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. 2020 Mar 5;5(10):4924–4936. doi: 10.1021/acsomega.9b03786

Comprehensive Comparison of the Combustion Behavior for Low-Temperature Combustion of n-Nonane

Junjiang Guo †,‡,*, Weijun Peng †, Shijie Zhang †, Jiazhi Lei †, Jiantong Jing †, Ruyi Xiao †, Shiyun Tang †,‡
PMCID: PMC7081281  PMID: 32201778

Abstract

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To meet the increasing need for clean combustion, improve the combustion efficiency of fuels, and reduce the pollutants produced in the combustion process, it is necessary to systematically study the combustion of hydrocarbon fuels. An accurate and detailed chemical kinetic model is an important prerequisite for understanding the combustion performance of hydrocarbon fuels and studying complex chemical reaction networks. Therefore, based on ReaxGen, new detailed mechanisms for the low-temperature combustion of n-nonane are proposed and verified in detail in this study. Meanwhile, some international mainstream combustion models such as the LLNL model and the JetSurf 2.0 model are compared with ours, showing that the proposed new mechanisms can better predict the ignition delay combustion characteristics of n-nonane, and they also hold in a wide range of conditions. In addition, the numerical simulation results of the concentration curve calculated for the new mechanisms, especially Model v2, are in good agreement with the experimental data, and the mechanisms can reproduce the performance of the negative-temperature-coefficient behavior toward n-nonane ignition. The numerical simulation results of the laminar flame propagation velocity varying with the equivalence ratio are also in good agreement with the available experimental data. Finally, the ignition delay sensitivity of n-nonane is analyzed by the sensitivity analysis method; the key reactions affecting the ignition mechanism are investigated; and the reaction path analysis is conducted to better understand the models’ predicted performance. In a word, the new mechanisms are helpful to understand the ignition properties of large hydrocarbon fuels for high-speed aircrafts.

1. Introduction

With the development of the aerospace industry, especially the acquisition of supersonic flight technology, higher technical requirements are put forward for the development and design of advanced engines. Aviation fuel gradually emerged with the birth of the aircraft at the beginning of this century. In order to ensure flight safety and long lifespan of engines, there are strict requirements on fuel quality. Linear paraffins usually account for a large proportion of diesel and aviation fuels.1,2 The literature shows that the mass fraction of RP-3 aviation kerosene is as high as 72.0%.3 At present, the basic combustion data on linear alkanes from methane to octane are abundant, and combustion-related measurement data on n-decane, n-dodecane, and other large hydrocarbons can be effectively obtained. Nonetheless, research on the oxidation chemistry of n-nonane is very scarce. Taking into account that n-nonane is a typical representative of paraffin in petroleum-based fuels,3−5 experimental and theoretical studies on n-nonane combustion are particularly necessary for the development of clean and efficient combustion and the development of new energy fuels.

The detailed description of the existing experimental data on n-nonane combustion is shown in Table 1.4,6−11 Although establishing a comprehensive n-nonane kinetic mechanism to describe its oxidation under a wide range of experimental conditions is important because of the complexity of large hydrocarbon fuels, the kinetic models currently used to describe n-nonane combustion are extremely rare, and are primarily acquired by manual construction. Among them, Westbrook et al. developed a kinetic model (LLNL model)12 for describing the pyrolysis and oxidation of linear alkanes (from n-octane to n-hexadecane) over a wide temperature range; Wang et al. developed a kinetic model (JetSurf 2.0 model)13 for the high-temperature oxidation of linear alkanes; cyclohexane; and methyl, ethyl, n-propyl, and n-butyl cyclohexanes. Because the detailed combustion mechanism usually contains a very large number of species and reactions, the mechanism for manual construction takes a long time and is prone to errors. Conversely, this paper proposes a method to develop a high-precision low-temperature mechanism for the combustion of n-nonane using an automatic mechanism construction program.

