Experimental Evaluation of Various Gasoline Surrogates Based on

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An experimental evaluation of various gasoline surrogates based on soot formation characteristics Yang Hua, Fushui Liu, Han Wu, Chia-fon F. Lee, and Ziman Wang Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b02931 • Publication Date (Web): 09 Oct 2018 Downloaded from http://pubs.acs.org on October 14, 2018

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Title Page Title: An experimental evaluation of various gasoline surrogates based on soot formation characteristics

Authors: Yang Huaa, Fushui Liua,b, Han Wua,*, Chia-fon Leea,c, Ziman Wanga

Author affiliations: a. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China b. Beijing electric vehicle Collaborative Innovation Center, Beijing 100081, China c. Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, IL 61801, USA *Corresponding

authors:

Han Wu, Email: [email protected]; Tel: +86-18500028278 School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China ORCID Han Wu: 0000-0002-9113-9774

1

ACS Paragon Plus Environment

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An experimental evaluation of various gasoline surrogates based on soot formation characteristics Yang Huaa, Fushui Liua,b, Han Wua,* , Chia-fon Leea,c, Ziman Wanga a. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China b. Beijing electric vehicle Collaborative Innovation Center, Beijing 100081, China

c. Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, IL 61801, USA (*Corresponding authors: [email protected])

Abstract: The evaluation of soot tendency of gasoline surrogates in simple atmosphere environments is essential for understanding soot formation processes and developing accurate soot models to represent real fuel chemistry in CFD simulations of gasoline engines. In this work, several surrogates were evaluated based on soot precursors and soot characteristics in laminar diffusion flames. The relative concentrations of PAHs with different ring size and soot were measured using LIF and LII techniques. The OH and CH luminescence intensities were also recorded using ICCD. The results showed that the gasoline surrogates failed to represent the formation characteristics of small ring aromatics (320/360 nm) for gasoline flames, but have certain characterization ability for large ring aromatics (400/450 nm). The relationship between PAHs-LIF signal and toluene content is not monotonically increasing. Based on the relative concentrations of larger PAHs and soot, the surrogate (1/3 n-heptane 1/3 isooctane 1/3 toluene) can characterize the formation characteristics of soot precursors and soot in gasoline laminar diffusion flames best. Based on the OH and CH luminescence intensities, the surrogate (1/3 n-heptane 1/3 isooctane 1/3 toluene) can best characterize the flame structure and development of gasoline. The CH trend is consistent with the PAH trend, inferring there exists a strong correlation between CH intensity and PAHs in the diffusion flames. As 2


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the aromatic ring number increases, its PAHs-LIF signal peaks at a higher position, and the high concentration region gradually evolves from the flame center to the two wings of the flame, which eventually leads to the characteristic of the two wings distribution of soot. For the binary mixture of n-heptane-toluene, the 320 nm PAHs-LIF signal increases monotonically with the toluene ratio. The maximum PAHs-LIF signals of 360-450 nm exhibit non-monotonic tendency, which reach to the peak at a 50% toluene ratio. Furthermore, there exists a tolerance in terms of toluene mixing ratio (10%), below which the effect of toluene on larger ring aromatics (A4-5) formation can be neglected. Key words: gasoline surrogates; polycyclic aromatic hydrocarbon; laser-induced fluorescence; laser-induced incandescence; laminar diffusion flame 1. Introduction Evaluating the soot tendencies of real commercial fuel in a simple environment, such as a laminar flame, is critical to understanding the soot formation process and developing an accurate soot model. This understanding is needed to improve the soot model used to predict soot formation in engineering CFD calculations for designing internal combustion engines [1]. With the increasingly stringent emission regulations and the large-scale application of GDI technology, gasoline engines are facing the problem of soot emission [2, 3]. Even the air-fuel mixing process is able to influence the soot forming though fuel distribution [4-8], fuel composition itself is a key factor in determining soot characteristics [9]. Currently, accurate prediction of the soot characteristics of gasoline during combustion has drawn more attention [10-12]. Gasoline fuel is a complex mixture of hydrocarbons mainly including n/i-paraffins, naphthenes, olefins, and aromatics. Currently, it is impossible to get a chemical kinetic model that contains all the components in gasoline, especially while blended with alternative fuels, for the combustion and emission 3


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numerical simulation [13-19]. Thus, CFD modeling of fuel chemistry for gasoline engine simulations is typically uses a simple surrogate fuels to represent the fuel chemistry of real gasoline. The surrogate fuels requires a mixture of minor components to characterize the key physicochemical properties of gasoline [20]. Initially, considering the physical properties of isooctane approaching that of gasoline, isooctane was widely used as the simplest gasoline surrogate [21]. Subsequently, a mixture of iso-octane and n-heptane, named as the primary reference fuel (PRF), was used to characterize the octane number of gasoline [22-25]. Later, toluene as a representative of aromatics in gasoline fuels became one of the most important components in gasoline surrogates [26]. Now, n-heptane, isooctane and toluene have been widely accepted as the reference component for gasoline surrogate fuel, named as toluene reference fuel (TRF). In addition, some studies also developed different components and proportions of gasoline surrogate fuels, including up to seven components [27]. However, the current research on gasoline surrogate fuels is also based primarily on TRF. For the proportions of components in the TRF, Gauthier et al. [28], Machrafi et al. [29], Sileghem et al. [30], Pera and Knop et al. [31, 32] respectively proposed different proportion in TRF based on the ignition delay time, the combustion performance, the laminar burning velocity, or the auto-ignition performance. However, it is also critical to obtain similar emission characteristics. In particular, soot emissions prediction is difficult due to the complexity associated with fuel composition, fuel chemistry, and solid particle dynamics [33]. For the fuel composition and chemistry, aromatics in gasoline may have a significant contribution to soot formation, which are rarely considered even in detailed gasoline engine soot modeling. Toluene, as a representative of aromatic compounds in gasoline surrogates, is crucial for predicting the formation of soot. Therefore, some studies on toluene addition have been carried out. Alexiou et al. [34] studied the soot formation of toluene blended with n-heptane or isooctane in shock tube pyrolysis, and 4


