Systematic analysis and reduction of combustion mechanisms for ignition of multi-component kerosene surrogate

Currently, most detailed chemical kinetic mechanisms for combustion are still not comprehensive enough and update of key reaction rate is still required to improve the combustion mechanisms. The development of systematic mechanism reduction methods have made significant progress, and have greatly facilitated analysis of the reaction mechanisms and identification of important species and key reactions. In the present work, time-integrated element flux analysis is employed to analyze a skeletal combustion mechanism of a tri-component kerosene surrogate mixture, consisting of n-decane, n-propylcyclohexane, and n-propylbenzene. The results of element flux analysis indicate that major reaction pathways for each component in the surrogate model are captured by the skeletal mechanism compared with the detailed mechanism. After that, sensitivity analysis (SA) and chemical explosive mode analysis (CEMA) are conducted to identify the dominant ignition chemistry. The SA and CEMA results demonstrate that the ignition of n-decane and n-propylcyclohexane is sensitive only to the oxidation chemistry of H₂/CO and C1–C4 small hydrocarbons, while the ignition of n-propylbenzene is very sensitive to the initial reactions of n-propylbenzene and related aromatic intermediates. This demonstrates that the hierarchic structure should be maintained in the reduction of detailed mechanism of substituted aromatic fuels. The skeletal mechanism is further reduced by combining the computational singular perturbation (CSP) method and quasi steady state approximation (QSSA). A 34-species global reduced mechanism is obtained and validated over a wide range of parameters for ignition.     

Evaluation of reduced combustion kinetic mechanisms using global sensitivity-based similarity analysis (GSSA)

Reduced combustion kinetic mechanisms, instead of detailed ones, are often used in computational fluid dynamics (CFD) simulations for reduced and frequently even affordable computational cost. The criterion for the evaluation of a reduced mechanism usually focuses on its prediction error for the global properties such as the ignition delay time, while ignoring the detailed features of reaction kinetics such as reaction pathways. In our opinion, good reduced mechanisms should have similar predicting behaviors as the detailed ones, and these behaviors include model predictions for specific targets, prediction error bars, and uncertainty sources for the errors. In this work, a new approach using global sensitivity-based similarity analysis (GSSA) is proposed to compare reduced mechanisms with detailed ones. The similarity coefficient for the reduced mechanism is calculated by similarity method based on Euclidean distance between sensitivity indices of the reduced mechanism and those of the detailed mechanism. The larger the similarity coefficient, the higher the degree of similarity between the reduced and detailed mechanisms. To demonstrate this similarity method, directed relation graph with error propagation (DRGEP) is employed to simplify both the GRI 3.0 mechanism without the NOx chemistry and the JetSurF mechanism consisting of 1459 reactions, resulting in reduced mechanisms with different sizes which can accurately predict the ignition delay times for corresponding fuel mixtures. Similarity analysis is then employed to evaluate these reduced mechanisms. The result shows that the actual reaction kinetic features cannot be replicated by some of the reduced mechanisms. First, the rankings of the important reactions obtained by reduced mechanisms are not consistent with those obtained by the detailed mechanism. Second, by investigating the sensitive reactions, the actual impact of uncertainties in reaction rates on the ignition delay times cannot be presented by reduced mechanisms. The similarity analysis on reduced mechanisms can be used to select a reduced mechanism which shows much better performance to replicate the actual combustion reaction kinetics. GSSA can provide information on the uncertainty sources induced by the reactions parameters of reduced mechanisms for target predictions, which is important for further reduced model optimization and for the sensitivity analysis of CFD simulations.     

Detailed investigation of soot formation from jet fuel in a diffusion flame with comprehensive and hybrid chemical mechanisms