Table 1. Ignition Delay Time, Flame Speed, and Speciation Measurements for n-Nonane Combustion in Literature.

    initial conditions
 reactant composition %
  
experiment year T (K) P (atm) ϕ n-C9H20 O2 bath gas references
shock tube 2010 1150–1550 1–4 0.5–2.0   4.0 Ar (6)
shock tube 2013 1263–1672 1.5–10 0.5–1.0 0.034–0.125   99.0 (Ar) (4)
shock tube 2016 1168–1600 2–20 0.5–2.0 0.143–0.571 4.0 Ar (7)
shock tube 2017 684–1448 2–15 0.5–2.0     N2 (8)
flow reactor 2018 750–1200 1 0.5–2.0 3.34–12.4 (sccm) 86.5–97.5 (sccm) 99.0 (Ar) (9)
jet-stirred reactor 2011 500–1100 1–10 0.5–2.0 0.1 0.7–2.8 N2 (10)
burning velocities flame 2010 403 1 0.7–1.5     N2 (4)
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At present, there have been a few automatic mechanism generation programs, such as EXGAS14 developed by Battin-Leclerc et al., MAMOX15 developed by Ranzi’s research group in Milan, REACTION16 developed by Blurock et al., RMG17 developed by Green et al., and ReaxGen18 developed by Li Xiang Yuan’s team. Among them, ReaxGen has successfully developed some low-temperature combustion mechanisms for large hydrocarbons, such as n-heptane,19,20n-decane,21 and n-undecane.21 Accordingly, this paper mainly uses ReaxGen to automatically generate the new detailed mechanisms for low-temperature combustion of n-nonane. In order to verify the reliability and rationality of the new mechanisms, a few internationally published models that can be used for n-nonane combustion simulation are compared with them, such as the LLNL model12 and the JetSurf 2.0 model.13 This study aims to investigate the ignition delay time in a shock tube, the concentration of important species in the jet stirred reactor (JSR), and the propagation speed of the premixed laminar flame. Furthermore, the numerical simulation results of these combustion models are analyzed and compared with the effective experimental data in literature. Finally, the sensitivity analysis and the reaction path analysis are used to identify the types of reactions that are critical for low-temperature ignition.

2. Mechanism Construction

The detailed combustion mechanism of hydrocarbon fuels can be constructed according to the hierarchical structure.19,22 The core mechanism is crucial to explain the combustion characteristics of large hydrocarbons.23 Generally, the mechanism construction for large hydrocarbons mainly includes two parts: the core mechanism and the expansion mechanism. The core mechanism is mainly low-carbon hydrocarbon molecules and free radicals (less than four carbon atoms). Previous studies have shown that AramcoMech 1.324 and AramcoMech 3.025 developed by Curran’s group have a good effect on the mechanism construction for large hydrocarbons.19 Therefore, the new mechanisms of n-nonane developed in this study are mainly based on AramcoMech 1.3 and AramcoMech 3.0, respectively. In addition, the expansion mechanisms are automatically generated by ReaxGen. The fundamental concept in generating a mechanism by ReaxGen is the reaction classes. The specific reaction classes in this work are mainly:18,21,26

High-temperature combustion reaction classes:

  • (1)

    Unimolecular decomposition of alkanes;

  • (2)

    H-abstraction from C atoms in alkanes by O, H, OH, O2, CH3, C2H3, C2H5, and HO2;

  • (3)

    Mutual isomerization of the alkyl radical;

  • (4)

    Decomposition of the alkyl radical;

  • (5)

    Oxidation of an alkyl radical to form an alkene;

  • (6)

    H-abstraction from alkenes;

  • (7)

    Decomposition of alkenes;

  • (8)

    Addition of alkenes to O, OH, CH3, H, and HO2 (CH3, H, and HO2 are not included in this work);

  • (9)

    Decomposition of the alkenyl radical;

  • (10)

    Retro-ene decomposition reactions;

  • (11)

    Mutual isomerization of the alkenyl radical;

  • (12)

    Lumped consumption reaction of the diene.

