Flamelet Table Research Articles

Carrier-phase direct numerical simulation and flamelet modeling of NOx formation in a pulverized coal/ammonia co-firing flame

A carrier-phase direct numerical simulation (CP-DNS) of a coal/ammonia co-firing flame in a turbulent mixing layer is performed with a detailed chemical reaction mechanism including NOx formation. The combustion characteristics and NOx formation mechanism of the coal/ammonia co-firing flame are investigated in detail through a conditional reaction pathway analysis. A new four-fuel-stream flamelet model is proposed to adapt to the piloted pulverized coal/ammonia co-combustion system, in which the complex mixing among the volatiles, char off-gases, ammonia, and the pilot stream is characterized with four mixture fractions. The flamelet solutions in the fourfold mixture fraction space are transformed into a uniform space to facilitate the access to the flamelet table. The performance of the flamelet model is evaluated through an a priori analysis, a combustion mode analysis, and a chemical timescale analysis. For the turbulent coal/ammonia co-firing flame studied, two distinct flame fronts within the shear layer are observed with the upper part being dominated by ammonia combustion and the lower part being governed by coal combustion. The conditional analyses show that NO species is mainly generated by the lower layer governed by pulverized coal combustion where the nitrogen-containing species from volatile combustion are highly involved in the NO formation. The NO concentration first increases with decreasing the fraction of ammonia in the local computational cell, and then decreases towards pure pulverized coal combustion, which is characterized with a newly introduced manifold coordinate. While the temperature and the major and intermediate species mass fractions in the coal/ammonia co-firing flame can be reasonably predicted by the proposed flamelet model, the NOx species mass fractions are not well predicted in the region where pulverized coal combustion dominates. It is clarified that the inaccurate prediction of the NOx species is not caused by interpolation errors, multiple combustion modes or the kinetics of NOx formation, but mainly attributed to the definition of the progress variable.Novelty and significance statementThe novelty of this research is the first DNS of a coal/ammonia co-firing flame in a turbulent mixing layer, and the proposal of a new flamelet tabulation method for predicting NOx formation in the coal/ammonia co-firing flame. It is significant because• Coal/ammonia co-firing promises to provide continuous, secure power supply at a much reduced carbon footprint compared to pure coal combustion;• The underlying physics governing the coal/ammonia co-firing are analyzed using carrier-phase DNS;• The performance of the newly proposed flamelet model in predicting the NOx species is evaluated based on the DNS dataset.

Multi-target active subspaces generated using a neural network for computationally efficient turbulent combustion kinetic uncertainty quantification in the flamelet regime

Propagating uncertainties in kinetic models through combustion simulations can provide important metrics on the reliability and accuracy of a model, but remains a challenging and numerically expensive problem especially for large kinetic models and expensive turbulent combustion simulations. Various surrogate model and dimension reduction techniques have previously been applied in order to reduce the cost of forward uncertainty propagation in combustion simulations, but these are often limited to low-dimensional, simple combustion cases with scalar solution targets. In the current work, we developed a neural network-accelerated framework for identifying a low-dimensional active kinetic subspace that applies to the entire temperature solution space of a flamelet table and can capture the mixture fraction and strain rate dependent effects of the kinetic uncertainty. We then demonstrated the computational savings enabled by this framework through a proof-of-concept, flamelet-based application in a Reynolds-averaged Sandia Flame D simulation using a chemical model for methane combustion with 217 reactions. By leveraging the large dimensional compression and low-cost scaling of the active subspace method, offloading the initial dimension reduction gradient sampling onto the laminar flamelet simulations, and accelerating the gradient sampling process with a specifically designed neural network, we were able to estimate the temperature uncertainty profiles across the solution space of the turbulent flame with strong accuracy of 70−85% using just seven perturbed solutions. Additionally, as it occurs entirely within the flamelet table, the cost of identifying the reduced subspace does not scale with the cost of the turbulent combustion model, which is a promising feature of this framework for future application to larger-scale and more complex turbulent combustion applications.

