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Applicability of high dimensional model representation correlations for ignition delay times of n-heptane/air mixtures

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Abstract

It is difficult to predict the ignition delay times for fuels with the two-stage ignition tendency because of the existence of the nonlinear negative temperature coefficient (NTC) phenomenon at low temperature regimes. In this paper, the random sampling-high dimensional model representation (RS-HDMR) methods were employed to predict the ignition delay times of n-heptane/air mixtures, which exhibits the NTC phenomenon, over a range of initial conditions. A detailed n-heptane chemical mechanism was used to calculate the fuel ignition delay times in the adiabatic constant-pressure system, and two HDMR correlations, the global correlation and the stepwise correlations, were then constructed. Besides, the ignition delay times predicted by both types of correlations were validated against those calculated using the detailed chemical mechanism. The results showed that both correlations had a satisfactory prediction accuracy in general for the ignition delay times of the n-heptane/air mixtures and the stepwise correlations exhibited a better performance than the global correlation in each subdomain. Therefore, it is concluded that HDMR correlations are capable of predicting the ignition delay times for fuels with two-stage ignition behaviors at low-to-intermediate temperature conditions.

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References

  1. Huang Z, Li Z, Zhang J Y, et al. Active fuel design–a way to manage the right fuel for HCCI engines. Frontiers in Energy, 2016, 10(1): 14–28

    Article  Google Scholar 

  2. Han D, Ickes A M, Bohac S V, et al. HC and CO emissions of premixed low-temperature combustion fueled by blends of diesel and gasoline. Fuel, 2012, 99(9): 13–19

    Article  Google Scholar 

  3. Benajes J, Molina S, García A, et al. Performance and engine-out emissions evaluation of the double injection strategy applied to the gasoline partially premixed compression ignition spark assisted combustion concept. Applied Energy, 2014, 134(C): 90–101

    Article  Google Scholar 

  4. Benajes J, García A, Domenech V, et al. An investigation of partially premixed compression ignition combustion using gasoline and spark assistance. Applied Thermal Engineering, 2013, 52(2): 468–477

    Article  Google Scholar 

  5. Benajes J, Molina S, García A, et al. Effects of low reactivity fuel characteristics and blending ratio on low load RCCI (reactivity controlled compression ignition) performance and emissions in a heavy-duty diesel engine. Energy, 2015, 90: 1261–1271

    Article  Google Scholar 

  6. Paykani A, Kakaee A H, Rahnama P, et al. Effects of diesel injection strategy on natural gas/diesel reactivity controlled compression ignition combustion. Energy, 2015, 90(1): 814–826

    Article  Google Scholar 

  7. Yang Y, Dec J E, Sjöberg M, et al. Understanding fuel anti-knock performances in modern SI engines using fundamental HCCI experiments. Combustion and Flame, 2015, 162(10): 4008–4015

    Article  Google Scholar 

  8. Han D, Lü X, Ma J J, et al. Influence of fuel supply timing and mixture preparation on the characteristics of stratified charge compression ignition combustion with n-heptane fuel. Combustion Science and Technology, 2009, 181(11): 1327–1344

    Article  Google Scholar 

  9. Sadabadi K K, Shahbakhti M, Bharath A N, et al. Modeling of combustion phasing of a reactivity-controlled compression ignition engine for control applications. International Journal of Engine Research, 2016, 17(4): 421–435

    Article  Google Scholar 

  10. Fatouraie M, Karwat DMA,WooldridgeMS. A numerical study of the effects of primary reference fuel chemical kinetics on ignition and heat release under homogeneous reciprocating engine conditions. Combustion and Flame, 2016, 163: 79–89

    Article  Google Scholar 

  11. Kéromnès A, MetcalfeWK, Heufer K A, et al. An experimental and detailed chemical kinetic modeling study of hydrogen and syngas mixture oxidation at elevated pressures. Combustion and Flame, 2013, 160(6): 995–1011

    Article  Google Scholar 

  12. Han D, Guang H, Yang Z, et al. Effects of equivalence ratio and carbon dioxide concentration on premixed charge compression ignition of gasoline and diesel-like fuel blends. Journal of Mechanical Science and Technology, 2013, 27(8): 2507–2512

    Article  Google Scholar 

  13. Wang Y, Yang Z, Yang X, et al. Experimental and modeling studies on ignition delay times of methyl hexanoate/n-butanol blend fuels at elevated pressures. Energy & Fuels, 2014, 28(8): 5515–5522

