single newly proposed flamelet tabulation method. The model is based on recently developed self-contained strained-curved premixed flamelet equations in composition space (Scholtissek et al., 2019, CNF), which inherently incorporate the interactions among differential diffusion, the strain rate and curvature. The validity of the newly proposed flamelet tabulation method is evaluated based on the representative strongly strained-curved flamelets extracted from the reference simulation, featuring wide ranges of strain rates and curvatures. The advance realized in the proposed flamelet model is confirmed by comparing it with a conventional flamelet tabulation method. Through the budget analysis, the effects of curvature on the diffusion along the flame front (i.e., tangential diffusion) are quantified. Through the a priori analysis, the suitability of the proposed flamelet tabulation method in predicting differential diffusion is confirmed. For the prediction of the strain rate and curvature, it is found that introducing the strain rate and curvature themselves as the trajectory variables does not necessarily improve the prediction accuracy in the reaction zone, compared to the flamelet model based on the 1D freely-propagating premixed flame with differential diffusion. To remedy this, the trajectory variables that can characterize the flame structure’s internal response to the strain rate and curvature are identified. The results show that the thermo-chemical variables in the thermodiffusively unstable flame at atmospheric pressure can be accurately predicted by the newly introduced trajectory variables based on the 1D strained-curved flamelet equations.

Extinction of incident hydrogen/air detonation in fine water sprays

Two-dimensional numerical simulations with Eulerian–Lagrangian method are conducted to study propagation and extinction of stoichiometric hydrogen/air detonations in fine water sprays. Parameterized by water mass loading and droplet size, a detonation extinction map is predicted. Detonation extinction occurs with larger mass loading and/or smaller droplet size. General features of water droplets and local detonation frontal structures are well captured. Numerical soot foils are used to characterize the influence of mass loading and droplet size on the detonation wave. The results also show that the detonation cell size increases with increased mass loading or decreased droplet size. Analysis on unsteady detonation extinction process is performed with the evolutions of detonation frontal structure, spatial distribution of thermochemical variables, and interphase transfer rates (mass, energy, and momentum). Moreover, the chemical explosive mode analysis reveals that for stable detonation, thermal runaway dominates behind the Mach stem, while chemical propensities of autoignition and thermal runaway appear alternately behind the incident wave. When the induction zone length increases as the reaction front (RF) and shock front (SF) are decoupled, localized burned pockets surrounded by the autoignition chemical explosive mixture can be observed. In addition, the interactions between detonation wave and water droplets demonstrate that the energy and momentum transfer have more direct interaction with SF and RF than the mass transfer. The interphase transfer rates increase with the water mass loading. Under the same mass loading, the smaller the droplet size, the larger the interphase transfer rates. However, the size of fine water droplets has a limited influence on the interphase momentum exchange. Moreover, high energy and mass transfer rates are observed at the onset of detonation extinction, and they gradually decrease when the reaction and detonation fronts are decoupled.

Assessment of disparities in estimating filtered chemical reaction rates in LES using DNS of turbulent premixed flames

An a priori assessment of the disparities in estimating the filtered chemical reaction rates in Large-Eddy Simulations (LES) is performed using two Direct Numerical Simulations (DNS) of turbulent premixed flames. DNS of turbulent premixed flames with the same turbulent Reynolds number but different Karlovitz numbers are carried out using semi-detailed finite-rate chemistry to represent different flame conditions. The sensitivities of the differences between the LES-filtered chemical reaction rates and those constructed using LES-filtered thermochemical variables (referred to as ‘disparity’ below) to reaction types, species characteristics, and flame conditions are systematically investigated. The sensitivity to reaction type is examined by quantifying the disparity in the filtered temperature-dependent reaction rate constant as a function of kinetic rate parameters. The sensitivity to species characteristics is examined by quantifying the disparity in the filtered law of mass action as a function of species chemical time scales and formation location. The sensitivity to flame conditions is examined by contrasting the results obtained from the two simulations. These disparities are compared to characterise distinct reaction/species categories with different levels of disparity in estimating the filtered chemical reaction rates in LES. For both flames, it is found that the rate constants estimated using LES-filtered temperature severely under-predict the LES-filtered rate constants, especially for reactions with high activation energies. The law of mass action estimated using LES-filtered species concentrations severely over-predicts the LES-filtered law of mass action, especially for reactions involving reactants with small chemical time scales. The combined effects are found to lead to considerable differences between the LES-filtered chemical reaction rates and those constructed using LES-filtered thermochemical quantities for all reaction types involving different classes of reactants typically included in combustion reaction mechanisms. The details and explanations of these differences provide test cases useful to the improvement of key LES modelling approximations.

