Simulation of single diesel droplet evaporation and combustion process with a unified diesel surrogate

ILASS-Americas 29th Annual Conference on Liquid Atomization and Spray Systems, Atlanta, GA, May 2017 Simulation of single diesel droplet evaporation and combustion process with a unified diesel surrogate Qiaoling Wang, C. P. Chen * University of Michigan-SJTU Joint Institute Shanghai Jiao Tong University Shanghai, China Abstract Real diesel fuel is composed of hundreds to thousands of components and is not suitable for multi-dimensional spray combustion simulations. Besides, the diesel spray combustion process involves both thermo-physical (heating and evaporation) and chemical (ignition and combustion) process. Therefore, unitizing a surrogate fuel with only a few representative components that can accurately capture both physical and chemical properties of real diesel fuel is essential for diesel spray combustion calculations. To this end, we have recently developed a unified surrogate that can simultaneously mimic the physical properties, distillation curve and combustion characteristics (ignition delays and laminar flame speeds) of a real diesel fuel. The developed surrogate has four representative components C 9 H 12 (1,2,4-trimethylbenzene), C 10 H 18 (trans-decalin), ic 16 H 34 (heptamethylnonane), and C 16 H 34 (n-hexadecane) from the hydrocarbon groups of linear paraffins, cyclo-paraffins and aromatics with mole fraction: 0.262/0.065/0.365/0.319. The purpose of this study is to use this surrogate to study a single diesel droplet s heating/evaporation and ignition process and compare the simulation results to experimental data. In this study, the recently developed discrete multicomponent modeling methodology with finite thermal and mass transfer rate was used to perform the single liquid droplet s heating, evaporation and ignition process. A detailed chemical kinetics of 352 species with 13264 reactions is used for ignition prediction. Comparisons are then made among surrogate droplet simulation results with experimental data. Our proposed multi-components surrogate model gives good prediction for both heating/evaporation and ignition delay times when compared with single diesel droplet s experimental data. * Corresponding author: chienpin.chen@sjtu.edu.cn

Introduction Diesel fuel has been extensively used in various transportation sectors, as well as for industrial generators and home heating, as it delivers good fuel economy. The diesel fuel is directly injected into cylinder of an engine by an injector system. Thus, fundamental understandings of diesel fuel atomization, spray, evaporation and ignition/combustion is of direct relevance in proving engine performance and emission control. Multidimensional spray combustion simulations have become an important tool, in conjunction with experimental setups, to gain insights of spray combustion processes in engines. Real diesel is a mixture of hundreds to thousands of hydrocarbon specie. Despite recent advances in CPU/GPU power, performing spray combustion simulation of real fuels with the entire hydrocarbon species is not possible. To this end, utilizing surrogate fuels composed of a limited number of representative hydrocarbon components that can mimic some targeted real fuel properties is essential. The objective of this study is to utilize a recently developed surrogate fuel to study a single diesel droplet s heating/evaporation and ignition process and validate the results by comparing to available experimental data. The study of a single multi-components droplet is an essential step to further extend to real multidimensional diesel spray combustion simulations. In this study, a recently developed discrete multicomponent modeling methodology with finite thermal and mass transfer rate was used to perform the single liquid droplet s heating, evaporation and ignition process. The unified diesel surrogate fuel The surrogate fuel used for this study is the unified surrogate model [1] matching both physical (distillation curves, density etc..) and chemical (ignition delay etc..) properties of the diesel fuel. For typical diesel fuel, the 2007 #2 ULSD certified diesel fuel denoted as CFA in [2] and a typical U.S#2 diesel fuel described in [3] are used as a target. The diesel surrogate was first formulated based on the distillation curve property matching since it is one of the important properties for droplet heating and evaporation. Then the concentration of components is adjusted to match the physical properties of U.S#2 diesel. In order to consider the chemical properties of diesel surrogates, components whose chemical kinetics is available in literature are selected. The boiling point of U.S#2 diesel fuel varies from 463 K to 623 K, which make it challenging to select heavy component whose chemical kinetics are available. After some trials, our proposed diesel surrogates are summarized in Table 1, in which the baseline 4-component surrogate directly derived from the methodology of [4] is named JI-D. In addition to the baseline surrogate, two additional surrogates (_ad1 and _ad2) are proposed by adjusting the compositions to better match other physical properties. COMP JI-D JI-D_ad1 JI-D_ad2 mass mole mass mole mass mole nc16h34 0.398 0.349 0.362 0.309 0.319 0.269 ic16h34 0.44 0.385 0.428 0.365 0.455 0.384 C10H18 0.003 0.005 0.047 0.065 0.061 0.085 C9H12 0.159 0.262 0.163 0.262 0.165 0.262 Table 1. Compositions of JI-D, JI-D_ad1 and JI-D_ad2. The predicted distillation curves using the three surrogates are shown in Fig. 1. All distillation curves match reasonably well with experimental data of [3] and [2] (measured with ASTM D86 method) from 10 to 80 volume fractions. The wide range of boiling temperature of components in diesel fuel makes it hard to match the whole distillation curve. Toward the end of distillation, surrogates deviates from real diesel fuel due to lack of heavy component in the current proposed surrogates. Figure 1. Predictive distillation curves of JI-D, JI- D_ad1 and JI-D_ad2; experimental data [2, 3] used for comparison. The physical properties of CFA, U.S#2 diesel and three surrogates are listed in Table 2. The surrogate mixture properties were estimated with methods introduced in [5]. The molecule weight of surrogate JI- D, JI-D_ad1 and JI-D_ad2 are 209.24, 204.99 and 203.49 respectively. CFA and U.S#2 diesel have density of 848 kg/m 3 and 843 kg/m 3 while the adjusted JI-D_ad1 and JI-D_ad2 predict 803 kg/m 3 and 805 kg/m 3. The overall deviation for density is about 4.5-5.3. For low heating value, all three surrogates give good predictions. The LHV (lower heating value) for CFA and U.S#2 are 42.9 MJ/kg and 42.98 MJ/kg, while