    Article  Google Scholar 

  14. Burke U, Somers K P, O’Toole P, et al. An ignition delay and kinetic modeling study of methane, dimethyl ether, and their mixtures at high pressures. Combustion and Flame, 2015, 162(2): 315–330

    Article  Google Scholar 

  15. Kooshkbaghi M, Frouzakis C E, Boulouchos K. n-Heptane/air combustion in perfectly stirred reactors: dynamics, bifurcations and dominant reactions at critical conditions. Combustion and Flame, 2015, 162(9): 3166–3179

    Article  Google Scholar 

  16. Burle S M, Metcalfe W, Herbinet O, et al. An experimental and modeling study of propene oxidation. Part 1: Speciation measurements in jet-stirred and flow reactors. Combustion and Flame, 2014, 161(11): 2765–2784

    Google Scholar 

  17. Sirjean B, Fournet R, Glaude P A, et al. A shock tube and chemical kinetic modeling study of the oxidation of 2,5-Dimethylfuran. Journal of Physical Chemistry A, 2013, 117(7): 1371–1392

    Article  Google Scholar 

  18. Chen Z, Zhang P, Yang Y, et al. Impact of nitric oxide (NO) on n-heptane autoignition in a rapid compression machine. Combustion and Flame, 2017, 186: 94–104

    Article  Google Scholar 

  19. Livengood J C, Wu P C. Correlation of autoignition phenomena in internal combustion engines and rapid compression machines. International Symposium on Combustion, 1955, 5(1): 347–356

    Article  Google Scholar 

  20. Tao M, Han D, Zhao P. An alternative approach to accommodate detailed ignition chemistry in combustion simulation. Combustion and Flame, 2017, 176: 400–408

    Article  Google Scholar 

  21. Donato N S, Petersen E L. Simplified correlation models for CO/H2 chemical reaction times. International Journal of Hydrogen Energy, 2008, 33(24): 7565–7579

    Article  Google Scholar 

  22. Zhou A, Dong T, Akih-Kumgeh B. Simplifying ignition delay prediction for homogeneous charge compression ignition engine design and control. International Journal of Engine Research, 2016, 17(9): 957–968

    Article  Google Scholar 

  23. Li G, Rosenthal C, Rabitz H. High dimensional model representations. Journal of Physical Chemistry A, 2001, 105(33): 7765–7777

    Article  Google Scholar 

  24. Zhao Z, Chen Z, Chen S. Correlations for the ignition delay times of hydrogen/air mixtures. Chinese Science Bulletin, 2011, 56(2): 215–221

    Article  Google Scholar 

  25. Zhao Z, Chen Z. HDMR correlations for the laminar burning velocity of premixed CH4/H2/O2/N2 mixtures. International Journal of Hydrogen Energy, 2012, 37(1): 691–697

    Article  Google Scholar 

  26. Guang H, Yang Z, Huang Z, et al. Experimental study of n-heptane ignition delay with carbon dioxide addition in a rapid compression machine under low-temperature conditions. Chinese Science Bulletin, 2012, 57(30): 3953–3960

    Article  Google Scholar 

  27. Li R, Liu Z, Han Y, et al. Experimental and kinetic modeling study of autoignition characteristics of n-heptane/ethanol by constant volume bomb and detail reaction mechanism. Energy & Fuels, 2017, 31(12): 13610–13626

    Article  Google Scholar 

  28. Dagaut P, Reuillon M, Cathonnet M. Experimental study of the oxidation of n-heptane in a jet stirred reactor from low to high temperature and pressures up to 40 atm. Combustion and Flame, 1995, 101(1–2): 132–140

    Article  Google Scholar 

  29. Shorter J A, Ip P C, Rabitz H A. An efficient chemical kinetics solver using high dimensional model representation. Journal of Physical Chemistry A, 1999, 103(36): 7192–7198

    Article  Google Scholar 

  30. Li G, Rabitz H. Ratio control variate method for efficiently determining high-dimensional model representations. Journal of Computational Chemistry, 2006, 27(10): 1112–1118

    Article  Google Scholar 

  31. Feng X J, Hooshangi S, Chen D, et al. Optimizing genetic circuits by global sensitivity analysis. Biophysical Journal, 2004, 87(4): 2195–2202

    Article  Google Scholar 

  32. Ziehn T, Tomlin A S. Global sensitivity analysis of a 3D street canyon model-Part I: The development of high dimensional model representations. Atmospheric Environment, 2008, 42(8): 1857–1873

    Article  Google Scholar 

  33. Li G, Wang S, Rabitz H. Practical approaches to construct RSHDMR component functions. Journal of Physical Chemistry A, 2002, 106(37): 8721–8733