A numerical and experimental study is performed to investigate soot formation from jet fuel in a laminar coflow diffusion flame. The combustion chemistry of the fuel is simulated using (1) the MURI jet fuel surrogate (Dooley et al. 2012) with a modestly reduced Ranzi mechanism (Ranzi et al. 2012), and (2) the recently proposed HyChem model (Xu et al. 2018) combined with the KAUST PAH mechanism 2 (Wang et al. 2013). The two reaction mechanisms are coupled with a sectional soot model to simulate a coflow diffusion flame of methane doped with the MURI jet fuel surrogate. The combined laser extinction and two-angle elastic light scattering method is used to perform non-intrusive in situ measurements of soot volume fraction, primary particle diameter and number density. The good agreement including soot particle size and number density between the experimental data and the simulation results computed with the reduced Ranzi mechanism demonstrate the robustness of the soot model to changes in fuel composition, as the model parameters are unchanged with a previous numerical study of soot formation of n-propylbenzene/n-dodecane mixtures (Zhang and Thomson, 2018). The computation with the combined HyChem/KAUST mechanism predicts similar results as the computation with the detailed chemistry of the reduced Ranzi mechanism for fuel breakdown, thus the basic premise of the HyChem model that the fuel decomposition process can be greatly simplified with the lumped reaction steps is supported. The results also show that by adding a PAH growth scheme to the HyChem model, the approach can be used to predict soot formation from jet fuel combustion in a laminar coflow diffusion flame. Finally, the dependency of the soot prediction on PAH chemistry is discussed and it is suggested that more experimental data is needed to validate the PAH mechanism and improve the predictive accuracy of the model.     

A reduced mechanism for biodiesel surrogates with low temperature chemistry for compression ignition engine applications

Biodiesel is a promising alternative fuel for compression ignition (CI) engines. It is a renewable energy source that can be used in these engines without significant alteration in design. The detailed chemical kinetics of biodiesel is however highly complex. In the present study, a skeletal mechanism with 123 species and 394 reactions for a tri-component biodiesel surrogate, which consists of methyl decanoate, methyl 9-decanoate and n-heptane was developed for simulations of 3-D turbulent spray combustion under engine-like conditions. The reduction was based on an improved directed relation graph (DRG) method that is particularly suitable for mechanisms with many isomers, followed by isomer lumping and DRG-aided sensitivity analysis (DRGASA). The reduction was performed for pressures from 1 to 100 atm and equivalence ratios from 0.5 to 2 for both extinction and ignition applications. The initial temperatures for ignition were from 700 to 1800 K. The wide parameter range ensures the applicability of the skeletal mechanism under engine-like conditions. As such the skeletal mechanism is applicable for ignition at both low and high temperatures. Compared with the detailed mechanism that consists of 3299 species and 10806 reactions, the skeletal mechanism features a significant reduction in size while still retaining good accuracy and comprehensiveness. The validations of ignition delay time, flame lift-off length and important species profiles were also performed in 3-D engine simulations and compared with the experimental data from Sandia National Laboratories under CI engine conditions.     

Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes

Acceleration of the chemistry solver for engine combustion is of much interest due to the fact that in practical engine simulations extensive computational time is spent solving the fuel oxidation and emission formation chemistry. A dynamic adaptive chemistry (DAC) scheme based on a directed relation graph error propagation (DRGEP) method has been applied to study homogeneous charge compression ignition (HCCI) engine combustion with detailed chemistry (over 500 species) previously using an R-value-based breadth-first search (RBFS) algorithm, which significantly reduced computational times (by as much as 30-fold). The present paper extends the use of this on-the-fly kinetic mechanism reduction scheme to model combustion in direct-injection (DI) engines. It was found that the DAC scheme becomes less efficient when applied to DI engine simulations using a kinetic mechanism of relatively small size and the accuracy of the original DAC scheme decreases for conventional non-premixed combustion engine. The present study also focuses on determination of search-initiating species, involvement of the NO_x chemistry, selection of a proper error tolerance, as well as treatment of the interaction of chemical heat release and the fuel spray. Both the DAC schemes were integrated into the ERC KIVA-3v2 code, and simulations were conducted to compare the two schemes. In general, the present DAC scheme has better efficiency and similar accuracy compared to the previous DAC scheme. The efficiency depends on the size of the chemical kinetics mechanism used and the engine operating conditions. For cases using a small n-heptane kinetic mechanism of 34 species, 30% of the computational time is saved, and 50% for a larger n-heptane kinetic mechanism of 61 species. The paper also demonstrates that by combining the present DAC scheme with an adaptive multi-grid chemistry (AMC) solver, it is feasible to simulate a direct-injection engine using a detailed n-heptane mechanism with 543 species with practical computer time.     

