- Email: [email protected]
Numerical and experimental study of gaseous fuel injection for CNG direct injection
Fuel 140 (2015) 693–700
Contents lists available at ScienceDirect
Fuel journal homepage: www.elsevier.com/locate/fuel
Numerical and experimental study of gaseous fuel injection for CNG direct injection Mingi Choi a, Sanghoon Lee a, Sungwook Park b,⇑ a b
Graduate School of Hanyang University, Seoul, Republic of Korea Department of Mechanical Engineering, Hanyang University, Seoul, Republic of Korea
h i g h l i g h t s KIVA-3V Release 2 code was modified for gaseous fuel injection. PLIF method was used for experiments of gaseous fuel injection. Gaseous fuel injection model was predicted well a general tendency of gas fuel injection. From the results, gaseous fuel injection model has the reliability about gas fuel direct injection.
a r t i c l e
i n f o
Article history: Received 8 February 2014 Received in revised form 1 October 2014 Accepted 8 October 2014 Available online 22 October 2014 Keywords: Gaseous fuel injection model KIVA-3V Release 2 code CNG direct injection Spray tip penetration Planar laser induced fluorescence
a b s t r a c t This paper describes numerical and experimental studies of gaseous fuel injection for CNG direct injection. To simulate the CNG direct injection, the injection sub-model was updated to include gaseous fuel injection methodology. The gaseous fuel injection methodology, which is similar to a liquid injection model, can be used in the KIVA-3V Release 2 code with some modifications. In addition, this model can be used to simulate gaseous fuel injection using a coarse mesh, which saves calculation time. The core region was defined as an inviscid region near the nozzle exit. The core length has an effect on the spray penetration where a longer core length results in longer spray penetration. The values of the turbulence kinetic energy, turbulence length scale, and turbulence kinetic energy dissipation rate were adjusted depending on the grid location since the RNG (re-normalization group) k–e turbulence model is known to over-predict gas jet diffusion. Furthermore, a PLIF (planar laser induced fluorescence) method was used for the gaseous fuel injection experiments. Acetone was selected as a tracer and post-image processing was performed using MATLAB code. In this study, the simulation results of CNG injection were compared to experimental data. Through comparison of the spray tip penetration results to experimental measurements, the gaseous fuel injection model produced reliable results for gas fuel direct injection. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Recently, the use of shale gas as an energy source has rapidly increased. Some analysts expect that shale gas will greatly expand the worldwide energy supply. In addition, a number of CNG vehicles have been produced because of environmental and economic advantages. Low emissions is one of the advantages of CNG vehicles [1,2]. In addition, the price of CNG is low compared to gasoline and diesel. Furthermore, gasoline vehicles can be easily converted to CNG vehicles with some modifications of the fuel supply system. ⇑ Corresponding author at: School of Mechanical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, Republic of Korea. Tel.: +82 2 2220 0430; fax: +82 2 2220 4588. E-mail address: [email protected] (S. Park). http://dx.doi.org/10.1016/j.fuel.2014.10.018 0016-2361/Ó 2014 Elsevier Ltd. All rights reserved.
In the foreseeable future, there will be an excess CNG supply and CNG vehicle demand is expected to increase. Meanwhile, the GDI (gasoline direct injection) engine has been widely used instead of the PFI (port fuel injection) engine because it demonstrates high fuel efficiency and high performance [3,4]. Therefore, if CNG fuel is applied in the GDI engine system, the emissions would be reduced. In addition, the CNG engine results in high engine performance and low fuel costs. For the development of the CNG direct injection engine, numerical simulation of the gas fuel injection must be conducted. Many researchers have investigated ways to simulate gas fuel injection [5–10]. Chitsaz et al. [11] reported an experimental and numerical study on the jet structure of a gaseous fuel injector in a spark ignition direct injection engine using the Schlieren technique and a numerical procedure. They found that a higher pressure ratio
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M. Choi et al. / Fuel 140 (2015) 693–700
Nomenclature Xc rnoz u0core Vinj Uc X
core length nozzle hole radius turbulence intensity injection velocity computed velocity at the current grid point axial distance from the nozzle exit
and larger exit nozzle diameter led to more tip penetration except in the initial stages of jet development. Baratta et al. [12] reported multi-dimensional modeling of methane direct injection and mixture formation in a stratified-charge SI engine with a centrally mounted injector using a very fine mesh near the injector nozzle. They used a very fine mesh to resolve the flow in the zone downstream of the nozzle and as a result, high computational effort is required to simulate the gas injection. Hong et al. [13] reported the development and application of multi-dimensional ignition, combustion, and emissions models which account for detailed chemistry and mixing effects in a direct injection engine simulation. Ra et al. [14] developed a new model to simulate the transient direct injection of a gaseous phase fuel into a combustion chamber using a practical computational grid. They reported that the new model successfully predicts gas jet behavior with a coarse grid compared to the results calculated using a fine mesh. Hessel et al. [15] investigated a method to simulate gas fuel injection using a coarse mesh. They reported gaseous fuel injection modeling using a gaseous fuel injection methodology. They introduced a new method for modeling the injection and air entrainment processes for gaseous fuel using a coarse mesh. Also, their model results were compared to experimental data. Furthermore, gas injection experiments have been conducted by many researchers [16–19]. Visualization of gaseous fuel injection can be performed using a laser system because gas injection is invisible to the naked eye. The Schlieren method is one of the visualization strategies of gaseous fuel injection. This method is a visual process that is used to photograph the flow of fluids of varying densities. The distortion creates a spatial variation in the intensity of the light, which can be visualized directly using a shadowgraph system. Also, the PLIF (planar laser induced fluorescent) method can be used for the visualization of gaseous fuel injection. In this study, the PLIF method was used for the visualization of gaseous fuel injection and the details are described in Section 3. In this paper, the method used to simulate gaseous fuel injection applied this gaseous fuel injection methodology [15]. The model was integrated in the KIVA-3V Release 2 code [20] and simulation of gaseous fuel injection was performed. Only the simulation results of CNG direct injection are covered in this paper.
