Citation: XI Shuanghui, WANG Fan, LI Xiangyuan. First- and Second-Order Local and Global Sensitivity Analyses on Ignition Delay Times of Four Typical Fuels[J]. Acta Physico-Chimica Sinica, ;2019, 35(2): 167-181. doi: 10.3866/PKU.WHXB201803022 shu

First- and Second-Order Local and Global Sensitivity Analyses on Ignition Delay Times of Four Typical Fuels

  • Corresponding author: WANG Fan, wangf44@gmail.com
  • Received Date: 18 December 2017
    Revised Date: 19 January 2018
    Accepted Date: 1 February 2018
    Available Online: 2 February 2018

    Fund Project: the National Natural Science Foundation of China 21773160the National Natural Science Foundation of China 21473116the National Key R & D Program of China 2017YFB0202400the National Key R & D Program of China 2017YFB0202401The project was supported by the National Key R & D Program of China (2017YFB0202400, 2017YFB0202401) and the National Natural Science Foundation of China (21473116, 21773160)

  • Sensitivity analysis is an important tool in model validation and evaluation that has been employed extensively in the analysis of chemical kinetic models of combustion processes. The input parameters of a chemical kinetic model are always associated with some uncertainties, and the effects of these uncertainties on the predicted combustion properties can be determined through sensitivity analysis. In this work, first- and second-order global and local sensitivity coefficients of ignition delay time with respect to the scaling factor for reaction rate constants in chemical kinetic mechanisms for combustion of H2, methane, n-butane, and n-heptane are examined. In the sensitivity analysis performed here, the output of the model is taken to be natural logarithm of ignition delay time and the input parameters are the natural logarithms of the factors that scale the reaction rate constants. The output of the model is expressed as a polynomial function of the input parameters, with up to coupling between two input parameters in the present sensitivity analysis. This polynomial function is determined by varying one or two input parameters, and allows the determination of both local and global sensitivity coefficients. The order of the polynomial function in the present work is four, and the factor that scales the reaction rate constant is in the range from 1/e to e, where e is the base of the natural logarithm. A relatively small number of sample runs are required in this approach compared to the global sensitivity analysis based on the highly dimensional model representation method, which utilizes random sampling of input (RS-HDMR). In RS-HDMR, sensitivity coefficients are determined only for the rate constants of a limited number of reactions; the present approach, by contrast, affords sensitivity coefficients for a larger number of reactions. Reactions and reaction pairs with the largest sensitivity coefficients are listed for ignition delay times of four typical fuels. Global sensitivity coefficients are always positive, while local sensitivity coefficients can be either positive or negative. A negative local sensitivity coefficient indicates that the reaction promotes ignition, while a positive local sensitivity coefficient suggests that the reaction actually suppresses ignition. Our results show that important reactions or reaction pairs identified by global sensitivity analysis are usually rather similar to those based on local sensitivity analysis. This finding can probably be attributed to the fact that the values of input parameters are within a rather small range in the sensitivity analysis, and nonlinear effects for such a small range of parameters are negligible. It is possible to determine global sensitivity coefficients by varying the input parameters over a larger range using the present approach. Such analysis shows that correlation effects between an important reaction and a minor reaction can have relatively sizable second-order sensitivity coefficient in some cases. On the other hand, first-order global sensitivity coefficients in the present approach will be affected by coupling between two reactions, and some results of the first-order global sensitivity analysis will be different from those determined by local sensitivity analysis or global sensitivity analysis under conditions where the correlation effects of two reactions are neglected. The present sensitivity analysis approach provides valuable information on important reactions as well as correlated effects of two reactions on the combustion characteristics of a chemical kinetic mechanism. In addition, the analysis can also be employed to aid global sensitivity analysis using RS-HDMR, where global sensitivity coefficients are determined more reliably.
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    1. [1]

      Tomlin, A. S.; Turányi, T. Cleaner Combust. Green Energy Technol. 2013, 411. doi: 10.1007/978-1-4471-5307-8_16  doi: 10.1007/978-1-4471-5307-8_16

    2. [2]

      Turányi, T. ; Tomlin, A. S. Analysis of Kinetic Reaction Mechanisms; Springer-Verlag: Berlin Heidelberg, German; 2014.