Exhaust Gas Recirculation (EGR) analysis of a swirl-stabilized pulverized coal flame with focus on NOx release using FPV-LES

Highly-resolved Large Eddy Simulations (LES) are performed to investigate the combustion characteristics and the NOx-formation in the swirl-induced recirculation zones of the Brigham Young University (BYU) Burner Flow Reactor (BFR). The simulations are performed using the in-house LES tool PsiPhi, utilizing a flamelet/progress variable (FPV) approach to model the reactive multiphase flow. Four dimensions are used to parameterize the thermochemical quantities consisting of two mixture fractions for volatiles and char burnout, the total enthalpy and a progress variable, defined by a linear combination of key product species mass fractions. A reduced CRECK mechanism with 120 species and 1551 reactions is used, including all NOx-formation mechanisms (prompt-, fuel-, thermal-, and pathway via N2O). Devolatilization, char burnout and radiation effects are considered in the LES. Radial profiles of major gas species are compared with experimental data, leading to an overall good agreement. Two variants to determine NO species were investigated: (1) the direct extraction of NO from the flamelet table and (2) the solution of an additional transport equation for NO with a modified NO source term, split into a formation and a rescaled consumption part. The solution of an additional transport equation for NO is clearly superior and necessary for pulverized coal simulations, showing a much improved prediction of forward- and backward reactions of NO inside the furnace, while the direct extraction of NO from the flamelet table greatly overpredicts its formation.

Flamelet LES of a turbulent non-premixed cool flame

Turbulence, low-temperature reactivity, and their couplings as turbulent cool flames are crucial to modern engine designing and low-carbon fuel development. While the flamelet method is a promising solution to turbulent combustion, its applicability and accuracy to cool flames have not been thoroughly comprehended. The objective of the present study is to explore the capability of the steady flamelet method in large eddy simulation (LES) of turbulent cool flames. A laminar counterflow non-premixed cool flame configuration is first simulated on a 2-dimensional grid, showing the good validity of flamelet library setup and table interpolation of the method. Then the application to full-scale turbulent cases of cool combustion is presented with the comparison to the experimental measurements and the referenced direct numerical simulation (DNS) data. This is the first LES of a turbulent cool flame, and the result demonstrates the ability of the method in capturing the mean and variance trends for the temperature, mixture fraction and formaldehyde with good quantitative agreement. Meanwhile, conditional result analysis also shows that this approach in a two-stream flamelet form can describe the three-stream experimental system reasonably well. On this basis, three well-documented reaction mechanisms are employed to examine their performances in flamelet LES of turbulent cool flames. The result reveals that the choice of the chemistry scheme does alter the time-averaged prediction of temperature and formaldehyde, whereas the variance profiles of formaldehyde and mixture fraction are not significantly influenced.

Hybrid Unsupervised Cluster-wise Regression Approach for Representing the Flamelet Tables

A novel hybrid unsupervised cluster-wise regression approach is developed to represent the flamelet tables and speed up the computations in turbulent combustion simulations. The proposed machine learning method utilizes a cluster-wise regression technique where specialized deep neural networks are trained on different parts of the input space. A new recursive unsupervised clustering (RUC) approach is proposed that leads to a lower root-mean-square error by over 30% and improves the individual cluster’s mean absolute error by over 20%. The RUC approach enables identifying different combustion manifolds within the input space. The regression models unique to these identified manifolds accurately capture the thermo-chemical scalars for the given input data set. To balance the tradeoffs between the accuracy of flamelet table predictions and the complexities of the RUC algorithm, a hybrid model is introduced that switches between a single neural network (SNN) which is a single regression model, and the SUC RUC approaches. The hybrid unsupervised cluster-wise-regression model benefits from the lower computational costs of SNN for parts of the input space where the SNN prediction error is low and switches to the unsupervised clustering models, that is, standard (SUC) and recursive (RUC) in areas where the SNN performs poorly. The hybrid model is trained on four-dimensional steady flamelet tables and used to model methane combustion by adopting the Sandia Flame D configuration. The hybrid clustering method more accurately captures the experimental measurements of temperature, carbon monoxide (CO), and hydroxyl radical (OH) mass fraction compared to the SNN model. A new hybrid model offers significant improvements in accuracy as compared to the SNN model along with reduction of computational storage by 2 orders of magnitude compared to the original flamelet approach and reduces the total computational time in 3D reacting flow simulations.