2. Numerical approach In the present study, gaseous fuel injection modeling was performed using the KIVA-3V Release 2 code. In addition, the gaseous fuel injection model was integrated into the KIVA-3V Release 2 code to simulate gaseous fuel injection.
2.1. Gaseous fuel injection model The gaseous fuel injection model has some benefits for the simulation of gaseous fuel injection using the KIVA-3V Release 2 code. For example, this model can be used with little modification of the liquid fuel injection model. Also, a fine mesh is not required to
TKE TLS EPS CNG PLIF GDI
turbulence kinetic energy turbulence length scale turbulence kinetic energy dissipation rate compressed natural gas planar laser induced fluorescent gasoline direct injection
resolve the inflow boundary for gaseous fuel injection, which saves calculation time. As with liquid injection, gaseous spheres are injected as parcels which represent a group of gaseous spheres. In the liquid injection model, liquid spheres are considered as a spray droplets. And these droplets go through evaporation process. But, in the gaseous fuel injection model, it is assumed that gaseous spheres are considered as high density spheres of gaseous state. Therefore, the evaporation of gaseous spheres could be regarded as the diffusion of gaseous fuel. According to Witze’s report [21], he defined the core region as an inviscid region near the nozzle exit. The diameter of the core region is the same as the nozzle diameter. The core length is defined in the following equation:
X c ¼ 12:5 r noz
ð1Þ
X c ¼ core length rnoz ¼ nozzle hole radius In the core region, the temperature of the gaseous spheres does not change and gaseous spheres do not evaporate. The gaseous spheres evaporate at a time without energy exchange when the parcel escapes the core region, as shown in Fig. 1. The core length has an effect on the spray penetration. A longer core length results in longer spray penetration. 2.2. Modification of the RNG k–e turbulence model The RNG k–e turbulence model needs to be modified because this model tends to over-predict gas jet diffusion, as shown in Fig. 2(a). TKE (turbulence kinetic energy), TLS (turbulence length scale), and EPS (turbulence kinetic energy dissipation rate) values were assigned depending on the grid location. According to Witze’s report [21], these values in the core region can be described by the following equations:
u0core ¼ 0:12 V inj TKEcore ¼ 1:5
ð2Þ
u0core2
TLScore ¼ r noz
ð3Þ ð4Þ
EPScore ¼ cmueps
TKE1:5 core =TLScore
ð5Þ
u0core ¼ turbulence intensity V inj ¼ injection velocity TKEcore ¼ turbulence kinetic energy in the core region TLScore ¼ turbulence length scale in the core region EPScore ¼ turbulence kinetic energy dissipation rate in the core region cmueps ¼ 0:25 These values are different in the fully developed region, as shown in the following equations.
u0jet ¼ 0:2 U c TKEjet ¼ 1:5 TLSjet ¼ r 1=2
ð6Þ u0jet 2
ð7Þ ð8Þ
M. Choi et al. / Fuel 140 (2015) 693–700
695
Fig. 1. Schematic of the gaseous fuel injection model.
(a) Conventional model
(b) Updated model
Fig. 2. Modification of the RNG k–e turbulence model.
EPSjet ¼ cmueps TKE1:5 jet =TLSjet
ð9Þ
U c ¼ computed velocity at the current grid point r 1=2 ¼ 1:18 rnoz V inj =U axis U axis ¼ V inj =ð1:63 0:043 ðX X core Þ=r noz þ 1:0Þ X ¼ axial distance from the nozzle exit As shown in Fig. 2(b), the modified RNG k–e turbulence model predicts gas jet diffusion and gas spray penetration properly compared to the conventional model results. 3. Gaseous fuel injection experiments 3.1. Experimental setup Fig. 3 shows a schematic diagram of the experimental setup used in this study for gas-phase spray visualizations. The PLIF (planar laser induced fluorescence) system consists of a fuel injection system, a Nd:Yag laser (wavelength of 266 nm, power of 40 mJ),
sheet beam optics, a digital-pulse generator (BNC, Model 555), and an ICCD camera (Dicam-Pro, 16 bit gray level, 1280 1024 pixel resolution). For safety reasons, compressed nitrogen was used instead of natural gas in the experiments. Acetone was selected as a tracer because it has a very low boiling point of 329 K, a high saturation pressure of 24 kPa at 293 K, a good fluorescence yield, and low toxicity. The tracer which plays an important role in PLIF was produced using an acetone-seed generator by simple bubbling. The acetone vapor could be homogeneously mixed with the nitrogen gas flow in the pipe and the injection pressure can be flexibly controlled by a pressure regulator. The fluorescence was excited at 266 nm and the 50 mJ pulse laser energy. By passing through a convex lens and concave lens, a sheet beam laser is produced. The injection system was comprised of a test injector, an acetone-seed generator pressurized by nitrogen gas, an electronic control unit (ECU), and a 14 V power supply. The acetoneseed generator was designed to allow the liquid acetone to be evaporated under a constant pressure and temperature for uniform seed distribution with nitrogen gas so that the equivalent seeding gas was delivered to the injector at the selected pressure through a
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Fig. 3. Schematic diagram of the PLIF (planar laser induced fluorescence) apparatus.
