Detailed reduction of reaction mechanisms for flame modeling☆
Abstract
A method for reduction of detailed chemical reaction mechanisms, introduced earlier for ignition systems, was extended to laminar premixed flames. The reduction is based on testing the reaction and reaction-enthalpy rates of the “full” reaction mechanism using a zero-dimensional model with a flame temperature profile as a constraint. The technique is demonstrated with numerical tests performed on the mechanism of methane combustion.
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Cited by (176)
Modeling of high-speed, methane-air, turbulent combustion, Part II: Reduced methane oxidation chemistry
2024, Combustion and FlameA reduced, 12-species reaction model (FFCMy-12) is proposed for modeling high-speed turbulent methane flames at high Karlovitz numbers. The model was derived from an early development version (FFCMy) of the 119-species Foundational Fuel Chemistry Model Version 2.0. The reduction was carried out by combining direct species pruning, quasi-steady-state assumption, and reaction lumping, targeting a minimum possible set of species that can capture methane combustion over a wide range of thermodynamic conditions. The performance of the reduced FFCMy-12 is compared to that of a 21-species skeletal reaction model (FFCM1-21) generated through conventional directed relation graph theory (DRG) and DRG-aided sensitivity analysis (DRGASA) algorithms. Model testing starts with legacy combustion properties such as homogeneous ignition delay time, laminar flame speed, and extinction/ignition residence time in a perfectly stirred reactor. More importantly, reduced model testing is extended to three-dimensional direct numerical simulations (DNS) of statistically planar, freely propagating turbulent premixed flames at Karlovitz numbers , , , and , which nominally represent conditions from corrugated flamelets to broken reaction zones. Comparisons are made between the DNS results generated by the two chemical kinetic models with respect to turbulent flame structures, turbulent flame speed, and species distributions. Overall, presented results demonstrate the potential of FFCMy-12 for efficient modeling of the methane flames under highly turbulent mixing conditions characterized by a wide range of Ka. As importantly, the one-dimensional turbulence (ODT) model, developed in the companion paper (Part I), is shown to reproduce adequately the mean values of the local thermochemical states observed in the DNS, and as such, the ODT model is a viable DNS surrogate for testing the accuracy and applicability of a reduced model.
Novelty and significance
We present a 12-species reduced methane oxidation reaction model for the modeling of highly turbulent reacting flows. The reduced model is validated using DNS of premixed turbulent methane-air flames over a wide range of turbulent intensities, from relatively modest corresponding to Karlovitz number to ultra-high intensities at . This represents virtually the entire range of turbulent intensities that could be encountered in any realistic situations. The performance of the 12-species reduced model is evaluated against a 21-species skeletal methane oxidation reaction model. The results show excellent agreement between the two models for DNS at . The one-dimensional turbulence (ODT) model is also examined over the same conditions and is shown to be an effective DNS surrogate for evaluating chemical kinetic model reductions.
Modeling of high-speed, methane–air, turbulent combustion, Part I: One-dimensional turbulence modeling with comparison to DNS
2024, Combustion and FlameThe ability of the one-dimensional turbulence (ODT) model to serve as a surrogate direct numerical simulation (DNS) is assessed for highly turbulent flames. The ODT model is applied to freely propagating premixed methane–air flames at Karlovitz numbers 10, 10, 10, and 10, and results are compared with DNS. The ODT model solves the conservation equations for momentum, energy, and species on a one-dimensional domain, which corresponds to a streamwise line of sight spanning the DNS domain. The effects of turbulent advection are modeled via a stochastic process, in which the Kolmogorov and reactive length and time scales are explicitly resolved. Molecular transport and chemical kinetics are concurrently advanced in time. Both the ODT and DNS simulations use a 21-species skeletal chemical model for methane combustion. The accuracy of the ODT model is assessed by comparing its predictions of several key characteristics of the flames for each Karlovitz number tested, including the turbulent flame speed and width and the joint probability density functions (jPDFs) of major and selected minor species as well as the heat release rate conditioned on temperature with the results of DNS under comparable conditions. The ODT model is shown to yield qualitative and quantitative agreement with the DNS data for most of the above flame characteristics. Discrepancies are observed primarily for the jPDFs of several minor species examined. Overall, the ODT approach is shown to be an effective surrogate of DNS, potentially useful for guiding chemical reaction model reduction and for assessing the sensitivities of the flame structure and the burning rate to chemistry under highly turbulent conditions.
Novelty and Significance:
The direct numerical simulations (DNS) of premixed turbulent methane–air flames presented in this work span a uniquely wide range of turbulent intensities, from relatively modest corresponding to Karlovitz number to ultra-high intensities at . This represents virtually the entire range of turbulent intensities that could be encountered in any realistic situation. This is also the first time that such a wide range of conditions is probed for methane in high-fidelity, fully resolved simulations, which use a fully compressible set of flow equations. The one-dimensional turbulence (ODT) model utilizes the same forcing that is present in the DNS enabling a direct comparison between the ODT and DNS. The results show that ODT captures the key features of the DNS results. ODT is shown to be an effective surrogate for DNS and may be useful in guiding chemical reaction model reduction, where many simulations are required.