Low-temperature combustion reaction classes:

  • (13)

    Alkyl addition to the oxygen molecule (•R + O2 = ROO•);

  • (14)

    Isomerization of ROO• (ROO• = QOOH•);

  • (15)

    ROO• reacts with HO2, H2O2, and the fuel molecule (RH) to form a hydroperoxide (ROO• + HO2/H2O2/RH = ROOH + O2/HO2/•R);

  • (16)

    ROOH = RO + OH;

  • (17)

    Decomposition of alkoxy radicals;

  • (18)

    Hydroperoxy alkyl radical addition to the oxygen molecule (QOOH• + O2 = O2QOOH);

  • (19)

    Decomposition of hydroperoxy alkyl radicals to form alkenes and aldehydes;

  • (20)

    Decomposition of hydroperoxy alkyl radicals to form cyclic ethers;

  • (21)

    β-pyrolysis of hydroperoxy alkyl radicals to form smaller alkyls;

  • (22)

    Oxidation of hydroperoxy alkyl radicals;

  • (23)

    Isomerization of O2QOOH (O2QOOH = HOOQ′OOH);

  • (24)

    Homolytic O–O scission of dihydroperoxy alkyl radicals;

  • (25)

    Decomposition of dihydroperoxy alkyl radicals to form hydroperoxy cyclic ethers;

  • (26)

    Decomposition of ketohydroperoxides;

  • (27)

    Decomposition of large carbonyl radicals;

  • (28)

    H-abstraction from the cyclic ether;

  • (29)

    Decomposition of the hydroperoxyl cyclic ether;

  • (30)

    H-abstraction from aldehydes;

  • (31)

    H-abstraction from ketones.

The kinetic parameters of these reaction classes are provided in the Supporting Information. Finally, the new n-nonane combustion mechanisms, Model v1, based on AramcoMech 1.3, including 1200 species and 4615 reactions, and Model v2, based on AramcoMech 3.0, including 1506 species and 6068 reactions, are developed (provided in the Supporting Information). In these mechanisms, the thermodynamic data and transport data for species in the core mechanisms are derived from refs (24) and (25), respectively; the thermodynamic data for other species are mainly calculated by the group contribution method proposed by Benson;27 transport data for other species are calculated through the diffusion coefficients using the approach introduced in ref (28).

3. Results and Discussion

3.1. Mechanism Validation and Comparison

In order to improve the accuracy and the applicability of the mechanisms, extensive verification is needed for the experimental data on various fuels in different temperature ranges, pressure ranges, the reaction atmosphere, and the physical model. At present, the combustion reaction dynamics experiments used to verify the model involve macroscopic combustion parameters such as the ignition delay time and the flame propagation speed and microscopic combustion parameters such as species concentration. In this paper, the new mechanisms for n-nonane combustion are verified by the experiments of the ignition delay time in a shock tube, species concentration in a JSR, and the laminar flame propagation speed. At the same time, a detailed comparison is made between the new mechanisms based on automatic program construction and the international mainstream mechanisms based on manual construction.

3.1.1. Ignition Delay in a Shock Tube

Yong et al.9 systematically studied gas-phase ignition delay experiments for n-nonane/air mixtures at temperatures ranging from 684 to 1448 K; pressures ranging from 2.0 to 15.0 atm; and equivalence ratios of 0.5, 1.0, and 2.0. The n-nonane shock tube ignition delay experiment was simulated, with the new mechanisms and the international mainstream combustion mechanisms,12,13 by the homogeneous closed reactor model in the Chemkin-Pro package.29 The assumption of adiabatic, constant volume, and homogeneous conditions is applied for high-temperature conditions. Moreover, at longer ignition delay times such as low-temperature ignition, the gradual pressure increase can have considerable effects on the ignition process. To consider this pressure increase, an average pressure rise rate of 3%/ms was considered by employing the Senkin/VITM approach.30 The comparison between the numerical simulation results and the experimental data is shown in Figures 1–3. The results show that the new mechanisms and the LLNL model12 can well predict the ignition and combustion characteristics at different equivalence ratios. Because the JetSurf 2.0 model13 does not contain the low-temperature combustion reaction classes of n-nonane, it can be seen that this model can only well predict the high-temperature ignition. On the contrary, the new mechanisms can accurately reproduce the negative-temperature-coefficient (NTC) behavior of n-nonane ignition under different conditions. However, some differences are still found. For example, in Figures 1c, 2d, and 3c, the new mechanisms and the LLNL model can give a good simulation performance, but in the low-temperature range (T < 750 K), there are some discrepancies between the numerical simulation results and the experimental data. Besides, as shown in Figure 3a, the predicted values of the LLNL model under rich combustion conditions are slightly higher than the experimental data, those of Model v1 are slightly lower than the experimental data, and those of Model v2 are in best agreement with the experimental data. However, at a pressure of 5 atm, as shown in Figure 3b, it can be found that the LLNL model and the JetSurf 2.0 model are in good agreement with the experimental data, while our models slightly underpredict the experimental data. Different combustion results are obtained because of the discrepancies in the reaction network and reaction rates in different combustion models.19 From the results of ignition simulation, it is seen that the new mechanisms and the LLNL model show a higher simulation accuracy.