Skeletal mechanism generation with CSP and validation for premixed n-heptane flames

An automated procedure has been previously developed to generate simplified skeletal reaction mechanisms for the combustion of n-heptane/air mixtures at equivalence ratios between 0.5 and 2.0 and different pressures. The algorithm is based on a Computational Singular Perturbation (CSP)-generated database of importance indices computed from homogeneous n-heptane/air ignition solutions. In this paper, we examine the accuracy of these simplified mechanisms when they are used for modeling laminar n-heptane/air premixed flames. The objective is to evaluate the accuracy of the simplified models when transport processes lead to local mixture compositions that are not necessarily part of the comprehensive homogeneous ignition databases. The detailed mechanism was developed by Curran et al. and involves 560 species and 2538 reactions. The smallest skeletal mechanism considered consists of 66 species and 326 reactions. We show that these skeletal mechanisms yield good agreement with the detailed model for premixed n-heptane flames, over a wide range of equivalence ratios and pressures, for global flame properties. They also exhibit good accuracy in predicting certain elements of internal flame structure, especially the profiles of temperature and major chemical species. On the other hand, we find larger errors in the concentrations of many minor/radical species, particularly in the region where low-temperature chemistry plays a significant role. We also observe that the low-temperature chemistry of n-heptane can play an important role at very lean or very rich mixtures, reaching these limits first at high pressure. This has implications to numerical simulations of non-premixed flames where these lean and rich regions occur naturally.     

Mechanisms of the oxidation and combustion of normal paraffin hydrocarbons: Transition from C1–C10 to C11–C16

Recently, detailed kinetic mechanisms of the oxidation and combustion of higher hydrocarbons, composed of hundreds of components and thousands of elementary reactions, have been proposed. Despite the undoubtful advantages of such detailed mechanisms, their application to simulations of turbulent combustion and gas dynamic phenomena is difficult because of their complexity. At the same time, to some extent limited, they cannot be considered exhaustive. This work applies previously proposed algorithm for constructing an optimal mechanism of the high- and low-temperature oxidation and combustion of normal paraffin hydrocarbons, which takes into account the main processes determining the reaction rate and the formation of key intermediates and final products. The mechanism has the status of a nonempirical detailed mechanism, since all the constituent elementary reactions have a kinetic substantiation. The mechanism has two specific features: (1) it does not include reactions of so-called double oxygen addition (first to the peroxide radical, and then to its isomeric form), i.e., the first addition turns out to be sufficient; (2) it does not include isomeric compounds and their derivatives as intermediates, since this oxidation pathway is slower than the oxidation of molecules and radicals with normal structure. Application of the algorithm makes it possible to compile a compact mechanism, which is important for modeling chemical processes involving paraffin hydrocarbons C _n with large n. Previously, based on this algorithm, compact mechanisms of the oxidation and combustion of propane, n-butane, n-pentane, n-hexane, n-heptane, n-octane, n-nonane, and n-decane have been constructed. In this work, we constructed a nonempirical detailed mechanism of the oxidation and combustion of hydrocarbons from n-undecane to n-hexadecane. The most important feature of the new mechanism is its staged nature, which manifests itself through the emergence of cool and blue flames during low-temperature autoignition. The calculation results are compared with experimental data.     

Influence of NOx chemistry on the prediction of natural gas end-gas autoignition in CFD engine simulations

Natural gas (NG) represents a promising low-cost/low-emission alternative to diesel fuel when used in high-efficiency internal combustion engines. Advanced combustion strategies utilizing high EGR rates and controlled end-gas autoignition can be implemented with NG to achieve diesel-like efficiencies; however, to support the design of these next-generation NG ICEs, computational tools, including single- and multi-dimensional simulation packages will need to account for the complex chemistry that can occur between the reactive species found in EGR (including NOx) and the fuel. Research has shown that NOx plays an important role in the promotion/inhibition of large hydrocarbon autoignition and when accounted for in CFD engine simulations, can significantly improve the prediction of end-gas autoignition for these fuels. However, reduced NOx-enabled NG mechanisms for use in CFD engine simulations are lacking, and as a result, the influence of NOx chemistry on NG engine operation remains unknown. Here, we analyze the effects of NOx chemistry on the prediction of NG/oxidizer/EGR autoignition and generate a reduced mechanism of a suitable size to be used in engine simulations. Results indicate that NG ignition is sensitive to NOx chemistry, where it was observed that the addition of EGR, which included NOx, promoted NG autoignition. The modified mechanism captured well all trends and closely matched experimentally measured ignition delay times for a wide range of EGR rates and NG compositions. The importance of C2-C3 chemistry is noted, especially for wet NG compositions containing high fractions of ethane and propane. Finally, when utilized in CFD simulations of a Cooperative Fuels Research (CFR) engine, the new reduced mechanism was able to predict the knock onset crank angle (KOCA) to within one crank angle degree of experimental data, a significant improvement compared to previous simulations without NOx chemistry.     