A tabulated chemistry method for heterogeneous solid propellant combustion

Detailed chemistry simulations of heterogeneous solid propellant combustion at the microstructure scale are very costly as they involve large and stiff chemical schemes in the gas phase. A usual workaround is to use global chemistry to approximate gas phase reactions. A drawback of this approach is the need for an a priori calibration which necessitates reference data and often limits the operating conditions range of validity. An alternative method based on 1-D burner-stabilized flames tabulation is proposed in this paper. The theoretical and numerical frameworks are detailed. An appropriate tabulation space is introduced to store useful thermochemical variables as well as Jacobian terms used for time-integration. Jump conditions are also rewritten to cope with tabulated chemistry formalism. Several 1-D validations are performed on classical propellant compositions. Detailed comparisons with available experimental data demonstrate the ability of the proposed methodology to tackle inner flame structure (temperature and species) as well as the evolution of the burning rate with pressure and composition. Finally, 2-D laminate propellant simulations are conducted showing the ability of the methodology to capture complex flame regimes and associated burning rate modifications.

Digital twin of a combustion furnace operating in flameless conditions: reduced-order model development from CFD simulations

The present paper presents the first-of-its-kind digital twin for a furnace operating in flameless combustion conditions. A methodology combining data compression, by means of Proper Orthogonal Decomposition (POD), and interpolation, using Kriging, was developed to design physics-based, reduced-order models (ROMs) for the prediction of combustion data at unexplored operating conditions. Three-dimensional simulations with detailed chemistry were carried out, spanning a wide range of operating conditions in terms of fuel composition (methane-hydrogen mixtures from pure methane to pure hydrogen), equivalence ratio (from 0.7 to 1) and air injector diameter (to adjust the air jet entrainment). Based on the available simulations, a ROM was developed, to predict both spatial fields, local and integral values of thermochemical variables at working conditions not included in the ROM development. Results showed that the developed ROM could reliably predict the temperature and main chemical species distribution in the furnace with an overall error below 10%, proving the effectiveness of the approach for the development of digital twins of combustion systems. A remarkable accuracy was observed for the prediction of specific quantities, including wall temperatures, OH decay length, OH peak value and location and exhaust gas composition, including pollutants, with prediction errors always below 5%, showing the potential of the approach to develop soft sensors.

Capturing multi-regime combustion in turbulent flames with a virtual chemistry approach

Multiple flame regimes are encountered in industrial combustion chambers, where premixed, stratified and non-premixed flame regions may coexist. To obtain a predictive tool for pollutant formation predictions, chemical flame modeling must take into account the influence of such complex flame structure. The objective of this article is to apply and compare two reduced chemistry models on both laminar and turbulent multi-regime flame configurations in order to analyze their capabilities in predicting flame structure and CO formation. The challenged approaches are (i) a premixed flamelet-based tabulated chemistry method, whose thermochemical variables are parameterized by a mixture fraction and a progress variable, and (ii) a virtual chemical scheme which has been optimized to retrieve the properties of canonical premixed and non-premixed 1-D laminar flames. The methods are first applied to compute a series of laminar partially-premixed methane-air counterflow flames. Results are compared to detailed chemistry simulations. Both approaches reproduced the thermal flame structure but only the virtual chemistry captures the CO formation in all ranges of equivalence ratio from stoichiometry premixed flame to pure non-premixed flame. Finally, the two chemical models combined with the Thickened Flame model for LES are challenged on a piloted turbulent jet flame with inhomogeneous inlet, the Sydney inhomogeneous burner. Mean and RMS of temperature and CO mass fraction radial profiles are compared to available experimental data. Scatter data in mixture fraction space and Wasserstein metric of numerical and experimental data are also studied. The analyses confirm again that the virtual chemistry approach is able to account for the impact of multi-regime turbulent combustion on the CO formation.

Data-driven selection of stiff chemistry ODE solver in operator-splitting schemes

Most computational fluid dynamics simulations of practical combustion applications employ operator-splitting schemes, where chemistry and transport are separated and integrated with distinct numerical methods. The changes in composition due to chemistry are evaluated by solving ordinary differential equations (ODE) in each cell of the computational domain, which typically dominates the computational cost when detailed chemistry is considered. In this work, a data-driven approach for the selection of chemistry ODE solvers in operator-splitting schemes is presented. Neural networks are used to predict the ODE solvers CPU times and errors for a given thermochemical state. This allows the selection of an optimal ODE solver on a cell-by-cell, timestep-by-timestep basis. The models are trained using a wide set of thermochemical states generated through partially-stirred reactors and flames simulations. The methodology is validated by quantifying the prediction errors, the classification accuracy, and the computational speedup. The model predicts the optimal ODE solver for 70 to 95% of the validation cases and decreases the computional cost by a factor of 3 or more. The generalizability of the methodology to different chemical mechanisms and different fuels is assessed and it is shown that the model’s performance is only slightly degraded and its applicability is significantly enhanced if the inputs to the neural networks are restricted to a small set of thermochemical state variables present in most chemical mechanisms. The models are used in an homogeneous reactor case and a multi-dimensional CFD simulation of a diesel spray at high pressure where a speedup of more than 3 is achieved.