    3. [3]

      Tomlin, A. S. Proc. Combust. Inst. 2013, 34, 159. doi: 10.1016/j.proci.2012.07.043  doi: 10.1016/j.proci.2012.07.043

    4. [4]

      Saltelli, A.; Ratto, M.; Tarantola, S.; Campolongo, F. Chem. Rev. 2005, 105, 2811. doi: 10.1021/cr040659d  doi: 10.1021/cr040659d

    5. [5]

      Zádor, J.; Zsély, I. G.; Turányi, T. Reliab. Eng. Syst. Saf. 2006, 91, 1232. doi: 10.1016/j.ress.2005.11.020  doi: 10.1016/j.ress.2005.11.020

    6. [6]

      Wang, H.; Sheen, D. A. Prog. Energy Combust. Sci. 2015, 47, 1. doi: 10.1016/j.pecs.2014.10.002  doi: 10.1016/j.pecs.2014.10.002

    7. [7]

      Skodje, R.T.; Tomlin, A. S.; Klippenstein, S. J.; Harding, L. B.; Davis, M. J. J. Phys. Chem. A 2010, 114, 8286. doi: 10.1021/jp1047002  doi: 10.1021/jp1047002

    8. [8]

      Saltelli, A. ; Tarantola, S. ; Campolongo, F. ; Ratto, M. Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models; John Wiley & Sons Ltd. : Chichester, UK; 2004.

    9. [9]

      Saltelli, A.; Ratto, M.; Tarantola, S.; Campolongo, F.; Commission, E. Relia. Eng. Syst. Saf. 2006, 91 (10-11), 1109. doi: 10.1016/j.ress.2005.11.014  doi: 10.1016/j.ress.2005.11.014

    10. [10]

      Saltelli, A. ; Ratto, M. ; Andres T. ; Campolongo, F. ; Cariboni, J. ; Gatelli, D. ; Sasana, M. ; Tarantola, S. Global Sensitivity Analisis: The Primer; John Wiley & Sons: Hoboken, NJ, USA; 2008.

    11. [11]

      Najm, H. N. Annu. Rev. Fluid Mech. 2009, 41, 35. doi: 10.1146/annurev.fluid.010908.165248  doi: 10.1146/annurev.fluid.010908.165248

    12. [12]

      Sobol, I. M. Modelirovanie 1990, 2, 112. doi: 10.1016/S0378-4754(00)00270-6  doi: 10.1016/S0378-4754(00)00270-6

    13. [13]

      Zsély, I. G.; Zádor, J.; Turányi, T. Reliab. Eng. Syst. Saf. 1997, 57, 41. doi: 10.1002/kin.20373  doi: 10.1002/kin.20373

    14. [14]

      Turányi, T. ; Rabitz, H. ; Saltelli, A. ; Chan, K. ; Scott, E. M. Sensitivity Analysis; Wiley: Chichester, UK; 2000.

    15. [15]

      McKay, M. D. Reliab. Eng. Syst. Saf. 1997, 57, 267. doi: 10.1016/S0951-8320(97)00039-2  doi: 10.1016/S0951-8320(97)00039-2

    16. [16]

      Xing, L.; Li, S.; Wang, Z.; Yang, B.; Klippenstein, S. J.; Zhang, F. Combust. Flame 2015, 162, 3427. doi: 10.1016/j.combustflame.2015.06.006  doi: 10.1016/j.combustflame.2015.06.006

    17. [17]

      Zheng, X. L.; Lu, T. F.; Law, C. K. Proc. Combust. Inst. 2007, 31, 367. doi: 10.1016/j.proci.2006.07.182  doi: 10.1016/j.proci.2006.07.182

    18. [18]

      Sankaran, R.; Hawkes, E. R.; Chen, J. H.; Lu, T. F.; Law, C. K. Proc. Combust. Inst. 2007, 31, 1291. doi: 10.1016/j.proci.2006.08.025  doi: 10.1016/j.proci.2006.08.025

    19. [19]

      Luo, Z.; Plomer, M.; Lu, T. F.; Som, S.; Longman, D. E.; Sarathy, S. M.; Pitz, W. J. Fuel 2012, 99, 143. doi: 10.1016/j.fuel.2012.04.028  doi: 10.1016/j.fuel.2012.04.028

    20. [20]

      Lu, T. F.; Law, C. K. Combust. Flame 2008, 154, 153. doi: 10.1016/j.combustflame.2007.11.013  doi: 10.1016/j.combustflame.2007.11.013

    21. [21]

      Niemeyer, K. E.; Sung, C. J. Combust. Flame 2014, 161, 2752. doi: 10.1016/j.combustflame.2014.05.001  doi: 10.1016/j.combustflame.2014.05.001

    22. [22]

      Niemeyer, K. E.; Sung, C. J.; Raju, M. P. Combust. Flame 2010, 157, 1760. doi: 10.1016/j.combustflame.2009.12.022  doi: 10.1016/j.combustflame.2009.12.022

    23. [23]

      Li, R.; Li, S. H.; Wang, F.; Li, X. Y. Combust. Flame 2016, 166, 55. doi: 10.1016/j.combustflame  doi: 10.1016/j.combustflame

    24. [24]

      SENKIN: A Fortran Program for Predicting Homogeneous Gas Phase Chemical Kinetics with Sensitivity Analysis. Available online: https: //www. osti. gov/biblio/5371815 (accessed on February 28, 2018).