A functional-group-based approach to modeling real-fuel combustion chemistry – III: Application to biodiesels

Real biodiesel fuels are mixtures comprising many high molecular weight components, making it a challenge to predict their combustion chemistry with detailed kinetic models. Our group previously proposed a functional-group approach (FGMech) to model the combustion chemistry of real gasoline and jet fuels; this approach has now been extended to model real biodiesel combustion and mixtures with petroleum fuels. As in our previous work, a decoupling philosophy is adopted for construction of the model. A lumped reaction mechanism describes the (oxidative) pyrolysis of fuels, while a detailed base chemistry model represents the oxidation of key pyrolysis intermediates. However, due to the presence of the ester group, several oxygenated species are identified as additional primary products and incorporated into the lumped reaction steps. In addition to the lumped reactions initiated by unimolecular decomposition and H-atom abstraction reactions, a lumped H-atom addition-elimination reaction is also incorporated as a new reaction class to account for the presence of double bonds. Stoichiometric parameters are obtained based on a multiple linear regression (MLR) model, which establishes relationships between the fuel's functional group distributions and the stoichiometric parameters of the lumped reactions. Global rate constants are developed from consistent rate rules obtained from pure fuels. New pyrolysis experimental data for methyl pentanoate/methyl nonanoate and methyl heptanoate/n-heptane mixtures (50%/50% in mol) are obtained in a jet-stirred reactor at atmospheric pressure. In general, kinetic models developed using the FGMech approach can reasonably reproduce all the validation targets obtained in this work, as well as those in the literature, confirming that functional-group-modeling is a promising approach to simulate combustion behavior of diesel/biodiesel surrogate fuels and real biodiesels.     

Experimental and modeling study of the high-temperature combustion chemistry of tetrahydrofurfuryl alcohol

Lignocellulosic tetrahydrofuranic (THF) biofuels have been identified as promising fuel candidates for spark-ignition (SI) engines. To support the potential use as transportation biofuels, fundamental studies of their combustion and emission behavior are highly important. In the present study, the high-temperature (HT) combustion chemistry of tetrahydrofurfuryl alcohol (THFA), a THF based biofuel, was investigated using a comprehensive experimental and numerical approach.Representative chemical species profiles in a stoichiometric premixed methane flame doped with ～20% (molar) THFA at 5.3 kPa were measured using online gas chromatography. The flame temperature was obtained by NO laser-induced fluorescence (LIF) thermometry. More than 40 chemical products were identified and quantified. Many of them such as ethylene, formaldehyde, acrolein, allyl alcohol, 2,3-dihydrofuran, 3,4-dihydropyran, 4-pentenal, and tetrahydrofuran-2-carbaldehyde are fuel-specific decomposition products formed in rather high concentrations. In the numerical part, as a complement to kinetic modeling, high-level theoretical calculations were performed to identify plausible reaction pathways that lead to the observed products. Furthermore, the rate coefficients of important reactions and the thermochemical properties of the related species were calculated. A detailed kinetic model for high-temperature combustion of THFA was developed, which reasonably predicts the experimental data. Subsequent rate analysis showed that THFA is mainly consumed by H-abstraction reactions yielding several fuel radicals that in turn undergo either β-scission reactions or intramolecular radical addition that effectively leads to ring enlargement. The importance of specific reaction channels generally correlates with bond dissociation energies. Along THFA reaction routes, the derived species with cis configuration were found to be thermodynamically more stable than their corresponding trans configuration, which differs from usual observations for hydrocarbons.     