Figure 1.

Figure 1

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Ignition delay time of n-nonane/air mixtures in a shock tube at Φ = 0.5, with pressures of (a) 2, (b) 5, and (c) 15 atm.

Figure 3.

Figure 3

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Ignition delay time of n-nonane/air mixtures in a shock tube at Φ = 2.0, with pressures of (a) 2, (b) 5, and (c) 15 atm.

Figure 2.

Figure 2

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Ignition delay time of n-nonane/air mixtures in a shock tube at Φ = 1.0, with pressures of (a) 2, (b) 5, (c) 9, and (d) 15 atm.

3.1.2. Jet-Stirred Reactor Speciation

Dagaut et al.4 experimentally studied the oxidation of n-nonane in the JSR over a wide range of conditions, which provided the basic data for verifying the rationality of the combustion mechanism of n-nonane. In this paper, the evolution of the concentration of important components such as n-nonane, C2H4, CH4, CH2O, CO, CO2, H2, and H2O was studied. The simulations in this section were carried out by using the transient perfectly stirred reactor code with an end time of 20 s in the Chemkin-Pro package, whose method is similar to that employed by Metcalfe et al.24 and Sarathy et al.31 The measurements and predictions with Model v1, Model v2, the LLNL model, and the JetSurf 2.0 model for the molar fraction profiles of n-nonane, C2H4, CH4, CH2O, CO, CO2, H2, and H2O are shown in Figures 4–9. The simulation conditions are performed at an initial concentration of 0.1% n-nonane; equivalent ratios of 0.5, 1.0, and 2.0; pressures of 1 and 10 atm; and residence times of 0.07 and 0.7 s. It can be seen from the figures that the numerical simulation results of the new mechanisms are in overall agreement with the available experimental data, especially at atmospheric pressure and with a residence time of 0.07 s (shown in Figures 4, 6, and 8). Model v2 is found to be superior to other combustion models for CO, CO2, H2, and H2O predictions, except for the H2O molar fraction in the NTC region, as shown in Figures 5h, 7h and 9h, for which Model v2 underpredicts the experimental data. In addition, the NTC behavior of n-nonane was discovered experimentally between 600 and 750 K, which is well reproduced by the new mechanisms from the evolution of n-nonane, CO, and H2O, as shown in Figures 5, 7, and 9. In contrast, the JetSurf 2.0 model cannot reproduce the NTC behavior of fuel combustion well (shown in Figures 5a, 7a, and 9a) because of the lack of low-temperature reactions in this model.

Figure 4.

Figure 4

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Comparison of the experimental and simulated results using different mechanisms for important species concentrations containing (a) n-C9H20, (b) C2H4, (c) CH2O, (d) CH4, (e) CO, (f) CO2, (g) H2, and (h) H2O in a JSR for 0.1% n-nonane diluted in nitrogen at 1 atm, ϕ = 0.5, and 0.07 s residence time.

Figure 9.

Figure 9

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Comparison of the experimental and simulated results using different mechanisms for important species concentrations containing (a) n-C9H20, (b) C2H4, (c) CH2O, (d) CH4, (e) CO, (f) CO2, (g) H2, and (h) H2O in a JSR for 0.1% n-nonane diluted in nitrogen at 10 atm, ϕ = 2.0, and 0.7 s residence time.

Figure 6.

Figure 6

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Comparison of the experimental and simulated results using different mechanisms for important species concentrations containing (a) n-C9H20, (b) C2H4, (c) CH2O, (d) CH4, (e) CO, (f) CO2, (g) H2, and (h) H2O in a JSR for 0.1% n-nonane diluted in nitrogen at 1 atm, ϕ = 1.0, and 0.07 s residence time.