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.
DRGEP-based mechanism reduction considering time dependency of reaction rate
2023, Chemical Engineering Journal AdvancesImportance of the method to determine interaction coefficient in the DRGEP method is explored by considering the pyrolysis reaction with time variation of temperature. To take into account time dependency, the interaction coefficients were determined using four different methods: the original method and three alternative methods. Two of the three alternative methods use the overall interaction coefficient computed from direct interaction coefficient determined by maximum value of ratio of production rate in each time, and the overall interaction coefficient computed from direct interaction coefficient determined by the averaged value of ratio of production rate in each time, respectively. The other method considers overall interaction coefficient computed from time-dependent direct interaction coefficient. The analytical condition for the mechanism reduction and the assessment of reduction accuracy are the pyrolysis of the gas composed of C2H2, C2H4, and N2 at 1000–1600 K and 0.1 MPa. The concentration of benzene during the simulation by the reduced mechanism was compared with original mechanism. In case of the DRGEP with method, the smallest reduced mechanism with accuracy has 60 species. In contrast, the reduced mechanisms constructed by the DRGEP with the latter two methods of the four accurately predict the concentration with only 45 species. In particular, the method that takes into account the time dependence of the reaction rate was able to describe the behavior in which the formation rate of the target chemical species, benzene, gradually approaches zero near equilibrium, even when the number of chemical species is 40.
Kinetic modeling of ion chemistry in diesel engines using a novel reduced ionic chemical mechanism
2023, Journal of the Taiwan Institute of Chemical EngineersModeling ion current in combustion processes based on chemical kinetics mechanisms, results in more accurately calculating of the temperature and pressure of the combustion chamber. The use of ionic mechanisms also estimates the output pollutants of the combustion chamber with higher accuracy.
The aim of the current study is modelling of ion chemistry during diesel combustion. To achieve this goal, a multi-zone thermodynamic model was used to model the diesel engines performance. The chemistry of the combustion is simulated based on a kinetic mechanism with 327 reactions and 75 species. To reduce this mechanism, the progress rates of the reactions were calculated at the start of combustion, end of combustion, and CAD50 for three different cases, and essential reactions were detected. The reduced mechanism includes 44 species and 92 reactions. At the next step, ions and ion-based reactions were added to the reduced mechanism, and the reduced ionic mechanism was developed with 98 reactions and 49 species
The results show that CH formation during the combustion process is the source of ion production inside the combustion chamber. The reduced ionic mechanism could accurately predict in-cylinder pressure, heat release rate, the start of combustion, and the location of 50% cumulative heat release. The highest error in prediction of CAD50 is less than 0.1%.
A Novel Surrogate Fuel Approach for the Numerical Simulation of Renewable Fuels for the Transport Sector
2023, Energy Conversion and ManagementThe use of fuels made from renewable resources can be beneficial in reducing the CO2 emission balance of the existing vehicle fleet. These fuels should be drop-in-capable, i.e., their properties should correspond as far as possible to those of fossil fuels. In addition, they should be able to be blended with conventional fuels. In order to determine the full potential of new renewable drop-in fuels, numerical investigations can make a significant contribution.
A novel Surrogate Fuel Approach (SFA) was proposed to perform the numerical simulations for blends of paraffinic diesel fuel and alcohols. A set of modeling and mixing rules were used to estimate and extrapolate the required thermo-physical and physicochemical properties of renewable fuels. The detailed chemical mechanisms for n-dodecane and n-octanol were merged. A systematic reduction of the detailed chemical mechanisms was performed using the Directed Relation Graph with Error Propagation (DRGEP) method. For the selected target species, the reduced mechanism from the DRGEP and lumping method contains 31% species and 40% reactions as of the merged reaction mechanism. The blended fuel properties and the reduced reaction mechanism were incorporated into the numerical simulations. The surrogate fuel approach was validated for steady-state as well as transient operating conditions using the experimental results obtained from the optical high-pressure chamber (HPC) and a heavy-duty single-cylinder engine (HD-SCE). The HD-SCE testing shows that the 60% B0-Di/40% RF blend increases ITE by 2% in absolute values and lower ISCO2, ISCO, ISHC and smoke emissions as compared to Diesel fuel. This is due to the paraffinic fuel structure, the fuel-borne oxygen, the high calorific value, and the high cetane number. The calibrated 3D-CFD spray models show an excellent agreement with experimental data from the optical investigations of different spray characteristic values — Liquid and Gaseous penetration Length, Lift of Length and ignition delay for the 60% B0-Di/40% RF fuel. Further, the pressure traces, heat release rates, and nitrogen oxides (NO) emissions from the numerical 3D-CFD simulations showed a good agreement with the results from the HD-SCE experiments. Overall, these results support the suitability of the proposed novel surrogate fuel approach for simulating different blends of renewable drop-in fuels.
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The work was supported by NASA-Lewis Research Center, Grant No. NAG 3-991.