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found that the soot formation decreases with the increasing n-heptane or isooctane ratio. Choi et al. [35] studied the soot and PAHs formation in counterflow diffusion flames of gasoline surrogate fuels. They found that as the toluene content increases, the soot formation increases monotonically, while PAHs shows a synergistic effect. Consalvi et al. [36] studied the effect of n-heptane/toluene or isooctane/toluene binary mixtures addition on the formation of PAHs and soot in methane laminar diffusion flames. They found that as the toluene content increases, soot formation increases monotonically, while the formation of benzene and pyrene shows a non-monotonic trend. Park et al. [37] studied the formation of PAHs and soot of gasoline surrogate fuels. They pointed out that the composition of gasoline surrogates has a strong effect on the formation of PAHs and soot. The above studies have shown that the composition of TRF, especially toluene, has a strong influence on the formation of PAHs and soot. However, for the existing various proportion of TRF [28-32], it is unknown that which proportion is more suitable predicting soot formation for gasoline. It is known that a detail soot model consists of gas phase soot precursors (PAHs) chemical kinetics and particle kinetics, since the nucleation reaction of soot closely relates to the larger polycyclic aromatic hydrocarbons (PAHs) [38-41]. The matching processes for detailed soot models are often achieved by optimizing the gas phase TRF-PAHs chemical mechanism and particle kinetics parameters. In fact, the proper proportion of components in the TRF is also important for accurate prediction of PAHs and soot formation. Currently, there is a lack of evaluation of soot precursors and soot formation characteristics for existing TRF components. In this study, the stable laminar coflow diffusion flames were obtained based on a Gülder liquid burner system. The relative concentrations of PAHs with different rings and soot were measured by using LIF and LII techniques, and the OH and CH luminescence intensities were also recorded by ICCD. The difference 5


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between various existing TRF and gasoline was evaluated based on soot precursors characteristics in laminar diffusion flames, and the effect of toluene ratio on surrogates was especially investigated. This study attempts to provide preliminary evidence of whether the current gasoline surrogates can replicate real soot formation behavior of real gasoline. The results obtained in the laminar diffusion flame have guiding significance to the engine CFD simulation regarding the component composition of surrogates required to capture soot tendency of real gasoline. 2. Experimental setup and method 2.1 Test system The liquid burner system includes the Gülder burner [42], accumulator, mass flow controllers (MFC), controlled evaporator mixer (CEM), heating bands, nitrogen cylinders, pressure stabilizing cavity, air compressor, and gas flowmeter (see Fig. 1). To prevent the flame from smoking, the fuel stream is first diluted with nitrogen, then evaporated in the CEM device (423 K). The fuel mass flow (7±0.05 g/h) is controlled by a Coriolis high-precision mass flow meter (CORI-FLOW Bronkhorst). The nitrogen volumetric flow rate (0.3 L/min, at 273 K, 1atm) is regulated by a thermal flow meter (EL-FLOW Bronkhorst). The airflow rate was set at about 200 L/min (at 273 K, 1atm), and the temperatures of the heating band were set at 423 K. The stable coflow diffusion flames with a height fluctuation of about 1 mm can be acquired. Laser-induced fluorescence (LIF) and laser-induced incandescence (LII) techniques are used to measure the relative concentrations of PAHs and soot. In the PAH-LIF test (see Fig. 1), the fourth harmonic of the pulsed Nd:YAG laser (266 nm, 10 Hz) and 80 mJ/pulse energy were used to form a sheet laser with a thickness of 0.8 mm through a light sheet system. Then the ICCD camera with a gate width of 30 ns captured the 2D LIF signals. Four band pass filters of 320, 360, 400, and 450 nm (FWHM 10 nm) were 6