Flame structure analysis and flamelet modeling of turbulent pulverized solid fuel combustion with flue gas recirculation

In this work, carrier-phase direct numerical simulation (CP-DNS) is conducted for a pulverized coal flame in a temporally evolving turbulent jet with flue gas recirculation (FGR). Detailed gas phase kinetics are considered and heavy hydrocarbon molecules up to C20 are included to accurately represent tars in the volatile matter. The structure of the pulverized coal flame is analyzed with different flamelet models considering two mixing scenarios, namely the mixing of recirculated flue gases with the other fuel or oxidizer streams. In the first model approach, the mixing of recirculated flue gases with the gaseous fuels released from the coal particle is characterized with a fuel-split-based flamelet (FLT-FS) model. In the second approach, the mixing of flue gases with the transport air is described with an oxidizer-split-based flamelet (FLT-OS) model. In total, five trajectory variables are introduced in the flamelet table to represent the pulverized coal combustion states with FGR. The suitability of the flamelet models is evaluated through an a priori analysis for both the fully ignited state, as well as (more challenging) the igniting states. Comparisons show that both the FLT-FS model and the FLT-OS model perform well in predicting the thermo-chemical quantities for the fully ignited state. The FLT-OS model performs slightly better than the FLT-FS model in predicting the gas temperature and specific species mass fractions. This is due to the fact that the partial oxidization of the gaseous fuels by the hot flue gases outside the mixing layers cannot be reproduced by the FLT-FS model. While the state at the beginning of ignition can still be accurately predicted by the FLT-OS model, discrepancies can be observed for the tar species C20H10 and the intermediate species CO at a later stage when many particles ignite and the reason for this is explained. Further analysis in the flamelet solution spaces shows that the gaseous fuels are ignited on the fuel-lean side. The time evolution of the gas temperature from the beginning of ignition to the fully ignited state can be overall characterized by both flamelet models.

Flame characterisation of gas-assisted pulverised coal combustion using FPV-LES

A multiphase flamelet/progress variable (FPV) model for the large eddy simulation (LES) of gas-assisted pulverised coal combustion (PCC) is developed. The target of the simulation is the Darmstadt turbulent gas-assisted swirling solid fuel combustion chamber. The coal particles are treated as Lagrangian point particles, the position, momentum and energy of which are tracked. The gas phase is described by the low-Mach Navier-Stokes equations alongside the Eulerian transport equations of the governing variables for the FPV model. The set of chemical states of the PCC flame is pre-tabulated in a six-dimensional flamelet table and determined by the mixing of the primary fuel stream, volatiles and char off-gases with the oxidising air, the progress of chemical reactions, the interphase heat transfer, as well as sub-grid scale variations. A presumed β-PDF approach for the total mixture fraction is applied to capture sub-grid scale effects. The discrete ordinate method (DOM) with the weighted sum of grey gases model (WSGGM) is employed to model radiation. The FPV-LES results are validated against the experimental evidence and a good agreement of the predicted mean and RMS velocities, as well as the mean gas temperature between experiments and simulations is obtained. The contributions of the pilot, volatile and char off-gas fuel streams to the coal flame are analysed. It is found that most regions of the furnace are dominated by either pilot or volatile combustion, while char conversion only occurs in the far downstream and outer furnace regions. The pilot gas dominates the near-wall region inside the quarl, whereas the volatile gas mainly released from small particles dominates a first volatile combustion zone in the interior of the internal recirculation zone. Larger particles heat up more slowly and release their volatile content further downstream, leading to a secondary volatile combustion zone.