Table 1 Experimental conditions employed for PLIF. Injection pressure Ambient pressure Ambient temperature Injection duration Nozzle hole diameter Injected fuel
2, 4.5 MPa 1 MPa 288 K 1.5 ms 0.14 mm N2
regulator. The power supply and ECU were used to generate injector-operating pulses. The details of the experimental conditions are shown in Table 1. 3.2. Post-image processing The spray was illuminated by a 1 mm light sheet generated by sheet-beam optics and captured with a time resolution of 2 ls by the camera. The camera and Nd:yag laser were synchronized with the injection pulse so that the images correspond to the time after the start of injection. The images captured by the ICCD camera were processed with MATLAB code to enhance the spray edge boundary and increase the image quality by removing background noise as well as transform the images into ‘pseudo color’ images so that the fuel concentration and distribution can be easily distinguished. Fig. 4 shows the original image, the enhanced image, and a representation of the pseudo color of the image. The red color 1 represents the highest density, while blue represents the lowest density. 4. Results and discussion 4.1. Model validation Validation of the gaseous fuel injection model was performed utilizing Yu’s experiment data [22]. The experimental conditions are shown in Table 2. The fuel was injected into a constant volume chamber and the image of gas spray was obtained by the PLIF (planar laser induced fluorescence) method. For safety reasons, com1
For interpretation of color in Fig. 4, the reader is referred to the web version of this article.
pressed nitrogen was used instead of compressed natural gas in the experiments. Fig. 5 shows the computational grids used for the gaseous fuel injection. As mentioned above, the gaseous fuel injection model can use a coarse mesh. These rectangular grids have a height of 100 mm and a length and width of 80 mm where the single cell size is 2 mm. A single hole injector was centrally mounted. Fig. 6 shows the comparison result of gaseous fuel injection by grid resolution change. All conditions were same except grid resolution. High resolution grid produces more detail shape of spray outline, but could not have an effect on penetration result. Fig. 7 shows the validation results of the gaseous fuel injection model. The injection pressures were 1 MPa and 2 MPa, the ambient pressure was 0.5 MPa, and the ambient temperature was 293 K. In addition, the injection duration was 4 ms and the nozzle hole diameter was 1.4 mm. A square wave was used as an injection pulse. Therefore, the mass flow rate and injection velocity were calculated by assuming a square wave profile. The simulation results agree well with the experiment data, as shown in Fig. 7. Fig. 8 shows distributions of the gaseous fuel depending on the injection pressure where the ambient pressure was 0.5 MPa and the nozzle hole diameter was 1.4 mm. With an injection pressure of 2 MPa, a longer spray penetration was obtained as time elapsed compared to an injection pressure of 1 MPa. The differences of the penetration results were within the acceptable range. Therefore, the gaseous fuel injection model is reliable for gas fuel direct injection. The modified RNG k–e turbulence model produced an acceptable result, as shown in Fig. 2. The conventional RNG k–e turbulence model tends to over-predict gas jet diffusion radially, which results in shorter penetration. The modified RNG k–e turbulence model reliably predicts the distribution of gaseous fuel as well. The modified RNG k–e turbulence model was used only for the injection period. After completing the fuel injection, the conventional RNG k–e turbulence model was used.
4.2. Image of gaseous fuel injection As mentioned above, a cross-sectional image of the gas injection was captured by the PLIF method. A liquid fuel injector for GDI engine was used in the experiment. Therefore, the diameter
M. Choi et al. / Fuel 140 (2015) 693–700
697
Fig. 4. Post-image processing using MATLAB code.
Fig. 5. Computational grids used for modeling gaseous fuel injection.
Fig. 6. Comparison of gaseous fuel injection results by grid resolution change.
Table 2 Experimental conditions for model validation [22]. Injection pressure Ambient pressure Ambient temperature Injection duration Nozzle hole diameter Injected fuel
1, 2 MPa 0.5 MPa 293 K 4 ms 1.4 mm N2
of the injector nozzle hole was very small compared to that of the gas fuel injector. The simulation was performed using the same conditions as the experiment. Fig. 9 shows the numerical
and experimental results of gas jet penetration depending on the injection pressure with values of 2 MPa and 4.5 MPa. At these pressures, the gas jet penetrations were 44.74 mm and 50.65 mm, respectively. The simulation results of the gas jet penetration agreed well with the experiment data. However, the simulation over predicted the diffusion of gas injection near the nozzle tip because the diameter of the injector nozzle hole was too small. In conclusion, the gaseous fuel injection model is not appropriate for the simulation of a liquid fuel injector using a coarse mesh. However, if one is not concerned about the gas jet diffusion near the nozzle tip, the gaseous fuel injection model could be used for the simulation of a very small nozzle type injector.
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M. Choi et al. / Fuel 140 (2015) 693–700 80
4.3. Fundamental study of gaseous fuel injection
70
A fundamental study of gaseous fuel injection was performed using the modified KIVA-3V Release 2 code. The gas jet penetration was defined as the distance from the nozzle hole exit to the spray tip. In the liquid fuel injection model, penetration is the distance of the farthest spray droplet from the nozzle hole. But this method could not be applied to the gaseous fuel injection model. Therefore, grid location with a range 0.1–1% fuel mole fraction is considered as the spray tip. Fig. 10 shows the changes of the core length depending on the nozzle hole diameter. As shown in Eq. (1), the core region was defined as a function of the nozzle hole diameter. The core diameter was equal to the nozzle diameter and as the nozzle hole size was increased, the core length increased, as shown in Fig. 10. Fig. 11 shows the spray penetration results depending on the nozzle hole diameter. The injection pressure, ambient pressure, and injection duration were the same in all three cases where
Penetration (mm)
60 50 40 30
Exp.(P=1MPa) Sim.(P=1MPa) Exp.(P=2MPa) Sim.(P=2MPa)
20 10 0 0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
T (ms) Fig. 7. Validation results of gaseous jet penetration (Penetration-distance from the nozzle hole exit to the spray tip).
Fig. 8. Distribution of gaseous fuel as a function of the injection pressure.
Fig. 9. Numerical and experimental results of gas jet penetration depending on the injection pressure.