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used to differentiate relative size of PAHs [43]. Previous studies have shown that as the detection wavelength becomes longer, the LIF signal represents larger ring aromatics [44, 45]. In the Soot-LII test, the second harmonic, instead of the fourth one, of the Nd:YAG laser (532 nm)and 250 mJ/pulse energy were used. Band filter with central wavelengths of 675nm (FWHM 30nm) are selected. 2D LII Images were captured by the ICCD with a delay of 30 ns, a gate width of 20 ns and a gain of 70. Furthermore, in order to observe the flame structural characteristics, the OH and CH luminescence intensities were recorded by the ICCD with a gate width of 990 µs using the band pass filters of 310 nm (FWHM 10nm) and 430 nm (FWHM 10nm) respectively. At least 90 images are recorded for each signal of each fuel in all tests. 2.2 Test Fuel The present study investigated pure gasoline (RON: 92, from a petrochemical gas station in Beijing, China), five gasoline surrogate fuels, and binary mixture of n-heptane-toluene. The real gasoline consists of 49.2% saturates, 14.7% olefins, and 36.1% aromatics. The components and octane number (average of RON and MON) of five existing gasoline surrogate fuels are listed in Table 1. The No. 1 surrogate [25] is primary reference fuel (PRF), and the No. 2-5 surrogates [28-31] are toluene reference fuel (TRF). The proportion of toluene increases gradually in No. 2-5 surrogates. Previous studies have evaluated their consistency with gasoline in terms of either ignition delay time or laminar burning velocity. The proportion of toluene in the binary mixture of n-heptane-toluene increases from 0% to 100%. The physicochemical properties of components in gasoline surrogate fuel are shown in Table 2. 3. Results and discussion 3.1 Soot precursor characteristics of based gasoline fuel Fig. 2 displays the distributions of PAHs-LIF signals detected at 320, 360, 400, and 450 nm and LII 7


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signal in gasoline flame. Since the PAHs-LIF measured at the laser incident side is more accurate, the PAHs distribution images are mirrored. The fluorescence around 320 and 360 nm appears at the nozzle exit, and their intensities are very high. As the height above burner increases, the fluorescence around the wavelengths of 400 and 450 nm gradually appears, and their signal intensity is weaker than that of small aromatics rings. Compared to the fluorescence signals, LII signals appear in a higher position. It is generally considered that 320 nm represents an aromatic ring (A1), 360 represents 2-3 aromatic rings (A2-A3), 400 represents 3-4 aromatic rings (A3-A4), and 450 represents 4-5 aromatic rings (A4-A5) [45, 46]. Therefore, the figure shows the evolution process of mono aromatics (A1) growing into larger polycyclic aromatics (A4-A5) and eventually forming soot along the fuel stream direction. From the peak position, the high concentration of small ring PAH is located near the flame centerline, and that of large ring PAH located in the two wings of the flame. As the aromatic ring increases, the high-concentration region of PAH gradually evolves from the flame center to the two wings of the flame, which eventually leads to the characteristic of the two wings distribution of soot. The distribution results show the close relationship between PAHs and soot formation. The research of Choi et al. [47] in ethylene counterflow diffusion flame also reported the correlation between PAHs and soot. Fig. 3 shows the profiles of normalized PAHs-LIF and LII signals along the axial centerline of the gasoline flame. It is seen that as the aromatic ring number increases, its PAHs-LIF signal peaks at a higher position. A1-A2 aromatics (LIF-320 and 360 nm) quickly form near the nozzle exit (HAB < 1 mm) and quickly reach to peak value at HAB< 10mm. The concentration of A4-A5 aromatics (LIF-450 nm) reaches its peak value near HAB=15 mm and decreases rapidly near HAB=25 mm. The location of the LII peak is the rapidly declining position of PAHs-LIF of A4-A5. Specifically, the rapid decline of the LIF of A4-A5 ends at HAB=40 mm, while the rapid decline of LII ends at HAB=50 mm. It can be inferred that a large 8


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amount of A4-A5 formed into soot before the rapid oxidation of soot [48]. 3.2 Comparison of various gasoline surrogate fuels Fig. 4 shows the comparison of normalized maximum PAHs-LIF signals between gasoline and various gasoline surrogate fuels (see Tab. 1). The data is normalized with the maximum values in gasoline flame. It is found that four kinds of PAHs-LIF signals in PRF flame (surrogate 1) are the weakest, and that in No. 4 surrogate flame are the strongest. Note that the toluene content in surrogate5 fuel is higher than that of surrogate4 fuel, but its PAH-LIF signal strength is weaker than that of surrogate4 fuel. Therefore, the relationship between the PAHs concentration and the toluene content in the TRF is not monotonously increased. Compared to gasoline, all surrogate fuels have lower PAHs-LIF signals, and the differences in small ring aromatics are particularly large. The five surrogate fuels failed to characterize the formation of small ring aromatics (320 or 360 nm) in gasoline flames. This may be due to the difference in the fluorescence spectrum of the monocyclic aromatic hydrocarbons. The aromatics in the surrogate fuels have only one toluene, and the major monocyclic product is benzene produced by C6H5CH3+H=A1+CH3 [49-51], but there are various kinds of alkyl benzene in the gasoline. As the number of aromatic rings increases, the difference between the fluorescent signals characterizing the fuel and the gasoline significantly decreases. This indicates that the gasoline surrogate fuels have certain characterization ability for large ring aromatics (400 or 450 nm). In fact, larger PAHs plays the dominant role in the formation of soot., thus the PAHs-LIF signals of larger aromatic rings are more suitable as an indicators for evaluating the PAH formation characteristics. For the 450 nm PAHs-LIF signal, surrogate4 is closest to gasoline. Fig. 5(a) displays a comparison of the PAHs-LIF signal distribution detected at 450nm for gasoline and various gasoline surrogates. It is observed that the PAH-LIF distribution in PRF (surrogate1) flame is different from gasoline and TRF (surrogate2-5). The signals in the PRF flame mainly distribute at the top of 9