Physics-aware neural network flame closure for combustion instability modeling in a single-injector engine

Neural networks (NN) are implemented as sub-grid flame models in a large-eddy simulation of a single-injector liquid-propellant rocket engine with the aim to replace a look-up table approach. The NN training process presents an extraordinary challenge. The multi-dimensional combustion instability problem involves multi-scale lengths and characteristic times in an unsteady flow problem with nonlinear acoustics, addressing both transient and dynamic-equilibrium behaviors, superimposed on a turbulent reacting flow with very narrow, moving flame regions. Accurate interpolation between the points of the training data becomes vital. A major novel aspect of the proposed NNs is that they are trained to reproduce relevant portions of the information stored in a flamelet table by using only limited data from a few CFD simulations of a single-injector liquid-propellant rocket engine under different dynamical configurations. This is made possible by enriching the training set with contrived data resulting from the physical characteristics of the combustion model and also by including the flame temperature as an extra input to the NNs that are trained to model other flame variables of interest. These physics-aware NN-based closure models are first tested offline by comparing them directly with the flamelet table and then are successfully implemented into CFD simulations in place of the flamelet table and verified on various dynamical configurations. The results from those tests compare favorably with counterpart table-based CFD simulations. Computational advantages of the approach are discussed.

Evaluation of the Flamelet/Progress-Variable Approach and Flamelet-Generated Manifolds Method in Laminar Counter-Flow Diffusion Flame

To evaluate characteristics of the Flamelet/Progress-Variable approach (FPV) and Flamelet-Generated Manifolds method which can consider a detailed chemical reaction mechanism, a combustion simulation was performed in a laminar counter-flow diffusion flame. While the numerical solutions of the FPV reproduced the measurements and almost completely agreed with those of the detailed chemical reaction mechanism, the numerical solutions of the FGM method overpredicted the measurements of CO mole fraction and underpredicted the ones of CO2 especially in fuel-rich region, and differed from those of the detailed chemical reaction mechanism. This is because the flamelet table of the FGM indicates the state close to chemical equilibrium and overpredicts dissociation of CO2 when the combustion reaction sufficiently progresses.

Neural Network Flame Closure for a Turbulent Combustor with Unsteady Pressure

In this paper, neural network (NN)-based models are generated to replace flamelet tables for subgrid modeling in large-eddy simulations of a single-injector liquid-propellant rocket engine. In the most accurate case, separate NNs for each of the flame variables are designed and tested by comparing the NN output values with the corresponding values in the table. The gas constant, internal flame energy, and flame heat capacity ratio are estimated with 0.0506, 0.0852, and 0.0778% error, respectively. Flame temperature, thermal conductivity, and coefficient of heat capacity ratio are estimated with 0.63, 0.68, and 0.86% error, respectively. The progress variable reaction rate is also estimated with 3.59% error. The errors are calculated based on mean square error over all points in the table. The developed NNs are successfully implemented within the computational fluid dynamics (CFD) simulation, replacing the flamelet table entirely. The NN-based CFD is validated through comparison of its results with the table-based CFD.

Accurate Numerical Integration of β-PDF for the Flamelet Approach

When turbulent combustion simulations are performed using the flamelet approach, which indirectly considers the detailed chemical reaction mechanism, the probability density function (PDF) gets applied to statistical distributions for turbulent fluctuations in the mixture fraction that are modeled using the Reynolds-averaged Navier–Stokes or the large eddy simulation. In this case, the so-called “presumed PDF”—i.e., one in which the PDF is assumed and the flamelet table is constructed in advance—is generally employed, and the β-function is widely used for the PDF. This study investigated numerical integration for the equation with the β-function and examined the appropriate method. We succeeded in establishing the optimum value of the parameter for the integration interval and determining the appropriate numerical integration method.