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Fig. 10. The core length as a function of the nozzle hole diameter.
100
80
Amb.P=0.5MPa Amb.P=1.0MPa Amb.P=1.5MPa
80
70
Penetration (mm)
Penetration (mm)
100
Noz.D=0.4mm Noz.D=0.9mm Noz.D=1.4mm
90
60 50 40
60
40
30 20
20 10
0 0.0
0 0.0
0.5
1.0
1.5
2.0
2.5
0.2
3.0
Fig. 11. Gas jet penetration results as a function of the nozzle hole diameter.
Inj.P=1MPa Inj.P=2MPa Inj.P=3MPa
Penetration (mm)
80
60
40
20
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Fig. 13. Gas jet penetration results as a function of the ambient pressure.
In addition, Fig. 13 shows the spray penetration depending on the ambient pressure where the injection pressure was 1 MPa and the nozzle hole diameter was 1.4 mm. Similar to the liquid spray penetration trend, in the gaseous fuel injection simulation results, a higher ambient pressure resulted in a shorter predicted spray penetration. Fig. 12 shows the spray penetration as a function of the injection pressure where the ambient pressure was 0.5 MPa and the injector nozzle diameter was 1.4 mm. As the applied injection pressure was increased, the predicted spray penetration increased. In conclusion, the gaseous fuel injection model predicted the general tendency of gas fuel injection well. Therefore, the gaseous fuel injection model can be used for the simulation of gaseous fuel injection using a coarse mesh. In addition, the gaseous fuel injection model has advantages for simulation of CNG direct injection and combustion because of the ability to use a coarse mesh.
120
0 0.0
0.6
T (ms)
T (ms)
100
0.4
0.8
1.0
1.2
1.4
1.6
1.8
2.0
T (ms)
5. Conclusions
Fig. 12. Gas jet penetration results as a function of the injection pressure.
the nozzle hole diameters were 0.4 mm, 0.9 mm, and 1.4 mm. As is well known, a longer spray penetration was obtained with a larger nozzle hole size in the simulation results.
For simulation of gaseous fuel injection, a gaseous fuel injection model was integrated in the KIVA-3V Release 2 code. The KIVA-3V Release 2 code could handle gaseous fuel injection with some modifications. The conclusions of present study can be summarized as follows.
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(1) The core region was defined as an inviscid region near the nozzle exit. The core region was dependent on the nozzle hole size. The core region has an effect on the gas fuel penetration. (2) The RNG k–e turbulence model needs to be modified because this model tends to over-predict gas jet diffusion radially. Turbulence kinetic energy, turbulence length scale, and turbulence kinetic energy dissipation rate values were assigned depending on the grid location. The modified RNG k–e turbulence model was used only for the injection period. After the fuel injection was finished, the conventional RNG k–e turbulence model was used. (3) The gaseous fuel injection model was validated using experiment data. The simulation results agreed well with the experiment data. Therefore, the gaseous fuel injection model can reliably predict gas fuel direct injection. (4) Gas injection experiments were performed using a liquid fuel injector. A cross-sectional image of gas injection could be captured by the PLIF method. The simulation results of gas jet penetration agree well with the experiment data. However, it is not appropriate for the simulation of the liquid fuel injector using a coarse mesh. If one is not concerned about the gas jet diffusion near the nozzle tip, the gaseous fuel injection model can be used for the simulation of a very small nozzle type injector. (5) The gaseous fuel injection model predicted the general tendency of gas fuel injection well. Therefore, the gaseous fuel injection model can be used for gas fuel injection using a coarse mesh. In addition, it can be used for simulation of CNG direct injection and combustion.
Acknowledgments This work was supported by the Researcher Program (NRF2013R1A1A2074615) through a NRF (National Research Foundation) grant funded by the MSIP (Ministry of Science, ICT and Future Planning). References [1] Lee J, Choi S, Kim H, Kim D, Choi H, Min K. Reduction of emissions with propane addition to a diesel engine. Int J Automot Technol 2013;14:551–8.
[2] Yu X, Liu Z, Wang Z, Dou H. Optimize combustion of compressed natural gas engine by improving in-cylinder flows. Int J Automot Technol 2013;14:539–49. [3] Zhao F, Lai MC, Harrington DL. Automotive spark-ignited direct-injection gasoline engines. Prog Energy Combust Sci 1999;25:437–562. [4] Iwamoto Y, Noma K, Nakayama O, Yamauchi T, Ando H. Development of gasoline direct injection engine. SAE Technical Papers; 1997. [5] Ouelette P, Hill PG. Visualization of natural gas injection for a compression ignition engine. SAE Technical Papers; 1992. [6] Mather DK, Reitz RD. Modeling the effects of auxiliary gas injection on diesel engine combustion and emissions. SAE Technical Papers; 2000. [7] Mather DK, Foster DE, Poola RB, Longman DE, Chanda A, Vachon TJ. Modeling the effects of late cycle oxygen enrichment on diesel engine combustion and emissions. SAE Technical Papers; 2002. [8] Baratta M, Catania AE, Spessa E, Herrmann L, Roessler K. Multi-dimensional modeling of direct natural-gas injection and mixture formation in a stratifiedcharge SI engine with centrally mounted injector. SAE Int J Engine 2008;1:607–26. [9] Whitesides R, Hessel RP, Flowers DL, Aceves SM. Application of gaseous sphere injection method for modeling under-expanded H2 injection. Combust Theor