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the flame, while the signals of the other fuels distribute in the two wings of the flame. Fig. 5(b) shows the normalized PAHs-LIF signal profiles along the centerline of the six flames. As a whole, the signals on the centerline show a tendency of first increasing and then decreasing. However, the specific trends are different, the upward trend in gasoline and TRF flames was faster, while the upward trend in PRF is very slower. Specially, the peak in gasoline flame centerline appears at the HAB30mm. This indicates that the presence of aromatic hydrocarbons promotes the formation of macrocyclic aromatic hydrocarbons. The PAHs-LIF signal trend on the centerline of surrogate 4 is similar to that of gasoline, except the peak is slightly below gasoline. Fig. 6(a) displays the comparison of LII signal distribution between gasoline and gasoline surrogates (No. 2-4). The peak value of LII signal in each flame are marked at the bottom of the figure. It should be noted that the LII signal of surrogate1 is weak, and the flame of the surrogate5 fuel smoke seriously, so no comparison is made. This figure shows the main area of soot formation [52, 53]. The high concentrations of soot are mainly distributed in the two wings of the flame, which is consistent with the distribution of PAHs-LIF signal detected at 450 nm (see Fig. 5). There is no soot formation in the inner cone area, where completely contains the PAHs-LIF region of 320-400 nm (see Fig. 2). Fig. 6(b) shows the normalized LII signal profiles along the centerline of the four flames. The trends of soot in three TRF flames (surrogate 2-4) are basically consistent with that in gasoline flame. As the height increases, the axial Soot-LII signal shows a three-stage trend: the soot is initially zero, then gradually increases to the peak, and finally decreases to zero, which corresponds exactly to the three regions of soot-precursors formation, soot formation and soot oxidation [54]. From the LII signal, the soot formation characteristic of No. 4 surrogate fuel is the closest to gasoline. Therefore, based on the analysis of Fig. 4 to Fig. 6, the surrogate4 can best represent the soot 10


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precursors and soot formation characteristics of real gasoline in laminar diffusion flames. Previous research have shown that the strongest chemiluminescent intensity peaks in hydrocarbon flames are produced by the excited hydroxyl radical (OH) and methylidyne radical (CH) [55]. And the OH and CH luminescence are usually used as the indicator of flame front location qualitatively. In order to understand the differences in the combustion state and flame structure distribution between gasoline and gasoline surrogates, the luminescence intensities of OH and CH are compared. Fig. 7(a) shows the comparison of OH luminescence intensity distribution between gasoline and various gasoline surrogates. The surrogates3-5 are similar to surrogate 2, so they are not listed. It can be seen that the OH distribution trends of gasoline and various surrogate fuels are similar. OH mainly distributes at the periphery of the flame, indicating where the main reaction zone is. This because the availability of oxygen atoms tends to move OH toward the air side [55]. In addition, for the whole flame, OH peaks at a lower height near the exit of the nozzle because of the relatively high flow velocity driving the mutual diffusion of fuel and oxygen at the flame bottom [56]. Furthermore, the OH peak locates in the blue region of the flame bottom (as shown by the red circle). The height at which the OH radicals begin to appear is also the height at which the visual flames appear. Marchese et al. [57] also pointed out that OH distribution can yield a rational indication of flame front position because of the peak OH is near the maximum flame temperature region. Fig. 7(b) displays the radial profiles of the six flames at the maximum OH position. The OH peak gradually increases slightly as the proportion of toluene in the surrogate fuel increases, which is different from the trend of PAHs shown in Fig. 4. This indicates that there is no strong correlation between OH intensity and PAHs in the diffusion flames. It is noted that the difference of OH peak intensity between the surrogate4 fuel and gasoline is the smallest, and the OH peak intensity of surrogate5 fuel (43.4% toluene) is much higher than that of gasoline. 11


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Fig. 8(a) displays the comparison of CH luminescence intensity distribution between gasoline and various gasoline surrogates. Note that the surrogates 3-5 are similar to surrogate 2, so they are not listed. It is found that the distribution of CH in the PRF (surrogate1) flame differs significantly from that of gasoline, and the distribution of CH in the TRF flame is similar to that of gasoline. In PRF flame, CH radical mainly distributes in the top of the flame. In gasoline and TRF flames, CH mainly distributes in the inner region of the middle flame, corresponding to the soot formation region (see Fig. 6). Compared with gasoline and TRF, CH peaks at a higher position in surrogate1 (PRF) flame. Since that the CH radical is the final product of the pyrolysis [58], the surrogate1 completes the pyrolysis for much longer than the gasoline and surrogate 2-5 (TRF). Fig. 8(b) shows the comparison of normalized maximum CH intensity in the six flames. It can be observed that the CH luminescence intensity in the surrogate4 fuel flame is the closest to gasoline. The relationship between CH intensity and toluene content is not monotonically increasing. In the flames of surrogate 1-4, CH intensity increases with the increasing toluene content in gasoline surrogate fuels. However, the toluene content in surrogate5 fuel is higher than that of surrogate4, but its CH intensity is lower. This trend is consistent with the PAH trend shown in Fig. 4. Thus, there is a strong correlation between CH intensity and PAHs in the diffusion flames. This can be explained from the heating value of the fuels. Giassi et al. [59] pointed out that the trend of peak heat release rate is consistent with the trend of CH, so the peak CH concentration can be a sign for the peak heat release rate. From this point of view, the heat release rate and temperature of the surrogate 4 flame are closest to the gasoline. Therefore, based on the analysis of Fig. 7 and Fig. 8, the surrogate4 can best represent the flame structure and development of real gasoline in laminar diffusion flame. 3.3 Effect of toluene ratio in binary mixture 12