Figure 8.

Figure 8

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Comparison of the experimental and simulated results using different mechanisms for important species concentrations containing (a) n-C9H20, (b) C2H4, (c) CH2O, (d) CH4, (e) CO, (f) CO2, (g) H2, and (h) H2O in a JSR for 0.1% n-nonane diluted in nitrogen at 1 atm, ϕ = 2.0, and 0.07 s residence time.

Figure 5.

Figure 5

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Comparison of the experimental and simulated results using different mechanisms for important species concentrations containing (a) n-C9H20, (b) C2H4, (c) CH2O, (d) CH4, (e) CO, (f) CO2, (g) H2, and (h) H2O in a JSR for 0.1% n-nonane diluted in nitrogen at 10 atm, ϕ = 0.5, and 0.7 s residence time.

Figure 7.

Figure 7

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Comparison of the experimental and simulated results using different mechanisms for important species concentrations containing (a) n-C9H20, (b) C2H4, (c) CH2O, (d) CH4, (e) CO, (f) CO2, (g) H2, and (h) H2O in a JSR for 0.1% n-nonane diluted in nitrogen at 10 atm, ϕ = 1.0, and 0.7 s residence time.

Formaldehyde is an important intermediate for the oxidation of n-nonane from low temperatures to high temperatures.10 As presented in Figure 4c, the formaldehyde concentration increases above 900 K and reaches the peak value at 1050 K. The predictions of the profile of formaldehyde concentration using the new mechanisms are in satisfactory agreement with the measurement. At the same time, under high-pressure conditions, as shown in Figures 5c, 7c, and 9c, the prediction of formaldehyde by the new models, especially Model v2, can also be in good agreement with the experimental data.

Although the new mechanisms and the LLNL model can well reproduce the NTC behavior of fuel combustion, there are still some discrepancies with the experimental data. For example, the new mechanisms, especially Model v2 can well predict the speciation of all the important species, except for C2H4 and CH4 at the pressure of 10 atm, as shown in Figure 5b,d. One of the possible reasons is that the reaction network is not fully described in these mechanisms. In order to develop a comprehensive detailed mechanism suitable for a wide temperature range, a wide pressure range, and different equivalence ratio conditions, further research work needs to be undertaken. Furthermore, our research group is trying to optimize it by combining high-precision quantum chemical calculations and species concentration analysis.

3.1.3. Laminar Flame Speeds

Laminar flame speed, as an important parameter for fuel mixture reactivity, diffusivity, and heat release, is a key factor for verifying the accuracy of the combustion model. Ji et al.11 experimentally determined the premixed flame propagation speeds of C5–C12 alkanes at atmospheric pressure. This section focuses on the verification of the flame propagation speed of n-nonane with different combustion models. Simulations were performed with the Premixed Laminar Flame-Speed Calculation code of Chemkin package.29Figure 10 shows the comparison between the simulation results and the experimental data on the laminar flame propagation speeds at the unburned mixture temperature of 403 K and pressure of 1.01 × 105 Pa. It can be clearly seen that these models have different prediction values for n-nonane. Among them, the LLNL model is in good agreement with the experimental values under rich combustion conditions. Under other conditions, it has a large error with the experimental data, especially when the equivalent ratio is 0.9–1.3. The detailed mechanisms developed in this paper are in overall agreement with the available experimental data except at the equivalent ratio from 1.0 to 1.2, at which the simulation results are slightly higher than the experimental value. The JetSurf 2.0 model, based on the core mechanism USC Mech II,32 is better than the other combustion models in predicting the laminar flame speed; it has been shown that the combustion mechanisms of large hydrocarbons, such as n-heptane,18,20 isooctane,18n-decane,18n-undecane,18n-dodecane,18 methylcyclohexane,33 and n-propylcyclohexane,34 developed with USC Mech II as the core mechanism, show good performance for the prediction of laminar flame propagation speed.

Figure 10.

Figure 10

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Comparison of experimental and simulated data for the n-nonane/air laminar flame speed at an unburned mixture temperature of 403 K and atmospheric pressure.