Model 2011;15:373–84. [10] Otobe Y, Kashimura H, Matsuo S, Setoguchi T, Kim HD. Influence of nozzle geometry on the near-field structure of a highly underexpanded sonic jet. J Fluids Struct 2008;24:281–93. [11] Chitsaz I, Saidi MH, Mozafari AA, Hajialimohammadi A. Experimental and numerical investigation on the jet characteristics of spark ignition direct injection gaseous injector. Appl Energy 2013;105:8–16. [12] Baratta M, Rapetto N, Spessa E, Fuerhapter A, Philipp H. Numerical and experimental analysis of mixture formation and performance in a direct injection CNG engine. SAE Technical Papers; 2012. [13] Hong S, Assanis D, Wooldridge M. Multi-dimensional modeling of NO and soot emissions with detailed chemistry and mixing in a direct injection natural gas engine. SAE Technical Papers; 2002. [14] Ra Y, Kong SC, Reitz RD, Rutland CJ, Han Z. Multidimensional modeling of transient gas jet injection using coarse computational grids. SAE Technical Papers; 2005. [15] Hessel RP, Abani N, Aceves SM, Flowers DL. Gaseous fuel injection modeling using a gaseous sphere injection methodology. SAE Technical Papers; 2006. [16] White TR, Milton BE. Shock wave calibration of under-expanded natural gas fuel jets. Shock Waves 2008;18:353–64. [17] Rubas PJ, Paul MA, Martin GC, Coverdill RE, Lucht RP, Peters JE, et al. Methane jet penetration in a direct-injection natural gas engine. SAE Technical Papers; 1998. [18] Johansen LCR, de Benito Sienes E, Dahlander P. Analysis of transient compressible gas jets using high speed schlieren imaging. SAE Technical Papers; 2013. [19] Kalam MA, Masjuki HH. An experimental investigation of high performance natural gas engine with direct injection. Energy 2011;36:3563–71. [20] Amsden AA. KIVA-3V Release 2, Improvement to KIVA-3V. Los Alamos National Laboratory Report. 1999; No. LA-UR-99-915. [21] Witze PO. Impulsively started incompressible turbulent jet. 1980. Sandia National Laboratory Report. 1980; No. SAND-80-8617. [22] Yu J, Vuorinen V, Hillamo H, Sarjovaara T, Kaario O, Larmi M. An experimental study on high pressure pulsed jets for DI gas engine using planar laser-induced fluorescence. SAE Technical Papers; 2012.
Contents lists available at ScienceDirect
Fuel journal homepage: www.elsevier.com/locate/fuel
Numerical and experimental study of gaseous fuel injection for CNG direct injection Mingi Choi a, Sanghoon Lee a, Sungwook Park b,⇑ a b
Graduate School of Hanyang University, Seoul, Republic of Korea Department of Mechanical Engineering, Hanyang University, Seoul, Republic of Korea
h i g h l i g h t s KIVA-3V Release 2 code was modified for gaseous fuel injection. PLIF method was used for experiments of gaseous fuel injection. Gaseous fuel injection model was predicted well a general tendency of gas fuel injection. From the results, gaseous fuel injection model has the reliability about gas fuel direct injection.
a r t i c l e
i n f o
Article history: Received 8 February 2014 Received in revised form 1 October 2014 Accepted 8 October 2014 Available online 22 October 2014 Keywords: Gaseous fuel injection model KIVA-3V Release 2 code CNG direct injection Spray tip penetration Planar laser induced fluorescence
a b s t r a c t This paper describes numerical and experimental studies of gaseous fuel injection for CNG direct injection. To simulate the CNG direct injection, the injection sub-model was updated to include gaseous fuel injection methodology. The gaseous fuel injection methodology, which is similar to a liquid injection model, can be used in the KIVA-3V Release 2 code with some modifications. In addition, this model can be used to simulate gaseous fuel injection using a coarse mesh, which saves calculation time. The core region was defined as an inviscid region near the nozzle exit. The core length has an effect on the spray penetration where a longer core length results in longer spray penetration. The values of the turbulence kinetic energy, turbulence length scale, and turbulence kinetic energy dissipation rate were adjusted depending on the grid location since the RNG (re-normalization group) k–e turbulence model is known to over-predict gas jet diffusion. Furthermore, a PLIF (planar laser induced fluorescence) method was used for the gaseous fuel injection experiments. Acetone was selected as a tracer and post-image processing was performed using MATLAB code. In this study, the simulation results of CNG injection were compared to experimental data. Through comparison of the spray tip penetration results to experimental measurements, the gaseous fuel injection model produced reliable results for gas fuel direct injection. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Recently, the use of shale gas as an energy source has rapidly increased. Some analysts expect that shale gas will greatly expand the worldwide energy supply. In addition, a number of CNG vehicles have been produced because of environmental and economic advantages. Low emissions is one of the advantages of CNG vehicles [1,2]. In addition, the price of CNG is low compared to gasoline and diesel. Furthermore, gasoline vehicles can be easily converted to CNG vehicles with some modifications of the fuel supply system. ⇑ Corresponding author at: School of Mechanical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, Republic of Korea. Tel.: +82 2 2220 0430; fax: +82 2 2220 4588. E-mail address: [email protected] (S. Park). http://dx.doi.org/10.1016/j.fuel.2014.10.018 0016-2361/Ó 2014 Elsevier Ltd. All rights reserved.