Flame enhancement of ethylene/methane mixtures by ozone addition

As one of the longest lasting species in plasma-assisted combustion, ozone has a pronounced effect on ignition and flame propagation. Many previous studies, however, have only investigated the combustion enhancement by ozone for single-component fuels. In the present study, the impact of ozone addition on multi-component fuel mixtures is examined through one-dimensional laminar flame simulations across a range of temperatures, pressures, residence times, and mixture compositions. Due to the presence of an alkene (ethylene), ozone is consumed through pre-flame ozonolysis reactions even at room temperature. The flame speed is shown to be dependent on the domain length (residence time), and a new reference flame speed is defined for ozonolysis-assisted flame propagation. It is also found that the flame speed enhancement by ozone is highly nonlinear, as a small amount of ethylene produces a disproportionate boost in the laminar flame speed. Finally, the competition between ozonolysis, ozone decomposition, and other ozone reactions in a mixture of alkenes and alkanes is examined in detail. Increases in the pressure, temperature, and equivalence ratio (for rich mixtures) favor ozonolysis reactions over other ozone reactions. The results of this study provide important insights into the timescales, length scales, and reaction pathways that govern ozone-assisted combustion of multi-component fuels in real combustors.     

振荡燃烧过程的计算和诊断

振荡燃烧现象是在发展洁净,高效和安全动力推进系统经常会遇到的问题.本文综述了作者近些年在针对油雾振荡燃烧方面的研究工作.通过把CFD和稳定性分析结合起来,发展了预测和诊断振荡燃烧的非稳定性及其振荡频率的新方法.运用这一方法,求解系统稳态方程和线性扰动方程可得到流场的动态信息和其稳定模态,将为深入认识振荡燃烧机理和开发控制方法提供指导.     

The mechanisms of oxidation and combustion of normal alkane hydrocarbons: The transition from C1–C3 to C4H10

The known detailed mechanisms of oxidation of the higher hydrocarbons include hundreds of particles and thousands of reactions. In spite of their merits, the use of such mechanisms for solving applied problems of the gas dynamics of combustion is impeded at present because of great computational expenditures. We suggest a compact kinetic mechanism of the oxidation of n-butane including the main processes and intermediate and final reaction products. The mechanism can be classified as a nonempirical detailed mechanism, because all its elementary reactions are kinetically substantiated. The mechanism does not contain reactions of the double addition of oxygen and intermediate species in the form of isomeric compounds and their derivatives. The calculation results are compared with the experimental data on the oxidation, self-ignition, and combustion of n-butane.     

Mechanism of the oxidation and combustion of normal paraffin hydrocarbons: Transition from C<Subscript>1</Subscript>–C<Subscript>6</Subscript> to C<Subscript>7</Subscript>H<Subscript>16</Subscript>

A previously proposed algorithm for constructing an optimal mechanism of the high- and low-temperature oxidation and combustion of normal paraffin hydrocarbons was used, which includes the major processes that determine the rate of reaction and the formation of the main intermediate and final products. The mechanism has the status of a nonempirical detailed mechanism, since all the constituent elementary reactions have a kinetic substantiation. The mechanism has two specific features: it included no reactions of so-called double addition of oxygen and no isomeric compounds and derivatives thereof as intermediate species. Realization of this algorithm leads to fairly compact models, a circumstance important for studies of chemical processes involving paraffin hydrocarbons C _n with large n. Previously, based on this algorithm, compact mechanisms of oxidation and combustion of propane, n-butane, n-pentane, and n-hexane were constructed. In this paper, we develop a nonempirical detailed mechanism of oxidation and combustion of n-heptane. The most important feature of the new mechanism is its ability to predict the staging of the process in the form of cool and blue flames at low autoignition temperatures. A comparison of the simulation results with the available experimental data is conducted.     

Theoretical analysis on the exergy destruction mechanisms and reduction under LTC relevant conditions

Low temperature combustion (LTC) is a potential thermodynamic pathway to maximize the thermal efficiency of internal combustion (IC) engines. However, high exergy loss is also observed within this combustion concept. The present study focuses on the homogeneous combustion process and examines the detailed exergy destruction mechanisms under representative LTC engine conditions. By varying both equivalence ratios (φ) and temperatures (T) at initial pressure of 50?bar, it is found that the decreased total exergy destruction fraction (f_ED) with increasing initial temperature mainly results from the decreased exergy destruction in the high temperature heat release stage, while using rich mixture can significantly reduce the f_ED in the ignition delay stage, which is dominated by the reactions involving large molecules (C7 species). Reaction pathway analysis reveals that the detailed exergy destruction sources are significantly affected by the reaction pathways. Furthermore, a qualitative exergy loss φ-T map was created to illustrate the exergy loss reduction potential. It is concluded that the combustion pathway that reforming the rich fuel/air mixtures before ignition followed by the low temperature combustion of lean reforming products offers the potential to simultaneously reduce exergy destruction and avoid soot and NOx formation. However, the potential advantages of this exergy reduction combustion concept still require further work.     