3.2. Sensitivity Analysis

Sensitivity analysis plays an important role in understanding the key reactions and mechanism simplification in the fuel combustion process. Considering that there is no low-temperature combustion reaction type in the JetSurf 2.0 model, the new mechanisms and the LLNL model were selected for sensitivity analysis. The specific conditions of the sensitivity analysis are the equivalent ratio of 1.0, the initial temperature of 700 K, and the pressure of 15 atm, and the result is shown in Figure 11. There are relatively significant differences between our mechanisms and the LLNL model in the types of key reactions that are sensitive to ignition. Among them, the reaction with the maximum promoting effect on the ignition of n-nonane, in the new mechanisms, is the reaction class ROOH = RO + OH, such as s46C9H20O2 ⇒ OH + s170C9H19O in Model v1 and s52C9H20O2 ⇒ OH + s187C9H19O in Model v2, and in the LLNL model is the isomerization reaction ROO = QOOH, such as c9h20o2-2 = c9ooh2-4. For the reaction with the greatest inhibition of ignition, all these mechanisms are of the reaction class ROO = QOOH, such as s12C9H20O2 ⇒ s49C9H20O2 in Model v1, s11C9H20O2 ⇒ s43C9H20O2 in Model v2, and c9h20o2-4 = c9ooh4-2 in the LLNL model. It can also be seen that at temperatures below 700 K, reactions that are sensitive to ignition are the reactions in the expansion mechanism. In addition, the reaction class RH + ROO = R + ROOH also has a promoting effect on ignition, such as the reactions s0C9H20 + s12C9H19O2 ⇒ s2C9H19 + s46C9H20O2, s0C9H20 + s12C9H19O2 ⇒ s4C9H19 + s46C9H20O2 and s0C9H20 + s12C9H19O2 ⇒ s3C9H19 + s46C9H20O2 in Model v1, as shown in Figure 11a, and the reactions s0C9H20 + s13C9H19O2 ⇒ s2C9H19 + s52C9H20O2, s0C9H20 + s13C9H19O2 ⇒ s4C9H19 + s52C9H20O2 s0C9H20 + s13C9H19O2 ⇒ s3C9H19 + s52C9H20O2, s0C9H20 + s12C9H19O2 ⇒ s2C9H19 + s45C9H20O2 and s0C9H20 + s12C9H19O2 ⇒ s4C9H19 + s45C9H20O2 in Model v2, as shown in Figure 11c, which is consistent with the low-temperature ignition characteristics of the n-heptane combustion mechanism.26 In the LLNL model, as shown in Figure 11b, it can be seen that both the reaction classes RH + OH = R + H2O, such as nc9h20 + oh = c9h19-4 + h2o, and RH + H = R + OH, such as nc9h20 + h = c9h19-5 + oh show strong positive sensitivity. In addition, in the LLNL model, it was found that the decomposition reaction of ketones such as c9ket2-4 = oh + ch3coch2 + nc5h11cho, c9ket3-5 = oh + c2h5coch2 + nc4h9cho, c9ket4-2 = oh + ch3cho + c5h11coch2, c9ket1-3 = oh + ch2cho + nc6h11cho, c9ket4-6 = oh + nc3h7coch2 + nc3h7cho, and c9ket5-3 = oh + c2h5cho + nc4h9coch2 all have an effect on ignition. Therefore, it can be concluded that the key reactions affecting the low-temperature ignition of the new mechanisms and the LLNL model are quite different. This indicates that these combustion models have different effects on the ignition delay due to the difference in the reaction network, which is like the previous comparative study of different n-heptane combustion models.19

Figure 11.

Figure 11

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Sensitivity analysis of ignition delay time with respect to the reaction rate during the low-temperature combustion of n-nonane with Model v1, Model v2, and the LLNL model.

3.3. Reaction Path Analysis

Based on the time-integrated element flux analysis,35 the reaction path of n-nonane under constant pressure ignition simulation was carried out with the C element as a flow target. The element flux results for the n-nonane/O2/N2 mixtures were obtained under the conditions of a pressure of 15 atm, an equivalent ratio of 1.0, and a temperature of 700 K (amounts less than 5% were ignored). The reaction path analysis of the LLNL model is displayed in Figure 12. In Figure 13, the conversion fraction of complex decomposition pathways for Model v1 and Model v2 prescribed for n-nonane are shown in red font and black font, respectively.