A comprehensive study of flamelet tabulation methods for pulverized coal combustion in a turbulent mixing layer — Part I: A priori and budget analyses

In this work, a comprehensive study of flamelet tabulation methods for pulverized coal combustion in a turbulent mixing layer is conducted. At first, a priori analyses are conducted to evaluate the suitability of the premixed and non-premixed flamelet models for the studied pulverized coal flame with multiple combustion modes. Then, to clarify why a certain flamelet model does work or not work in certain regions, a more in-depth investigation of the premixed and non-premixed flamelet models is conducted through a budget analysis. The results show that the first and second derivatives in physical space can be well reproduced by the tabulated manifolds in trajectory variable space for both the premixed and non-premixed flamelet models, between which the non-premixed flamelet model performs slightly better. For the time derivative, large discrepancies can be observed, although the predicted variation trend overall follows the reference results. Through the analysis of the individual budget terms in the trajectory variable space, the individual trajectory variable’s contributions to the convection and diffusion of thermo-chemical variables are quantified. Through the analysis of the individual budget terms for the sensible enthalpy and the CO mass fraction governing equations, the influences of the space transformation on the individual transport process (e.g., convection, diffusion, etc.) are clarified. Overall, the findings obtained from the budget analyses are consistent with those obtained from the a priori analyses.

Influence of flow topology and scalar structure on flame-tangential diffusion in turbulent non-premixed combustion

Flamelet-based combustion models have been extensively used in the modeling of turbulent non-premixed combustion due to their notable advantages in reducing computational cost. The classical one-dimensional flamelet equations are derived based on an assumption: flame-normal transport of thermochemical state variables in mixture fraction gradient direction dominates over flame-tangential transport along iso-surfaces of mixture fraction. The motivation of this work is to quantify the contribution of tangential diffusion (TD) and seek the source of TD, since several recent studies have shown that TD effects may play an important role in the regions with large curvature and finite-rate chemistry. In this work, the most probable cause and effect chain that elucidates the source of TD in a turbulent non-premixed jet flame is proposed for the first time from a flow topology perspective. To this end, local flow topology and its effects on scalar structure are first investigated. It is found that the local flow structures with unstable focus compressing (UFC) topology have the highest probability of large compressive strain and that the negative correlation between curvature and strain strongly depends on local flow topology, scalar structure and reaction. Then, the influence of flow topology and scalar structure on the relevance of TD is assessed with the angle between reactive scalars and mixture fraction. The results show that TD effects mainly exist in the regions with high curvatures and low strain rates or scalar dissipation rates. These findings suggest that the local flow structures with low probability of UFC topology tend to cause significant flame-tangential diffusion in the turbulent non-premixed flame.

A self-contained progress variable space solution method for thermochemical variables and flame speed in freely-propagating premixed flamelets

Flamelet models for premixed combustion, which are based on equations formulated and solved in progress variable space, have been proposed in the past, but have not been adopted for chemistry reduction methods. This is due to one limitation of these models: they need a closure for both the magnitude and the shape of the gradient (or scalar dissipation rate) of the progress variable, which is essential for an accurate prediction of the flame displacement speed. So far, solution methods for the aforementioned models require gradient information as an input, which is either modelled and non-generic, or extracted from a previous physical space flame solution for the analogous problem. The objective of this work is to provide a self-contained solution method for freely-propagating premixed flamelets in progress variable space, by solving an additional flamelet equation for the gradient of the progress variable. With this, the novel method provides both magnitude and shape of the gradient. Studying hydrogen-air and methane-air configurations, it is demonstrated that an accurate prediction of the laminar flame speed without the necessity for further input parameters can be obtained.

Numerical studies of turbulent swirling reacting flows using LES and URANS

Numerical studies of turbulent swirling reacting flows are performed using unsteady Reynolds-averaged Navier-Stokes (URANS) and large-eddy simulation (LES) approaches. Aiming at the reduction of computational costs, the present research assesses the feasibility of URANS for the computations of turbulent reacting flows. The conserved scalar-mixture fraction-based thermo-chemical variables are described using the steady laminar flamelet model. The Favre-filtered scalars are obtained from the presumed beta probability density function (β–PDF) approach. The flow field exhibits upstream recirculation zone due to the bluff body and a downstream vortex breakdown region induced by the swirling flow. The study reveals that the strength of the vortex decays with the increase of distance from the injection region. The temperature exhibits high values in the region surrounding the flame. The present research shows that in spite of its low computational cost, the URANS approach is quite dissipative when compared with LES. Therefore, LES is a more appropriate approach for the numerical simulation of turbulent combustion, when the solution accuracy is of concern.