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In order to further clarify the effect of toluene ratio on the PAH formation characterization of surrogate fuels in laminar diffusion flames, Fig. 9 shows the normalized maximum PAHs-LIF signals detected at 320, 360, 400, and 450 nm as a function of toluene ratio in binary mixture of n-heptane-toluene. The data are normalized with the maximum values at 100% toluene ratio. The PAHs-LIF signal at 320 nm increases monotonically with the toluene ratio. However, with the increase of toluene ratio, the increasing trend weakens and converges to the ratio of 50% toluene. The trend of 320nm-LIF is attributed to the increase in toluene content because it is also a monocyclic aromatic hydrocarbon. The maximum PAHs-LIF signal at 360-450 nm exhibits a non-monotonic trend. As the toluene ratio increases from 0 to 50%, the maximum PAHs-LIF signals of 360-450 nm increases, and then the PAH signals gradually decrease as the toluene ratio continue to increase. The PAHs-LIF signal at 360-450 nm peaks at a toluene ratio of 50%. The tendencies of 360-450 nm is may due to the decrease of PAH growth components, such as H, C2H2, C2H4, and C4H4, which are mainly produced by the cracking of long chain hydrocarbons (n-heptane or isooctane in TRF) [60]. Thus, the increase of toluene ratio reduces the content of n-heptane or isooctane, leading to this trend [35]. In addition, it is noted that the addition of 10% toluene has little effect on the 450 nm PAHs-LIF signal, which indicates there exists a tolerance in terms of toluene blending ratio, below which the effect of toluene on larger ring aromatics (A4-5) formation can be neglected. Therefore, in determining the components proportion of TRF fuel for predicting the formation characteristics of gaseous soot precursors of gasoline, the appropriate proportion of toluene is between 10% and 50%. For ternary mixture, the above analysis also shows that TRF (1/3 n-heptane, 1/3 isooctane, 1/3 toluene) performs best on soot precursors and soot predictions with respect to the existing proportion of TRF. 4. Conclusions In the current work, the relative concentrations of PAHs with different rings and soot were measured 13


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using LIF and LII techniques, and the OH and CH luminescence intensities were also recorded by ICCD. The difference between various gasoline surrogates and real gasoline was evaluated based on soot precursors and soot characteristics in laminar coflow diffusion flames. For real gasoline fuel, as the aromatic ring number increasing, the PAHs-LIF signal peaks move to a higher position, and the high concentration region gradually evolves from the flame center to the two wings of the flame, which eventually leads to the characteristic of the two wings distribution of soot. The gasoline surrogate fuels (PRF and TRF) failed to represent the formation tendency of small ring aromatics (320 or 360 nm) for gasoline flames, but have certain characterization ability for large ring aromatics (400 or 450 nm). The relationship between PAHs-LIF signal and toluene content is not monotonically increasing. Based on the relative concentrations of PAHs and soot, the surrogate (1/3 n-heptane 1/3 isooctane 1/3 toluene) can best represent the soot precursors and soot formation characteristics of real gasoline in laminar diffusion flames. Based on the OH and CH luminescence intensities, the surrogate (1/3 n-heptane 1/3 isooctane 1/3 toluene) can best represent the flame structure and development of real gasoline. The CH trend is consistent with the tendencies of PAHs, indicating there is a strong correlation between CH intensity and PAHs in the diffusion flames. For the binary mixture of n-heptane-toluene, the 320 nm PAHs-LIF signal increase with the toluene ratio monotonically, while the maximum PAHs-LIF signals of 360-450 nm exhibit non-monotonic tendency. The signals reach to the peak at a 50% toluene. Furthermore, there exists a tolerance in terms of toluene mixing ratio (10%), below which the effect of toluene addition on larger ring aromatics (A4-5) formation can be neglected. Acknowledgements This study is based upon work supported by National Key Research and Development Program of 14


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Ma X, Huang Biao, Li Y, et al. Numerical simulation of single bubble dynamics under acoustic travelling waves. Ultrason. Sonochem. 2018, 42, 619-630.

8.

Wu Q, Huang B, Wang G, Gao S. The transient characteristics of cloud cavitating flow over a flexible hydrofoil. Int J Multiphas Flow 2018, 99, 162-173. 15


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Jia G, Wang H, Tong L, Wang X, Zheng Z, Yao M. Experimental and numerical studies on three gasoline surrogates applied in gasoline compression ignition (GCI) mode. Appl. Energy 2017, 192, 59-70.