In the foreseeable future, there will be an excess CNG supply and CNG vehicle demand is expected to increase. Meanwhile, the GDI (gasoline direct injection) engine has been widely used instead of the PFI (port fuel injection) engine because it demonstrates high fuel efficiency and high performance [3,4]. Therefore, if CNG fuel is applied in the GDI engine system, the emissions would be reduced. In addition, the CNG engine results in high engine performance and low fuel costs. For the development of the CNG direct injection engine, numerical simulation of the gas fuel injection must be conducted. Many researchers have investigated ways to simulate gas fuel injection [5–10]. Chitsaz et al. [11] reported an experimental and numerical study on the jet structure of a gaseous fuel injector in a spark ignition direct injection engine using the Schlieren technique and a numerical procedure. They found that a higher pressure ratio
694
M. Choi et al. / Fuel 140 (2015) 693–700
Nomenclature Xc rnoz u0core Vinj Uc X
core length nozzle hole radius turbulence intensity injection velocity computed velocity at the current grid point axial distance from the nozzle exit
and larger exit nozzle diameter led to more tip penetration except in the initial stages of jet development. Baratta et al. [12] reported multi-dimensional modeling of methane direct injection and mixture formation in a stratified-charge SI engine with a centrally mounted injector using a very fine mesh near the injector nozzle. They used a very fine mesh to resolve the flow in the zone downstream of the nozzle and as a result, high computational effort is required to simulate the gas injection. Hong et al. [13] reported the development and application of multi-dimensional ignition, combustion, and emissions models which account for detailed chemistry and mixing effects in a direct injection engine simulation. Ra et al. [14] developed a new model to simulate the transient direct injection of a gaseous phase fuel into a combustion chamber using a practical computational grid. They reported that the new model successfully predicts gas jet behavior with a coarse grid compared to the results calculated using a fine mesh. Hessel et al. [15] investigated a method to simulate gas fuel injection using a coarse mesh. They reported gaseous fuel injection modeling using a gaseous fuel injection methodology. They introduced a new method for modeling the injection and air entrainment processes for gaseous fuel using a coarse mesh. Also, their model results were compared to experimental data. Furthermore, gas injection experiments have been conducted by many researchers [16–19]. Visualization of gaseous fuel injection can be performed using a laser system because gas injection is invisible to the naked eye. The Schlieren method is one of the visualization strategies of gaseous fuel injection. This method is a visual process that is used to photograph the flow of fluids of varying densities. The distortion creates a spatial variation in the intensity of the light, which can be visualized directly using a shadowgraph system. Also, the PLIF (planar laser induced fluorescent) method can be used for the visualization of gaseous fuel injection. In this study, the PLIF method was used for the visualization of gaseous fuel injection and the details are described in Section 3. In this paper, the method used to simulate gaseous fuel injection applied this gaseous fuel injection methodology [15]. The model was integrated in the KIVA-3V Release 2 code [20] and simulation of gaseous fuel injection was performed. Only the simulation results of CNG direct injection are covered in this paper.
2. Numerical approach In the present study, gaseous fuel injection modeling was performed using the KIVA-3V Release 2 code. In addition, the gaseous fuel injection model was integrated into the KIVA-3V Release 2 code to simulate gaseous fuel injection.
2.1. Gaseous fuel injection model The gaseous fuel injection model has some benefits for the simulation of gaseous fuel injection using the KIVA-3V Release 2 code. For example, this model can be used with little modification of the liquid fuel injection model. Also, a fine mesh is not required to
TKE TLS EPS CNG PLIF GDI
turbulence kinetic energy turbulence length scale turbulence kinetic energy dissipation rate compressed natural gas planar laser induced fluorescent gasoline direct injection
resolve the inflow boundary for gaseous fuel injection, which saves calculation time. As with liquid injection, gaseous spheres are injected as parcels which represent a group of gaseous spheres. In the liquid injection model, liquid spheres are considered as a spray droplets. And these droplets go through evaporation process. But, in the gaseous fuel injection model, it is assumed that gaseous spheres are considered as high density spheres of gaseous state. Therefore, the evaporation of gaseous spheres could be regarded as the diffusion of gaseous fuel. According to Witze’s report [21], he defined the core region as an inviscid region near the nozzle exit. The diameter of the core region is the same as the nozzle diameter. The core length is defined in the following equation:
X c ¼ 12:5 r noz
ð1Þ
X c ¼ core length rnoz ¼ nozzle hole radius In the core region, the temperature of the gaseous spheres does not change and gaseous spheres do not evaporate. The gaseous spheres evaporate at a time without energy exchange when the parcel escapes the core region, as shown in Fig. 1. The core length has an effect on the spray penetration. A longer core length results in longer spray penetration. 2.2. Modification of the RNG k–e turbulence model The RNG k–e turbulence model needs to be modified because this model tends to over-predict gas jet diffusion, as shown in Fig. 2(a). TKE (turbulence kinetic energy), TLS (turbulence length scale), and EPS (turbulence kinetic energy dissipation rate) values were assigned depending on the grid location. According to Witze’s report [21], these values in the core region can be described by the following equations:
u0core ¼ 0:12 V inj TKEcore ¼ 1:5
ð2Þ
u0core2
TLScore ¼ r noz
ð3Þ ð4Þ
EPScore ¼ cmueps
TKE1:5 core =TLScore
ð5Þ
u0core ¼ turbulence intensity V inj ¼ injection velocity TKEcore ¼ turbulence kinetic energy in the core region TLScore ¼ turbulence length scale in the core region EPScore ¼ turbulence kinetic energy dissipation rate in the core region cmueps ¼ 0:25 These values are different in the fully developed region, as shown in the following equations.
u0jet ¼ 0:2 U c TKEjet ¼ 1:5 TLSjet ¼ r 1=2
ð6Þ u0jet 2
ð7Þ ð8Þ
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Fig. 1. Schematic of the gaseous fuel injection model.
(a) Conventional model
(b) Updated model
Fig. 2. Modification of the RNG k–e turbulence model.