LES modelling of turbulent non-premixed jet flames with correlated dynamic adaptive chemistry

Large eddy simulations (LES) for turbulent flames with detailed kinetic mechanisms have received growing interest. However, a direct implementation of detailed kinetic mechanisms in LES modelling of turbulent combustion remains a challenge due to the requirement of huge computational resources. An on-the-fly mechanism reduction method named correlated dynamic adaptive chemistry (CoDAC) is proposed to overcome this issue. A LES was conducted for Sandia Flame-D, with the reaction mechanism of GRI-Mech 3.0 consisting of 53 species and 325 reactions. The reduction threshold used in LES was obtained a priori by using auto-ignition model and partially stirred reactor (PaSR) with pairwise mixing model. LES results with CoDAC are in good agreement with experimental data and those without reduction. The conditional mean of the number of selected species indicates that a large size of locally reduced mechanism is required in the reaction zone where CH₄ is destructed. A computational time analysis shows that the PaSR model predicts better than the auto-ignition model on the wall time reduction with CoDAC in LES.     

Numerical simulation and validation of SI-CAI hybrid combustion in a CAI/HCCI gasoline engine

SI-CAI hybrid combustion, also known as spark-assisted compression ignition (SACI), is a promising concept to extend the operating range of CAI (Controlled Auto-Ignition) and achieve the smooth transition between spark ignition (SI) and CAI in the gasoline engine. In this study, a SI-CAI hybrid combustion model (HCM) has been constructed on the basis of the 3-Zones Extended Coherent Flame Model (ECFM3Z). An ignition model is included to initiate the ECFM3Z calculation and induce the flame propagation. In order to precisely depict the subsequent auto-ignition process of the unburned fuel and air mixture independently after the initiation of flame propagation, the tabulated chemistry concept is adopted to describe the auto-ignition chemistry. The methodology for extracting tabulated parameters from the chemical kinetics calculations is developed so that both cool flame reactions and main auto-ignition combustion can be well captured under a wider range of thermodynamic conditions. The SI-CAI hybrid combustion model (HCM) is then applied in the three-dimensional computational fluid dynamics (3-D CFD) engine simulation. The simulation results are compared with the experimental data obtained from a single cylinder VVA engine. The detailed analysis of the simulations demonstrates that the SI-CAI hybrid combustion process is characterised with the early flame propagation and subsequent multi-site auto-ignition around the main flame front, which is consistent with the optical results reported by other researchers. Besides, the systematic study of the in-cylinder condition reveals the influence mechanism of the early flame propagation on the subsequent auto-ignition.     

Adaptive digital twins of combustion systems using sparse sensing strategies

This work proposes to implement a sparse sensing framework to build a hybrid numerical-experimental Digital Twin of a practical combustion system. The goal is to find the optimal sensor placement that minimizes the prediction error, and to predict the distribution of reacting scalars using few measurements. Three-dimensional CFD simulations with detailed chemistry were used to build the design space by varying the fuel composition (from pure methane to pure hydrogen), the equivalence ratio (from 0.7 to 1) and the air velocity. The Proper Orthogonal Decomposition (POD) was applied to the numerical data to find a tailored basis for dimensionality reduction. Then, the QR decomposition with column pivoting was applied to the tailored basis to find the optimal sensor placement. Finally, the model was employed to predict the three-dimensional temperature distribution in the unexplored part of the design space, using the experimental samples as input. The optimal placement of the sensors provides valuable information on the key locations and features, which can then be used in the design of reactor network models, for example. Also, the results show that the hybrid Digital Twin could predict an adjusted temperature distribution which reduces the error with the experimental measurements, when compared to the original CFD temperature distribution.