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gasoline, its surrogates and components in laminar non-premixed flows. P. Combust. Inst. 2009, 32(1), 493-500. 27. Puduppakkam K V, Liang L, Naik C V, et al. Combustion and emissions modeling of a gasoline HCCI engine using model fuels. SAE Technical Paper, 2009-01-0669. 28. Gauthier B M, Davidson D F, Hanson R K. Shock tube determination of ignition delay times in full-blend and surrogate fuel mixtures. Combust. Flame 2004, 139(4), 300-311. 29. Machrafi H, Cavadias S. Three-stage autoignition of gasoline in an HCCI engine: An experimental and chemical kinetic modeling investigation. Combust. Flame 2008, 155(4), 557-570. 30. Sileghem L, Alekseev V A, Vancoillie J, et al. Laminar burning velocity of gasoline and the gasoline surrogate components iso-octane, n-heptane and toluene. Fuel 2013, 112(3), 355-365. 31. Pera C, Knop V. Methodology to define gasoline surrogates dedicated to auto-ignition in engines. Fuel 2012, 96(7), 59-69. 32. Knop V, Pera C, Duffour F. Validation of a ternary gasoline surrogate in a CAI engine. Combust. Flame 2013, 160(10), 2067-2082. 33. An Y, Jaasim M, Raman V, et al. In-Cylinder Combustion and Soot Evolution in the Transition from Conventional Compression Ignition (CI) Mode to Partially Premixed Combustion (PPC) Mode. Energ. Fuel 2018, 32(2), 2306-2320. 34. Alexiou A, Williams A. Soot formation in shock-tube pyrolysis of toluene-n-heptane and toluene-iso-octane mixtures. Fuel 1995, 74(2), 153-158. 35. Choi B C, Choi S K, Chung S H. Soot formation characteristics of gasoline surrogate fuels in counterflow diffusion flames. P. Combust. Inst. 2011, 33(1), 609-616. 36. Consalvi J L, Liu F, Kashif M, et al. Numerical study of soot formation in laminar coflow methane/air 18


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46. Kobayashi Y, Furuhata T, Amagai K, et al. Soot precursor measurements in benzene and hexane diffusion flames. Combust. Flame 2008, 154(3), 346-355. 47. Choi S K, Choi B C, Lee S M, et al. The effect of liquid fuel doping on PAH and soot formation in counterflow ethylene diffusion flames. Exp. Therm. Fluid Sci. 2015, 60, 123-131. 48. Hayashida K, Mogi T, Amagai K, et al. Growth characteristics of polycyclic aromatic hydrocarbons in dimethyl ether diffusion flame. Fuel 2011, 90(2), 493-498. 49. An Y, Pei Y, Qin J, Zhao H, Li X. Kinetic modeling of polycyclic aromatic hydrocarbons formation process for gasoline surrogate fuels. Energ. Convers. Manage. 2015; 100, 249-61. 50. Liu F, Hua Y, Wu H, et al. Experimental and kinetic investigation on soot formation of n-butanol-gasoline blends in laminar coflow diffusion flames. Fuel 2018, 213, 195-205. 51. Liu F, Hua Y, Wu H, et al. Effect of toluene addition on the PAH formation in laminar coflow diffusion flames of n-heptane and isooctane. Energ. Fuel 2018, 32(6), 7142-7152. 52. Khosousi A, Liu F, Dworkin SB, Eaves NA, Thomson MJ, He X, et al. Experimental and numerical study of soot formation in laminar coflow diffusion flames of gasoline/ethanol blends. Combust. Flame 2015, 162, 3925-3933. 53. Thomson K A, Johnson M R, Snelling D R, et al. Diffuse-light two-dimensional line-of-sight attenuation for soot concentration measurements. Appl. Optics 2008, 47(5), 694-703. 54. Liu F, Hua Y, Wu H, et al. Effect of alcohol addition to gasoline on soot distribution characteristics in laminar diffusion flames. Chem. Eng. Technol. 2018, 41(5), 897-906. 55. De Leo M, Saveliev A, Kennedy L A, et al. OH and CH luminescence in opposed flow methane oxy-flames. Combust. Flame 2007, 149(4), 435-447. 56. Zhang T, Guo Q, Liang Q, et al. Distribution characteristics of OH*, CH*, and C2* luminescence in 20


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CH4/O2 co-flow diffusion flames. Energ. Fuel 2012, 26(9), 5503-5508. 57. Marchese A J, Dryer F L, Nayagam V, et al. Hydroxyl radical chemiluminescence imaging and the structure of microgravity droplet flames. P. Combust. Inst. 1996, 26(1), 1219-1226. 58. Smooke M D, Xu Y, Zurn R M, et al. Computational and experimental study of OH and CH radicals in axisymmetric laminar diffusion flames. P. Combust. Inst. 1992, 24(1), 813-821. 59. Giassi D, Cao S, Bennett B A V, et al. Analysis of CH* concentration and flame heat release rate in laminar coflow diffusion flames under microgravity and normal gravity. Combust. Flame 2016, 167, 198-206 60. Jia G, Yao M, Liu H, et al. PAHs formation simulation in the premixed laminar flames of TRF with alcohol addition using a semi-detailed combustion mechanism. Fuel 2015, 155, 44-54.

21


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure Captions Figure 1: The schematic of liquid burner and PAH-LIF systems Figure 2: Images of PAHs-LIF signals and LII signal in gasoline laminar diffusion flame Figure 3: Profiles of normalized PAHs-LIF and LII signals along the centerline of the gasoline flame Figure 4: Comparison of normalized maximum PAHs-LIF signals between gasoline and gasoline surrogates Figure 5: Comparison of PAHs-LIF signals detected at 450nm between gasoline and gasoline surrogates Figure 6: Comparison of LII signals between gasoline and various gasoline surrogates Figure 7: Comparison of OH chemiluminescence intensity between gasoline and gasoline surrogates Figure 8: Comparison of CH chemiluminescence intensity between gasoline and gasoline surrogates Figure 9: Normalized maximum PAHs-LIF signals as a function of toluene ratio in n-heptane/toluene mixture flames: (a) 320 nm, (b) 360 nm, (c) 400 nm, (d) 450 nm