An Improved NO Prediction Model for Large Eddy Simulation of Turbulent Combustion

Accurate prediction of nitrogen oxides (NOX) emissions is of great importance in combustion simulations. This work proposes an improved model to predict NO distributions in turbulent flames, based on the large eddy simulation approach and flamelet-progress-variable turbulence combustion model. A separate table for NO reaction rate is constructed to account for both unsteady and nonadiabatic effects on NO production. Different from the existing models, the nonadiabatic effect is considered by specifying different enthalpy defects by a scaling factor in the flamelet calculations. Additionally, it is observed that the transient variation of NO reaction rate with NO concentration exhibits two linear stages. As a result, only three flamelet databases are included to describe the NO reaction rate in a transient process, thereby simplifying the flamelet table while maintaining model accuracy. The proposed NO prediction model is validated in large eddy simulations of turbulent combustion, including the classic Sandia D and the Sydney swirling SM1 flames. The calculated NO variations show good agreement with experimental data, demonstrating the applicability and accuracy of the proposed model.

DNS-driven analysis of the Flamelet/Progress Variable model assumptions on soot inception, growth, and oxidation in turbulent flames

Modeling suites for Large-Eddy Simulations of soot evolution in turbulent flames include a number of submodels describing the chemistry of soot precursors, particle dynamics, heterogeneous soot chemistry, turbulent mixing, and combustion. To understand the reasons for model failure and to enhance the overall model performance, it is necessary to identify and subsequently improve model components with a leading order effect on the overall error. In this work, errors in soot predictions associated with flamelet-based combustion models are isolated and quantified in a combined a-priori and partial a-posteriori analysis using large-scale Direct Numerical Simulation (DNS) data of a sooting turbulent jet diffusion flame. Gas-phase quantities entering the calculation of the soot source terms and hence coupling the combustion model to the soot model are analyzed in the DNS first. The performance of a Flamelet/Progress Variable model with respect to these quantities is then analyzed a-priori for two DNS cases employing a mixture-averaged transport model and unity Lewis numbers. Then, the soot evolution along Lagrangian trajectories extracted from the DNS is re-computed using rate coefficients directly taken from the DNS and from the flamelet table. In the context of this partial a-posteriori analysis, flamelet-induced errors are also compared to errors induced by the chemical soot model. The soot surface growth and oxidation rate coefficients are reasonably well predicted by the flamelet library. Considerably larger errors in the model-predicted soot mass originate from the tabulated quantities entering the calculation of PAH-based soot growth rates. However, these errors can be reduced to a few percent if the rate is appropriately scaled with the mass fraction of polycyclic aromatic hydrocarbons (PAH). However, this requires the solution of a transport equation for the PAH mass fraction, and modeling the source term in this equation is shown to be challenging. Overall, the largest uncertainties can be attributed to the chemical mechanism for PAH formation and the model for the PAH source term.

Examination of errors of table integration in flamelet/progress variable modeling of a turbulent non-premixed jet flame

• Different flamelet tables can be generated by using the same laminar flamelet solutions. • Different flamelet table integration approaches can lead to different predictions. • Effect of table integration on a turbulent combustion flame is investigated. A flamelet model implementation consists of two steps: the generation of a set of laminar flamelet solutions and the integration of the laminar flamelet solutions with presumed shape probability density functions (PDFs) to produce a flamelet table for turbulent flame simulations. Many studies have been done in the past to examine the effect of different flamelet modeling strategies including the effect of employing different laminar flamelet solutions for the modeling. However, little work has been done to examine the effect of different presumed PDF table integration approaches on different flamelet model predictions. This work aims at investigating the source of errors arising from the flamelet table integration. The flamelet/progress variable model is chosen as a representative flamelet model, and three different presumed PDF table integration approaches are compared to examine the effect of table integration on flamelet model predictions. A laboratory-scale turbulent non-premixed jet flame (Sandia flame D) is chosen as a test case for the examination. In general, some evident sensitivity of the modeling results to the different flamelet table integration approaches is observed. The underlying reasons for the performance difference of different approaches are explored, and it is found that a model that preserves the one-dimensional laminar flamelet structure during the presumed-PDF table integration can improve the model prediction accuracy. Different sources of errors involved in flamelet model implementation are investigated, including numerical integration errors, flamelet table errors, and the errors in the predictions of the flamelet independent variables.