EPSjet ¼ cmueps TKE1:5 jet =TLSjet
ð9Þ
U c ¼ computed velocity at the current grid point r 1=2 ¼ 1:18 rnoz V inj =U axis U axis ¼ V inj =ð1:63 0:043 ðX X core Þ=r noz þ 1:0Þ X ¼ axial distance from the nozzle exit As shown in Fig. 2(b), the modified RNG k–e turbulence model predicts gas jet diffusion and gas spray penetration properly compared to the conventional model results. 3. Gaseous fuel injection experiments 3.1. Experimental setup Fig. 3 shows a schematic diagram of the experimental setup used in this study for gas-phase spray visualizations. The PLIF (planar laser induced fluorescence) system consists of a fuel injection system, a Nd:Yag laser (wavelength of 266 nm, power of 40 mJ),
sheet beam optics, a digital-pulse generator (BNC, Model 555), and an ICCD camera (Dicam-Pro, 16 bit gray level, 1280 1024 pixel resolution). For safety reasons, compressed nitrogen was used instead of natural gas in the experiments. Acetone was selected as a tracer because it has a very low boiling point of 329 K, a high saturation pressure of 24 kPa at 293 K, a good fluorescence yield, and low toxicity. The tracer which plays an important role in PLIF was produced using an acetone-seed generator by simple bubbling. The acetone vapor could be homogeneously mixed with the nitrogen gas flow in the pipe and the injection pressure can be flexibly controlled by a pressure regulator. The fluorescence was excited at 266 nm and the 50 mJ pulse laser energy. By passing through a convex lens and concave lens, a sheet beam laser is produced. The injection system was comprised of a test injector, an acetone-seed generator pressurized by nitrogen gas, an electronic control unit (ECU), and a 14 V power supply. The acetoneseed generator was designed to allow the liquid acetone to be evaporated under a constant pressure and temperature for uniform seed distribution with nitrogen gas so that the equivalent seeding gas was delivered to the injector at the selected pressure through a
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Fig. 3. Schematic diagram of the PLIF (planar laser induced fluorescence) apparatus.
Table 1 Experimental conditions employed for PLIF. Injection pressure Ambient pressure Ambient temperature Injection duration Nozzle hole diameter Injected fuel
2, 4.5 MPa 1 MPa 288 K 1.5 ms 0.14 mm N2
regulator. The power supply and ECU were used to generate injector-operating pulses. The details of the experimental conditions are shown in Table 1. 3.2. Post-image processing The spray was illuminated by a 1 mm light sheet generated by sheet-beam optics and captured with a time resolution of 2 ls by the camera. The camera and Nd:yag laser were synchronized with the injection pulse so that the images correspond to the time after the start of injection. The images captured by the ICCD camera were processed with MATLAB code to enhance the spray edge boundary and increase the image quality by removing background noise as well as transform the images into ‘pseudo color’ images so that the fuel concentration and distribution can be easily distinguished. Fig. 4 shows the original image, the enhanced image, and a representation of the pseudo color of the image. The red color 1 represents the highest density, while blue represents the lowest density. 4. Results and discussion 4.1. Model validation Validation of the gaseous fuel injection model was performed utilizing Yu’s experiment data [22]. The experimental conditions are shown in Table 2. The fuel was injected into a constant volume chamber and the image of gas spray was obtained by the PLIF (planar laser induced fluorescence) method. For safety reasons, com1
For interpretation of color in Fig. 4, the reader is referred to the web version of this article.
pressed nitrogen was used instead of compressed natural gas in the experiments. Fig. 5 shows the computational grids used for the gaseous fuel injection. As mentioned above, the gaseous fuel injection model can use a coarse mesh. These rectangular grids have a height of 100 mm and a length and width of 80 mm where the single cell size is 2 mm. A single hole injector was centrally mounted. Fig. 6 shows the comparison result of gaseous fuel injection by grid resolution change. All conditions were same except grid resolution. High resolution grid produces more detail shape of spray outline, but could not have an effect on penetration result. Fig. 7 shows the validation results of the gaseous fuel injection model. The injection pressures were 1 MPa and 2 MPa, the ambient pressure was 0.5 MPa, and the ambient temperature was 293 K. In addition, the injection duration was 4 ms and the nozzle hole diameter was 1.4 mm. A square wave was used as an injection pulse. Therefore, the mass flow rate and injection velocity were calculated by assuming a square wave profile. The simulation results agree well with the experiment data, as shown in Fig. 7. Fig. 8 shows distributions of the gaseous fuel depending on the injection pressure where the ambient pressure was 0.5 MPa and the nozzle hole diameter was 1.4 mm. With an injection pressure of 2 MPa, a longer spray penetration was obtained as time elapsed compared to an injection pressure of 1 MPa. The differences of the penetration results were within the acceptable range. Therefore, the gaseous fuel injection model is reliable for gas fuel direct injection. The modified RNG k–e turbulence model produced an acceptable result, as shown in Fig. 2. The conventional RNG k–e turbulence model tends to over-predict gas jet diffusion radially, which results in shorter penetration. The modified RNG k–e turbulence model reliably predicts the distribution of gaseous fuel as well. The modified RNG k–e turbulence model was used only for the injection period. After completing the fuel injection, the conventional RNG k–e turbulence model was used.
4.2. Image of gaseous fuel injection As mentioned above, a cross-sectional image of the gas injection was captured by the PLIF method. A liquid fuel injector for GDI engine was used in the experiment. Therefore, the diameter
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Fig. 4. Post-image processing using MATLAB code.
Fig. 5. Computational grids used for modeling gaseous fuel injection.
Fig. 6. Comparison of gaseous fuel injection results by grid resolution change.
Table 2 Experimental conditions for model validation [22]. Injection pressure Ambient pressure Ambient temperature Injection duration Nozzle hole diameter Injected fuel
1, 2 MPa 0.5 MPa 293 K 4 ms 1.4 mm N2
of the injector nozzle hole was very small compared to that of the gas fuel injector. The simulation was performed using the same conditions as the experiment. Fig. 9 shows the numerical
and experimental results of gas jet penetration depending on the injection pressure with values of 2 MPa and 4.5 MPa. At these pressures, the gas jet penetrations were 44.74 mm and 50.65 mm, respectively. The simulation results of the gas jet penetration agreed well with the experiment data. However, the simulation over predicted the diffusion of gas injection near the nozzle tip because the diameter of the injector nozzle hole was too small. In conclusion, the gaseous fuel injection model is not appropriate for the simulation of a liquid fuel injector using a coarse mesh. However, if one is not concerned about the gas jet diffusion near the nozzle tip, the gaseous fuel injection model could be used for the simulation of a very small nozzle type injector.