22


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Page 23 of 29

ICCD

data acquisition (Lavision )

filter

aperture beam dump air compressor

light sheet system

burner

gas flowmeter

mass flow controller fuel

controlled evaporator mixer

accumulator

Nd: YAG Laser 266nm

reflector

heating band pressure stabilizing cavity

Fig. 1. The schematic of liquid burner and PAH-LIF systems

40 3000

1000 10

1000 10

500

500

0

-4-2 0 2 4 r (mm)

0

0

-4-2 0 2 4 r (mm)

0

0

800 3030

30

600 2020

20 1000 10 500

-4-2 0 2 4 r (mm)

0 0


1200

-4 -2 0 2 4 r (mm)

1000 2000 2000 800 1500 1500 600

400

1000 1000 400

1010 200

500 500 200

0 00 -4-4-2 -2 00 22 4 -4-2 (mm) rrr(mm) (mm)

Fig. 2. Images of PAHs-LIF signals and LII signal in gasoline laminar diffusion flame

23

3000 3000

2500 2500

1500

20 1500

5050 1200

Soot Soot

4040 1000

2000

2000

LII signal

LIF signal

450nm

2500 40

2500 30

20 1500

3000 50

Height above burner (mm)

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400nm


3500

2000

20

LIF signal

4000 50

3500

2500 30

30

10

a

LIF signal

360nm


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4000 50


50

320nm

above burner (mm) Height above Height

LIF signal


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

00

Energy & Fuels

Normalized LIF signals

0.8

1.0 0.8

0.6

0.6

0.4

0.4

0.2

0.2

0.0

0

10

20 30 40 Height above burner (mm)

50

Normalized LII signals

LIF-320 nm LIF-360 nm LIF-400 nm LIF-450 nm LII

1.0

0.0

Fig. 3. Profiles of normalized PAHs-LIF and LII signals along the centerline of the gasoline flame

1.0

Normalized max. LIF signals

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 29

0.8 0.6

gasoline surrogate1 surrogate2 surrogate3 surrogate4 surrogate5

0.4 0.2 0.0

320nm

360nm

400nm

450nm

Fig. 4. Comparison of normalized maximum PAHs-LIF signals between gasoline and gasoline surrogates

24


Page 25 of 29

50

50

20

400

400 10

20

800

30

600 600

600 20 20

20

400

10 10

200

20

400

400

0.6

80040 1000

800 800

30

20

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800

60030

0.4 600 600

600

20

0.2 400

400 400

400

1010 0.0 200 0

10 10200 20 30 40 200 Height above burner (mm)

200

200 200

200

50

0. 1

8.0

0

6.0

r (mm) 0 -4-2 0 2 4 r (mm)

4.0

-4-2 0 2 4 r (mm)

0

0

2. 0

0 0 0 0 0 0 0 0 0 -4-2 0 2 4 -4-2 0 2 4 -4-2 0 2 40 -4-2 0 2 4 -4-2 00 2 4 -4-2 024 r (mm) r (mm) r (mm) r (mm) 0 r (mm)

0.0

0

30

30

0

-4 -2 0 2 4 r (mm)

40 1000 800

30

800

1010

10

200

40

Normalized LIF signals

600

600 20


30

burner above Height (mm) (mm) burner above Height

800

1000

30



30

800

40


1000

0.8

01

10



20

0.2 0.4 0.6 0.8 1.0 Normalized LIF LIF signals Normalized signals

0

Fig. 5. Comparison of PAHs-LIF signals detected at 450nm between gasoline and gasoline surrogates

(a) LII signal distribution

(b) LII signal along centerline

3000 50 Surrogate3 3000 50 Surrogate4 3000 50 Gasoline 50 Surrogate2

20

30

20

Peak 2266

500

30

1500

1500

1000

1000

500

500

20

20

10

Peak 2444

1.0

10 Peak 2820

0.6

0.8

1.0 0. 1

0.6 0.2 0.4

8.0

0

6.0

0

4. 0

0

gasoline surrogate2 surrogate3 surrogate4

0.8

2.0

0 0 0 0 0 -4-2 0 2 4 -4-2 0 2 4 -4-2 0 2 4 r (mm) r (mm) r (mm)

0. 0

0

30

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-4-2 0 2 4 r (mm)

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Peak 2911

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30

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01

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2500 40

enilosag 2etagorrus 3etagorrus 4etagorrus

20

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02 03 04 )mm( renrub evoba thgieH

30

40

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Normalized LII signals

2500 40



30

40

1000

enilosag 1etagorrus 2etagorrus 3etagorrus 4etagorrus 5etagorrus

40

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gasoline surrogate1 surrogate2 surrogate3 surrogate4 surrogate5

50

1200

02 03 04 )mm( renrub evoba thgieH

40

1000

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1200 40

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0

(b) along centerline

1200

1400 40 Surrogate5 Gasoline 50 Surrogate150 Surrogate2 4050 Surrogate350 Surrogate4 50 1.0

05

50

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1200

50 (a) overall distribution

05

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Normalized Normalized LII LII signals

0.4

Fig. 6. Comparison of LII signals between gasoline and various gasoline surrogates

0.2 0.0

25


0

10

20 30 40 Height above burner (mm)