Figure 12.

Figure 12

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Time-integrated element flux analysis result of the LLNL model for n-nonane ignition at 700 K and 15 atm with ϕ = 1.0. The data are conversion percentages of carbon.

Figure 13.

Figure 13

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Time-integrated elemental flux analysis result of Model v1 and Model v2 for n-nonane ignition at 700 K and 15 atm with ϕ = 1.0. The data are conversion percentages of carbon. (Both the species name with the red font in Model v1 and the adjacent species name with the black font in Model v2 represent the same species.)

As shown in Figures 12 and 13, the main fuel consumption paths are hydrocarbon fuels (RH) producing the alkyl radicals R• by H-abstraction. Then, the reaction R• + O2 → ROO• took place to yield peroxy radicals ROO•, which will first isomerize to produce hydroperoxyalkyl radicals QOOH. The QOOH radicals will further yield some O2QOOH radicals by the reaction QOOH + O2 → O2QOOH. It can be found that the main reaction path is almost the same, but the conversion fraction of complex decomposition pathways is quite different. Take n-nonyl radicals as an example. In the LLNL model, approximately 60% of n-nonyl radicals underwent the R• + O2 chemistry, and there is only 12.57% in Model v2 and only 41.17% in the Model v1. The existence of the NTC zone is mainly due to the enhanced reversibility of the reaction R• + O2 = ROO as the temperature increases.36 In summary, the discrepancy in the reaction flux will affect the ignition of these mechanisms.

4. Conclusion

An accurate and detailed chemical kinetic model is an important prerequisite for understanding the combustion performance of hydrocarbon fuels. Although large mechanisms can be produced manually, automatic generation provides a systematic tool that helps to simplify and systematize mechanism production. The use of a mechanism automatic program to develop a complex large hydrocarbon combustion mechanism can effectively reduce the mechanism construction time and errors. Accordingly, in this study, combined with the core mechanisms—AramcoMech1.3 and AramcoMech3.0—and the expansion mechanisms produced by the automatic generation program ReaxGen, new mechanisms for low-temperature combustion of n-nonane are developed. In order to verify the rationality of the mechanisms, they are analyzed and compared with international mainstream combustion mechanisms. Systematic comparisons show that the low-temperature combustion mechanism of n-nonane developed by the mechanism automatic program possesses a high simulation precision in both the shock tube experiment and the species concentration generation experiment, and can be used in a wide range of conditions. Finally, through the ignition sensitivity analysis, the key reactions affecting the ignition are investigated. It is found that the reactions which have obvious effects on fuel ignition are quite different in different combustion models; and through the reaction path analysis, it can be seen that the conversion fraction of complex decomposition pathways is also distinct. Therefore, it can be inferred that different combustion models have different effects on combustion characteristics because of different reaction networks. In addition, because of some discrepancies between the predicted values and the experimental data, our research group is trying to optimize the model by combining high-precision quantum chemical calculations and species concentration analysis. A systematic method to automatically generate a mechanism for the low-temperature combustion of n-nonane could also be used to generate the mechanisms of other large hydrocarbons. Moreover, the new mechanisms of n-nonane provide a theoretical basis for revealing the nature of fuel combustion and basic data for the development of advanced engines.

Acknowledgments

We are thankful to the Combustion Dynamics Center of Sichuan University for providing us with the ReaxGen Program.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.9b03786.

  • Mechanisms of Model v1 and Model v2 (TXT)

  • Rate constant expressions for main reaction classes of the expansion mechanism (PDF)

Author Contributions

All authors contributed equally to this work.

This work was supported by the National Natural Science Foundation of China (21963006), the Civil-Military Integration in Guizhou Institute of Technology (KJZX17-016), and the High-level Talent Research Start-up Project in Guizhou Institute of Technology (XJGC20190903)

The authors declare no competing financial interest.

Supplementary Material

ao9b03786_si_001.txt (3.1MB, txt)
ao9b03786_si_002.pdf (132.1KB, pdf)

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