JI-D_ad1 and JI-D_ad2 give 43.36 MJ/kg and 43.34 MJ/kg respectively. The overall deviation of LHV is about 0.84-1.1. For DCN (derived cetane number), CFA diesel and U.S#2 vary and give values of 43.7 and 46. DCN of JI-D_ad1 is 46.8 which is close to U.S#2 and gives deviation of 1.7. DCN of JI-D_ad2 is 43.3 which is close to CFA and gives deviation of 0.92. C/H mass ratio of JI-D_ad1 and JI-D_ad2 gives deviation of 7-9 when compared to the experimental data. From these validation studies, the JI- D_ad1 shows best overall comparisons, and is shosen to be the surrogate fule for further invistigation. CFA U.S#2 JI-D JI-D _ad1 JI-D _ad2 MW 209.24 204.99 203.49 LHV MJ/kg 42.9 42.98 43.44 43.36 43.34 DCN 43.7 46 49.1 46.8 43.3 C/H ratio 6.68 6.53 5.98 6.04 6.05 Density kg/m 3 20 848 843 799 803 805 Table 2. Physical properties of the three surrogates compared with CFA and U.S#2 diesel fuel data. To match chemical property of the diesel, the gas phase ignition delay times are predicted using the surrogate fuel JI-D_ad1. The numerical tool Cantera [6] with constant volume homogeneous reactor setup and a detailed chemical kinetics of 352 and 13264 reactions [7] was used to predict the gas phase ignition delay. In Fig. 2, ignition delay times of JI-D_ad1 are compared with U.S#2 diesels experimental data [8] under different conditions. At higher pressure condition, predicted ignition delay times of JI-D_ad1 matches better with experimental data as compared to low pressure predictions. Under the equivalence ratio (phi) equals to 0.69, P (pressure) equals to 10.0bar and phi equals to 1.02, P equals to 15.0bar conditions, JI-D_ad1 over-predicts the ignition delay. From these comparisons, the overall tendency of ignition delay times, as well as the Negative Temperature Coefficient (NTC) regions, is captured reasonably well by the JI-D_ad1 surrogate. Figure 2. Comparisons of predicted ignition delay time of surrogate JI-D_ad1 under different conditions vs. experimental data of U.S#2 [8]. Droplet heating and evaporation JI-D_ad1 surrogate was used to predict the single droplet heating, evaporation and ignition process. The multi-component droplet evaporation model of [1, 9] was used for the transport phenomena modeling. Gas phase diffusion coefficients are predicted with method introduced in [10]. A 0.9 mm-diameter droplet at 1 atm ambient pressure was modeled and the results are compared with experimental data of [11]. Two different ambient temperature conditions of 623/823K are studied. As shown in Fig. 3, the droplet first undergoes a heating up period during which causes volume swelling and the density declines. After heating up period, the simulation result of JI-D_ad1 droplet well captures D- square law decay trend. The overall predictions of single JI-D_ad1 droplet match well with diesel droplet evaporation process. Mass variation of the four components in droplet heating and evaporation process at 823K was discussed below. The mass fraction of four components in droplet liquid-side interface is shown in Fig. 4. The lightest component 1, 2, 4-trimethybenzene decrease firstly followed with trans-decalin. The mass fraction of heptamethynonane first undergoes a slightly increase due to evaporation of other two light components and then decreases obviously. Finally, the mass fraction of the heaviest (least volatile) component n- hexadecane reaches 1. At vapor-side interface, 1, 2, 4- trimethybenzene first increase and then decrease versus time followed with trans-decalin and heptamethynonane as shown in Fig. 5. Only the heaviest component n- hexadecane left at the end of evaporation process. Fig. 6 gives the mass increase of four components in the environmental gas phase. At around 1.5s, light components 1, 2, 4-trimethybenzene and trans-decalin evaporate completely while two heavy component heptamethynonane and n-hexadecane get fully evaporated at around 3.25s. The temperature of droplet surface is