Energy & Fuels

Page 26 of 29

26


Normalized max. signals

Normalized radiation Intensity




Normalized radiation Intensity




1 2 3 (a) OH intensity distribution (b) normalized OH inten 4 1.2 5 3000 1.2 3000 50 3000 PRF TRF 50 Gasoline50 Normalized max. signals 6 (surrogate1) (surrogate2) 1.0 7 1.0 0.8 8 gasoli 2500 2500 2500 40 40 40 surrog 0.6 9 surrog 0.8 10 0.4 surrog 2000 2000 2000 11 surrog 0.2 30 30 30 surrog 12 0.0 0.6 13 1500 1500 1500 14 20 20 20 15 0.4 1000 1000 1000 16 17 0.2 10 10 10 18 500 500 500 19 20 0.0 21 0 0 0 0 0 0 -6 -4 -2 0 -4-2 0 2 4 -4-2 0 2 4 -4-2 0 2 4 22 r (mm) r (mm) r (mm) Radius ( 23 24 (a) OH intensity distribution (b) normalized OH intensity profiles 25 1.2 26 50 PRF 3000 1.2 Gasoline 3000 50 3000 TRF gasoline Normalized max. signals (surrogate1) (surrogate2) 27 surrogate1 1.0 1.0 28 surrogate2 0.8 gasoline 2500 2500 2500 surrogate3 29 40 40 surrogate1 0.6 surrogate4 surrogate2 30 0.8 0.4 surrogate3 surrogate5 2000 2000 2000 31 surrogate4 0.2 32 30 30 surrogate5 0.0 0.6 33 1500 1500 1500 34 20 35 20 0.4 1000 1000 1000 36 37 0.2 10 38 10 500 500 500 39 40 0.0 0 0 0 0 0 -6 -4 -2 0 2 4 6 41 -4-2 0 2 4 -4-2 0 2 4 -4-2 0 2 4 r (mm) r42 (mm) r (mm) Radius (mm) 43 44 Fig. 7. Comparison of OH chemiluminescence intensity between gasoline and gasoline surrogates 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 27 of 29

Energy & Fuels




Normalized max. signals Normalized max. signals



1 2 3 4 5 6 (a) CH chemiluminescence intensity distribution 7 Gasoline PRF TRF 3000 3000 3000 50 50 50 8 (surrogate1) (surrogate2) 9 10 2500 2500 2500 11 40 40 40 12 13 2000 2000 2000 14 30 30 30 15 16 1500 1500 1500 17 18 20 20 20 19 1000 1000 1000 20 21 10 10 10 22 500 500 500 23 24 25 0 0 0 0 0 0 -4-2 0 2 4 -4-2 0 2 4 -4-2 0 2 4 26 normalized max. CH intensity r (mm) r (mm) r(b) (mm) 27 adiation intensity distribution (b) CH normalized max.CH intensity CH normalized max. intensity ne 28 PRF TRF (b)(b)normalized max. intensity 3000 3000 3000 1.0 50 29 (surrogate1)50 (surrogate2) 30 1.0 31 2500 0.8 2500 2500 32 40 40 0.8 33 0.6 34 2000 2000 2000 35 gasoline 30 30 0.6 36 surrogate1 0.4 gasoline 1500 1500 37 1500 surrogate2 surrogate1 38 0.4 surrogate3 20 20 39 surrogate2 0.2 surrogate4 1000 1000 40 1000 surrogate3 0.2 surrogate5 41 surrogate4 0.0 42 10 10 surrogate5 500 500 43 500 0.0 44 45 0 0 0 0 Fig. 8. Comparison 0 of CH chemiluminescence intensity between gasoline and gasoline surrogates 4 46 -4-2 0 2 4 -4-2 0 2 4 r (mm) r (mm) ) 47 48 49 50 51 52 53 54 55 56 57 58 59 60 27


Page 28 of 29

1.6


(a) 320 nm

1.0 0.8 0.6 0.4 0.2 0.0

1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

0

20

40 60 80 Toluene ratio (Vol%)

100

(b) 360 nm

1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

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1.6



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Energy & Fuels

(c) 400 nm

0

20


100

(d) 450 nm

1.4 1.2 1.0 0.8 0.6 0.4 0.2 0

20


100

Fig. 9. Normalized maximum PAHs-LIF signals as a function of toluene ratio in n-heptane/toluene mixture flames: (a) 320 nm, (b) 360 nm, (c) 400 nm, (d) 450 nm

28


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Energy & Fuels

Table with Caption Table 1 Composition of the various gasoline surrogate fuels Gasoline surrogate

Surrogate1[25]

Surrogate2[28]

Surrogate3[29]

Surrogate4[30]

Surrogate5[31]

N-heptane

0.08

0.17

0.11

1/3

0.137

Isooctane

0.92

0.63

0.59

1/3

0.429

Toluene

0

0.20

0.30

1/3

0.434

Octane number

92

86.5

95

73.6

91.4

Table 2 Physicochemical properties of components in gasoline surrogate fuel Parameter name

N-heptane

Isooctane

Toluene

Molecular formula

n-C7H16

i-C8H18

C6H5CH3

Relative molecular mass

100.2

114.23

92.14

Density/kg·m-3

684

691.9

866

Boiling point/0C

98.5

99.25

110.8

Low heat value/MJ·kg-1

44.93

44.65

40.94

RON

0

100

120

MON

0

100

103.5

29


Experimental Evaluation of Various Gasoline Surrogates Based on

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