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4.3. Fundamental study of gaseous fuel injection
70
A fundamental study of gaseous fuel injection was performed using the modified KIVA-3V Release 2 code. The gas jet penetration was defined as the distance from the nozzle hole exit to the spray tip. In the liquid fuel injection model, penetration is the distance of the farthest spray droplet from the nozzle hole. But this method could not be applied to the gaseous fuel injection model. Therefore, grid location with a range 0.1–1% fuel mole fraction is considered as the spray tip. Fig. 10 shows the changes of the core length depending on the nozzle hole diameter. As shown in Eq. (1), the core region was defined as a function of the nozzle hole diameter. The core diameter was equal to the nozzle diameter and as the nozzle hole size was increased, the core length increased, as shown in Fig. 10. Fig. 11 shows the spray penetration results depending on the nozzle hole diameter. The injection pressure, ambient pressure, and injection duration were the same in all three cases where
Penetration (mm)
60 50 40 30
Exp.(P=1MPa) Sim.(P=1MPa) Exp.(P=2MPa) Sim.(P=2MPa)
20 10 0 0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
T (ms) Fig. 7. Validation results of gaseous jet penetration (Penetration-distance from the nozzle hole exit to the spray tip).
Fig. 8. Distribution of gaseous fuel as a function of the injection pressure.
Fig. 9. Numerical and experimental results of gas jet penetration depending on the injection pressure.
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Fig. 10. The core length as a function of the nozzle hole diameter.
100
80
Amb.P=0.5MPa Amb.P=1.0MPa Amb.P=1.5MPa
80
70
Penetration (mm)
Penetration (mm)
100
Noz.D=0.4mm Noz.D=0.9mm Noz.D=1.4mm
90
60 50 40
60
40
30 20
20 10
0 0.0
0 0.0
0.5
1.0
1.5
2.0
2.5
0.2
3.0
Fig. 11. Gas jet penetration results as a function of the nozzle hole diameter.
Inj.P=1MPa Inj.P=2MPa Inj.P=3MPa
Penetration (mm)
80
60
40
20
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Fig. 13. Gas jet penetration results as a function of the ambient pressure.
In addition, Fig. 13 shows the spray penetration depending on the ambient pressure where the injection pressure was 1 MPa and the nozzle hole diameter was 1.4 mm. Similar to the liquid spray penetration trend, in the gaseous fuel injection simulation results, a higher ambient pressure resulted in a shorter predicted spray penetration. Fig. 12 shows the spray penetration as a function of the injection pressure where the ambient pressure was 0.5 MPa and the injector nozzle diameter was 1.4 mm. As the applied injection pressure was increased, the predicted spray penetration increased. In conclusion, the gaseous fuel injection model predicted the general tendency of gas fuel injection well. Therefore, the gaseous fuel injection model can be used for the simulation of gaseous fuel injection using a coarse mesh. In addition, the gaseous fuel injection model has advantages for simulation of CNG direct injection and combustion because of the ability to use a coarse mesh.
120
0 0.0
0.6
T (ms)
T (ms)
100
0.4
0.8
1.0
1.2
1.4
1.6
1.8
2.0
T (ms)
5. Conclusions
Fig. 12. Gas jet penetration results as a function of the injection pressure.
the nozzle hole diameters were 0.4 mm, 0.9 mm, and 1.4 mm. As is well known, a longer spray penetration was obtained with a larger nozzle hole size in the simulation results.
For simulation of gaseous fuel injection, a gaseous fuel injection model was integrated in the KIVA-3V Release 2 code. The KIVA-3V Release 2 code could handle gaseous fuel injection with some modifications. The conclusions of present study can be summarized as follows.
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(1) The core region was defined as an inviscid region near the nozzle exit. The core region was dependent on the nozzle hole size. The core region has an effect on the gas fuel penetration. (2) The RNG k–e turbulence model needs to be modified because this model tends to over-predict gas jet diffusion radially. Turbulence kinetic energy, turbulence length scale, and turbulence kinetic energy dissipation rate values were assigned depending on the grid location. The modified RNG k–e turbulence model was used only for the injection period. After the fuel injection was finished, the conventional RNG k–e turbulence model was used. (3) The gaseous fuel injection model was validated using experiment data. The simulation results agreed well with the experiment data. Therefore, the gaseous fuel injection model can reliably predict gas fuel direct injection. (4) Gas injection experiments were performed using a liquid fuel injector. A cross-sectional image of gas injection could be captured by the PLIF method. The simulation results of gas jet penetration agree well with the experiment data. However, it is not appropriate for the simulation of the liquid fuel injector using a coarse mesh. If one is not concerned about the gas jet diffusion near the nozzle tip, the gaseous fuel injection model can be used for the simulation of a very small nozzle type injector. (5) The gaseous fuel injection model predicted the general tendency of gas fuel injection well. Therefore, the gaseous fuel injection model can be used for gas fuel injection using a coarse mesh. In addition, it can be used for simulation of CNG direct injection and combustion.
Acknowledgments This work was supported by the Researcher Program (NRF2013R1A1A2074615) through a NRF (National Research Foundation) grant funded by the MSIP (Ministry of Science, ICT and Future Planning). References [1] Lee J, Choi S, Kim H, Kim D, Choi H, Min K. Reduction of emissions with propane addition to a diesel engine. Int J Automot Technol 2013;14:551–8.
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