shown in Fig. 7 and gives 487K at the end of the heating and evaporation process. Figure 6. Mass increase of four components in the gas phase versus time. Figure 3. Normalized diameter of JI-D_ad1 droplet versus time during heating and evaporation compared with experimental data[11]. Figure 7. Temperature of droplet surface versus time Figure 4. Mass fraction of four components at droplet liquid-side interface versus time. Figure 5. Mass fraction of four components at droplet vapor-side interface versus time. Droplet ignition/combustion For droplet ignition process, a 0.7mm-diameter JI- D_ad1 droplet was modeled and compared with experimental data under constant 1 atm pressure and different temperature conditions [12]. A detailed chemical kinetics of 352 species with 13264 reactions [7] is used for chemical ignition prediction. A zero-dimension model [9] implemented with Cantera [6] was used for total ignition delay time simulation. Ignition delay includes both physical delay and chemical delay process. In Fig. 8, the physical delay time, chemical delay time and total ignition delay time is plot over different temperature. Both physical delay and chemical delay decreases with temperature obviously. For lower temperature environment condition (<950K), the slower chemical delay time plays a significant role in the total droplet ignition process. At higher temperature, the physical delay, including both heating and evaporation, contributes greatly to the total droplet ignition time. The overall ignition delay time predictions matches well with experimental data [12].

Figure 8. Total ignition delay of JI-D_ad1 droplet under p=1 atm and phi (equivalence ratio)=1.0 condition, experimental data of [12] Summary and conclusion In this study, a recently developed four-component unified surrogate fuel was utilized to study the heating, evaporation and ignition of a single diesel droplet within stagnant environment. The surrogate fuel is capable of mimic both physical and chemical aspects of the real diesel fuel. Distillation curve and physical properties including density, molecular weight, lower heating value, which are important for droplet heating and evaporation, are matched satisfactorily when validated with real diesel fuel property data. DCN, C/H ratio, as well ignition delay times are also shown to match closely to experimental data. Subsequent droplet heating, evaporation and ignition predictions using the discrete multicomponent evaporation model of [9] also show good comparison with available experimental data. The current single drop ignition study would pave the way for this unified surrogate fuel to be used for more complete multi-dimensional spray combustion simulation studies. optical diagnostic data for multi-mode combustion in a heavy-duty DI diesel engine, SAE technical paper Report No. 0148-7191. 4. Abianeh, O. S., Chen, C. P., and Cerro, R. L., Industrial & Engineering Chemistry Research 51:12435-12448 (2012). 5. Kim, D., Martz, J., and Violi, A., Combustion and Flame 161:1489-1498 (2014). 6. David GG, Harry KM, Raymond LS. Cantera: An object- oriented software toolkit for chemical kinetics, thermodynamics, and transport processes. Available from: http://www.cantera.org 2015. Version 2.1.2. 7. Primary Reference Fuels (PRF) + PAH + Real Fuels, Version 1412; The CRECK Modeling Group, Milano, Italy, December 2014; http://creckmodeling.chem.polimi.it/index.php/men u-kinetics/menu-kinetics-detailedmechanisms/menu-kinetics-prf-pah-real-fuelsmechanism. Accessed Nov.1, 2016. 8. Kukkadapu, G., and Sung, C. J., Combustion and Flame 166:45-54 (2016). 9. Abianeh, O. S. and Chen, C. P., International Journal of Heat and Mass Transfer 55:6897-6907 (2012) 10. Fuller, E. N., Schettler, P. D., and Giddings, J. C., Industrial and Engineering Chemistry 58:18-27 (1966). 11. Ma, X. K., Zhang, F. J., Han, K., Yang, B., and Song, G. Q., Fuel 160: 43-49 (2015). 12. Barman, J., Gakkhar, R. P., Kumar, V., Kumar, V., Gakkhar, S., International Journal of Oil, Gas and Coal Technology 1:464-477 (2008).. Acknowledgement The authors acknowledge the financial support from the subsection of the third round 985 project through the University of Michigan-Shanghai Jiao Tong University Joint Institute. References 1. Chen, X., Khani, E., and Chen, C. P., Fuel 182: 284-291 (2016). 2. Mueller, C. J., Cannella, W. J., Bruno, T. J., Bunting, B., Dettman, H., Franz, J., Huber, M. L., Natarajan, M., Pitz, W. J., Ratcliff, M. A., and Wright, K., Energy and Fuels 26:3284 3303 (2012). 3. Singh, S., Reitz, R. D., and Musculus, M.P., Comparison of the characteristic time (CTC), representative interactive flamelet (RIF), and direct integration with detailed chemistry combustion models against