    25. [25]

      Turányi, T. Tools Appl. J. Math. Chem. 1990, 5, 203. doi: 10.1007/BF01166355  doi: 10.1007/BF01166355

    26. [26]

      Ziehn, T.; Tomlin, A. S. Env. Model. Soft. 2009, 24, 775. doi: 10.1016/j.envsoft  doi: 10.1016/j.envsoft

    27. [27]

      Sobol, I. M. Math. Comp. Sim. 2001, 55, 271. doi: 10.1016/S0378-4754(00)00270-6  doi: 10.1016/S0378-4754(00)00270-6

    28. [28]

      Li, S.; Yang, B.; Qi, F. Combust. Flame 2016, 168, 53. doi: 10.1016/j.combustflame.2016.03.028  doi: 10.1016/j.combustflame.2016.03.028

    29. [29]

      Ziehn, T.; Hughes, K. J.; Griffiths, J. F.; Porter, R.; Tomlin, A. S. Combust. Theory Modell. 2009, 13, 589. doi: 10.1080/13647830902878398  doi: 10.1080/13647830902878398

    30. [30]

      Tomlin, A. S.; Ziehn, T. Lect. Notes Comput. Sci. Eng. 2010, 75, 9. doi: 10.1007/978-3-642-14941-2_2  doi: 10.1007/978-3-642-14941-2_2

    31. [31]

      Saltelli, A.; Annoni, P.; Azzini, I.; Campolongo, F.; Ratto, M.; Tarantola, S. Comput. Phys. Commun. 2010, 181, 259. doi:10.1016/j.cpc.2009.09.018  doi: 10.1016/j.cpc.2009.09.018

    32. [32]

      Davis, M. J.; Liu, W.; Sivaramakrishnan, R. J. Phys.Chem.A 2017, 121 (3), 553. doi: 10.1021/acs.jpca.6b09310  doi: 10.1021/acs.jpca.6b09310

    33. [33]

      Davis, M. J.; Skodje, R. T.; Tomlin, A. S. J. Phys. Chem. A 2011, 115, 1556. doi: 10.1021/jp108017t  doi: 10.1021/jp108017t

    34. [34]

      Ziehn, T.; Tomlin, A. S. Int. J. Chem. Kinet. 2008, 40, 742. doi: 10.1002/kin.20367  doi: 10.1002/kin.20367

    35. [35]

      Ziehn, T.; Tomlin, A. S. Atmos. Environ.2008, 42, 1857. doi: 10.1016/j.atmosenv.2007.11.018  doi: 10.1016/j.atmosenv.2007.11.018

    36. [36]

      Zhou, D. Y.; Davis, M. J.; Skodje, R. T. J. Phys. Chem. A 2013, 117, 3569. doi: 10.1021/jp312340q  doi: 10.1021/jp312340q

    37. [37]

      Rabitz, H.; Alis, Ö. F. J. Math. Chem. 1999, 25, 197. doi: 10.1023/A:1019188517934  doi: 10.1023/A:1019188517934

    38. [38]

      Wang, S. W.; Georgopoulos, P. G.; Li, G.; Rabitz, H. Lect. Notes Comput. Sci. 2001, 2179, 326. doi: 10.1007/3-540-45346-6_34  doi: 10.1007/3-540-45346-6_34

    39. [39]

      Brell, G.; Li, G.; Rabitz, H. J. Chem. Phys. 2010, 132, 174103. doi: 10.1063/1.3407440  doi: 10.1063/1.3407440

    40. [40]

      Alis, Ö. F.; Rabitz, H. J. Math. Chem. 2001, 29, 127. doi: 10.1023/A:1010979129659  doi: 10.1023/A:1010979129659

    41. [41]

      Li, G.; Wang, S. W.; Rabitz, H. J. Phys. Chem. A 2002, 106, 8721. doi: 10.1021/jp014567t  doi: 10.1021/jp014567t