A Novel In Situ Flamelet Tabulation Methodology for the Representative Interactive Flamelet Model

ABSTRACTA priori flamelet tabulation methods have been used extensively to model premixed and non-premixed combustion in Reynolds-averaged Navier–Stokes (RANS) and large Eddy simulations (LES). Pre-tabulation of flamelet libraries have led to significant cost reduction of Computational Fluid Dynamics (CFD) simulations. However, these tabulation methods rely on certain simplifying assumptions. The dimensionality of the flamelet manifolds and size of flamelet libraries are also constrained due to memory and computational limitations. This limits the applicability and predictive capability of flamelet models. The traditional representative interactive flamelet (RIF) approach with multiple flamelets on the other hand involves online solution of flamelet equations and presumed probability density function (PDF) integration at each computational cell, making it attractive but computationally expensive and not suitable for LES with large cell counts. The current work discusses the development of a novel methodology that combines the advantages of an online flamelet solver along with the computational efficacy of tabulated models. The novel in situ tabulation approach consists of creating a flamelet table at each computational time step using the unsteady flamelet equations. The flamelets are then integrated in real time based on their respective scalar dissipation rate histories. This approach is capable of including history effects and unsteady chemical kinetic effects as it involves the online solution of unsteady flamelets. Implementation and comprehensive validation of the new framework is carried out against gas-jet flames as well as spray flames at high pressures. The approach is first validated for a partially premixed methane gas-jet flame in a RANS framework. The temperature and species mass fractions are compared against experimental results at different locations of a lifted flame. The approach is able to capture the transient flame characteristics. The model is then validated against an n-dodecane spray flame at high pressures in an LES framework with a 103-species n-dodecane chemistry mechanism. The model is able to capture ignition delays and flame liftoff of the n-dodecane spray over varying ambient temperature conditions. Due to the offsetting of presumed PDF integration cost, the proposed framework is shown to be faster than the traditional RIF approach, and the speedup over RIF increases with an increase in the cell count. This framework enables use of the RIF model for large cell count LES simulations.

Improved Flamelet Modeling of Supersonic Combustion

This paper has the objective of addressing a few basic issues pertaining to the use of the laminar flamelet method to model turbulence-combustion interactions in supersonic combustion. Specifically, this paper documents the way in which the use of Troe’s pressure-reaction-rate model affects the laminar flame solutions that are used in the generation of the flamelet library for supersonic combustion. For the opposed-jet model of nonpremixed flames, this study also investigates how the laminar-flamelet results obtained using the flamelet equations differ from those obtained from the canonical equations for opposed-jet flame (OJF). The differential results obtained for supersonic combustion predictions in two models of the scramjet isolator/combustor when pressure, in several formulations, is included as an independent variable of the flamelet table are also presented. Lastly, this study investigates the manner in which the use of various interpolations of the reaction progress variable from the S-curve affects turbulent supersonic combustion results. The overall goal of the various studies is to provide an improved flamelet modeling of supersonic combustion. Simulations based on linear progress variable interpolation coupled with the seven-level pressure field in the base flamelet library, using the OJF equations, appear to yield the best results.

Flame structure analysis and flamelet progress variable modelling of strained coal flames

Strained two-phase pulverised coal flames in a counterflow configuration are investigated numerically. Three operating conditions with different coal-to-primary-air ratios and inlet velocities were evaluated in order to establish different flame regimes. At first, the two-phase flow of the fully resolved reference cases is calculated solving the transport equation for the species and directly evaluating the reaction rates. Different flame structures are identified using the heat release rate and the chemical explosive mode as markers, showing that complex structures with a combination of lean premixed and non-premixed flames can be observed in strained counterflow coal flames. In addition to the fully resolved simulation, the suitability of the Flamelet-Progress Variable (FPV) model is investigated. Both premixed and non-premixed tables are employed. At first, the suitability of the look-up tables is evaluated by means of an a priori analysis, using the fully resolved simulations as reference solutions, showing that the non-premixed flamelet table correctly predicts the structure of the strained coal flames, while the premixed table shows sensible deviations in terms of temperature and species, especially at rich conditions. Finally, the a posteriori analysis shows that the fully coupled FPV model with a non-premixed flamelet look-up table can accurately predict strained coal flames.