    Article  Google Scholar 

  34. Liu Y, Yousuff Hussaini M, Ökten G. Accurate construction of high dimensional model representation with applications to uncertainty quantification. Reliability Engineering & System Safety, 2016, 152: 281–295

    Article  Google Scholar 

  35. Li G, Rabitz H, Wang S W, et al. Correlation method for variance reduction of Monte Carlo integration in RS-HDMR. Journal of Computational Chemistry, 2003, 24(3): 277–283

    Article  Google Scholar 

  36. Li G, Hu J, Wang S W, et al. Random sampling-high dimensional model representation (RS-HDMR) and orthogonality of its different order component functions. Journal of Physical Chemistry A, 2006, 110(7): 2474–2485

    Article  Google Scholar 

  37. Li G, Rabitz H, Hu J, et al. Regularized random-sampling high dimensional model representation (RS-HDMR). Journal of Mathematical Chemistry, 2008, 43(3): 1207–1232

    Article  MathSciNet  MATH  Google Scholar 

  38. Kee R J, Rupley F M, Miller J A. Sandia laboratories report 1989. Sandia National Laboratories, Albuquerque, NM, USA, 1989

    Google Scholar 

  39. Curran H J, Gaffuri P, Pitz W J, et al. A comprehensive modeling study of n-heptane oxidation. Combustion and Flame, 1998, 114(1–2): 149–177

    Article  Google Scholar 

  40. Mehl M, Pitz W J, Westbrook C K, et al. Kinetic modeling of gasoline surrogate components and mixtures under engine conditions. Proceedings of the Combustion Institute, 2011, 33(1): 193–200

    Article  Google Scholar 

  41. Mehl M, Pitz W, Sjöberg M, et al. Detailed kinetic modeling of low-temperature heat release for PRF fuels in an HCCI engine. SAE Technical Paper 2009–01–1806, 2009

    Google Scholar 

  42. Hall JM, RickardMJ A, Petersen E L. Comparison of characteristic time diagnostics for ignition and oxidation of fuel/oxidizer mixtures behind reflected shock waves. Combustion Science and Technology, 2005, 177(3): 455–483

    Article  Google Scholar 

  43. Law C. Combustion Physics. Cambridge: Cambridge University Press, 2006

    Book  Google Scholar 

  44. Zhang K, Banyon C, Bugler J, et al. An updated experimental and kinetic modeling study of n-heptane oxidation. Combustion and Flame, 2016, 172: 116–135

    Article  Google Scholar 

  45. Ciezki H K, Adomeit G. Shock-tube investigation of selfignition of n-heptane-air mixtures under engine relevant conditions. Combustion and Flame, 1993, 93(4): 421–433

    Article  Google Scholar 

  46. Heufer K A, Olivier H. Determination of ignition delay times of different hydrocarbons in a new high pressure shock tube. Shock Waves, 2010, 20(4): 307–316

    Article  MATH  Google Scholar 

  47. Zeuch T, Moréac G, Ahmed S S, et al. A comprehensive skeletal mechanism for the oxidation of n-heptane generated by chemistry-guided reduction. Combustion and Flame, 2008, 155(4): 651–674

    Article  Google Scholar 

  48. Peters N, Paczko G, Seiser R, et al. Temperature cross-over and nonthermal runaway at two-stage ignition of n-heptane. Combustion and Flame, 2002, 128(1–2): 38–49

    Article  Google Scholar 

  49. Herzler J, Jerig L, Roth P. Shock tube study of the ignition of lean nheptane/air mixtures at intermediate temperatures and high pressures. Proceedings of the Combustion Institute, 2005, 30(1): 1147–1153

    Article  Google Scholar 

  50. Maroteaux F, Noel L. Development of a reduced n-heptane oxidation mechanism for HCCI combustion modeling. Combustion and Flame, 2006, 146(1–2): 246–267

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 51776124).

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Authors and Affiliations

  1. Key Laboratory of Power Machinery and Engineering of the Ministry of Education, Shanghai Jiao Tong University, Shanghai, 200240, China

    Wang Liu, Jiabo Zhang, Zhen Huang & Dong Han

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  1. Wang Liu
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  2. Jiabo Zhang
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  4. Dong Han
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Correspondence to Dong Han.

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Liu, W., Zhang, J., Huang, Z. et al. Applicability of high dimensional model representation correlations for ignition delay times of n-heptane/air mixtures. Front. Energy 13, 367–376 (2019). https://doi.org/10.1007/s11708-018-0584-9

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  • DOI: https://doi.org/10.1007/s11708-018-0584-9

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