    42. [42]

      Li, G.; Wang, S. W.; Rabitz, H.; Wang, S.; Jaffé, P. Chem. Eng. Sci. 2002, 57, 4445. doi: 10.1016/S0009-2509(02)00417-7  doi: 10.1016/S0009-2509(02)00417-7

    43. [43]

      Feng, X. J.; Hooshangi, S.; Chen, D.; Li, G.; Weiss, R.; Rabitz, H. Biophys. J. 2004, 87, 2195. doi: 10.1529/biophysj.104.044131  doi: 10.1529/biophysj.104.044131

    44. [44]

      Rabitz, H.; Alis, Ö. F.; Shorter, J.; Shim, K. Comput. Phys. Commun. 1999, 117, 11. doi: 10.1016/S0010-4655(98)00152-0  doi: 10.1016/S0010-4655(98)00152-0

    45. [45]

      Li, G.; Rabitz, H.; Wang, S. W.; Georgopoulos, P. G. J. Comput. Chem. 2003, 24, 277. doi: 10.1002/jcc.10172  doi: 10.1002/jcc.10172

    46. [46]

      Li, G.; Rabitz, H. J. Comput. Chem. 2006, 27, 1112. doi: 10.1002/jcc.20435  doi: 10.1002/jcc.20435

    47. [47]

      McKay, M. D. Reliab. Eng. Syst. Saf. 1997, 57, 267. doi: 10.1016/S0951-8320(97)00039-2  doi: 10.1016/S0951-8320(97)00039-2

    48. [48]

      O'Conaire, M.; Curran, H. J.; Simmie, J. M.; Pitz, W. J.; Westbrook, C. K. Intl. J. Chem. Kinet. 2004, 36 (11), 603. doi: 10.1002/kin.20036  doi: 10.1002/kin.20036

    49. [49]

      Konnov, A. A. Combust. Flame 2008, 152, 507. doi: 10.1016/j.combustflame.2007.10.024  doi: 10.1016/j.combustflame.2007.10.024

    50. [50]

      Wang, Q. D. Acta Phys. -Chim. Sin 2016, 32, 595.  doi: 10.3866/PKU.WHXB201512211

    51. [51]

      Lu, T. F.; Law, C. K. Combust. Inst. 2005, 30, 1333. doi: 10.1016/j.proci.2004.08.145  doi: 10.1016/j.proci.2004.08.145

    52. [52]

      Li, S. H.; Li, R.; Guo, J. J.; Tan, N. X.; Wang, F.; Li, X. Y. Acta Phys. -Chim. Sin. 2016, 32, 1623.  doi: 10.3866/PKU.WHXB201604084

    53. [53]

      Jiang, Y.; Qiu, R. Acta Phys. -Chim. Sin. 2009, 25, 1019.  doi: 10.3866/PKU.WHXB20090426

    54. [54]

      Pepiot-Desjardins, P.; Pitsch, H. Combust. Flame 2008, 154, 67. doi: 10.1016/j.combustflame.2007.10.020  doi: 10.1016/j.combustflame.2007.10.020

    55. [55]

      Luo, Z.; Lu, T. F.; Maciaszek, M. J.; Som, S.; Longman, D. E. Energy Fuels 2010, 24, 6283. doi: 10.1021/ef1012227  doi: 10.1021/ef1012227

    56. [56]

      Sun, W.; Chen, Z.; Gou, X.; Ju, Y. Combust. Flame 2010, 157, 1298. doi: 10.1016/j.combustflame.2010.03.006  doi: 10.1016/j.combustflame.2010.03.006

    57. [57]

      Liu, A. K.; Jiao, Y.; Li, S. H.; Wang, F.; Li, X. Y. Energy Fuels 2014, 28, 5426. doi: 10.1021/ef5002502  doi: 10.1021/ef5002502

    58. [58]

      Available online: http://c3.nuigalway.ie/butane.html (accessed on February 28, 2018).

    59. [59]

      Mehl, M.; Pitz, W. J.; Westbrook, C. K.; Curran, H. J. Proc. Combust. Inst. 2011, 33 (1), 193. doi: 10.1016/j.proci.2010.05.027  doi: 10.1016/j.proci.2010.05.027

    60. [60]

      Mehl, M.; Pitz, W. J.; Sjöberg, M.; Dec, J. E. SAE Tech. Paper. 2009, 1, 1806. doi: 10.4271/2009-01-180  doi: 10.4271/2009-01-180

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