A comparison of different approaches to integrate flamelet tables with presumed-shape PDF in flamelet models for turbulent flames

Flamelet models for turbulent combustion modelling make use of presumed-shape probability density functions (PDFs) for integrating laminar flamelet solutions to obtain an integrated flamelet table that can readily be used for turbulent flame calculations. The existence of non-unique approaches for such an integration has rarely been investigated before. For the first time, this work studies systematically the non-uniqueness of the flamelet table integration approaches. A flamelet model called the flamelet/progress variable model is used in the study, although the issue exists generally in many other flamelet models. Two classes of table integration approaches are investigated, one preserving the laminar flamelet structures during integration and the other not. Three different table integration approaches are examined and compared in detail to provide a thorough understanding of the different approaches. A partially stirred reactor is used as a test case for examining the different approaches. A method based on the transported PDF method is also employed to provide a reference for the assessment of the different flamelet table integration approaches. It is found in general that the flamelet preserving integration approach yields a more reasonable joint PDF of the mixture fraction and the progress variable, and the prediction results are closer to the referenced transported PDF results.

Highly resolved flamelet LES of a semi-industrial scale coal furnace

A highly resolved large eddy simulation (LES) of the semi-industrial IFRF coal furnace [1,2] employing the steady flamelet model is presented. The flamelet table is based on mixture fractions of volatile and char off-gases as well as on enthalpy and scalar dissipation rate. Turbulence–chemistry interaction is treated with an assumed pdf approach, with the variance obtained from a transport equation. Radiation is computed by the discrete ordinates method and the grey weighted sum of grey gases model. The simulation is conducted with the massively parallel “PsiPhi” code on up to 1.7 billion cells and with 40 million particles. Results are processed and compared against the comprehensive set of experiments to (i) validate the new flamelet model and the simulation method and to (ii) gain further insight into the combustion process that is not available from the experiment. The simulation results show that the flamelet LES approach can successfully describe the flow field and combustion inside the furnace; major species and velocities are found in good agreement with the experiment.The results are further analyzed with a focus on the processes of particle heating, devolatilization, char combustion and flame stabilization in a highly turbulent environment. Additionally, the relative importance of scalar dissipation rate is highlighted, showing a large separation of mixing scales between volatile and char off-gas combustion due to the long residence time and generally much lower scalar dissipation rates than typical for lab-scale experiments.

A flamelet/progress variable approach for modeling coal particle ignition

In this work an extended flamelet/progress variable (FPV) approach is presented with the aim of simulating the homogeneous auto-ignition of single coal particles during devolatilization. The FPV approach allows chemistry to be decoupled from the solution of the flow field, using a pre-computed strained flamelet look-up table. In this way, the complex chemistry governing coal particle ignition can be accurately accounted for. In particular, one-dimensional unsteady laminar diffusion flamelet (ULDF) simulations are used to generate the table, considering different values of the mixture fraction and the scalar dissipation rate on the particle surface. A new analytical formulation for the scalar dissipation rate is used to solve the diffusion flamelet equations in mixture fraction space, characterized by maximum values on the particle side, rapidly decreasing to zero towards the oxidizer. The time of the ULDF simulations is mapped to progress variable to characterize the ignition process. The FPV approach is then used in laminar resolved CFD simulations of the reactive boundary layer around a single coal particle. The flamelet table look-up is performed using the cell values of the mixture fraction and progress variable along with the particle surface values of the mixture fraction and scalar dissipation rate. Results from the new approach are finally compared with results from a simulation fully resolving transport processes and the detailed chemistry by means of a priori and a posteriori analyses. The results show that the FPV method is able to correctly reproduce the flame structure before and during the ignition process.