Impact of Kinetic Uncertainties on Accurate Prediction of NO Concentrations in Premixed Alkane-Air Flames

References

• Abian, M., Alzueta, M.U., and Glarborg, P. 2015. Formation of NO from N2/O2 mixtures in a flow reactor: toward an accurate prediction of thermal NO. Int J Chem Kinet, 47(8), 518–532. doi: 10.1002/kin.20929
   Web of Science ®Google Scholar
• Adams, B., Bauman, L., Bohnhoff, W., Dalbey, K., Ebeida, M., Eddy, J., Eldred, M., Hough, P., Hu, K., Jakeman, J., Stephens, J., Swiler, L., Vigil, D., and Wildey, T. 2015. Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.0 User’s Manual, Technical report, Sandia Technical Report SAND2014-4633.
   Google Scholar
• Askey, R., and Wilson, J. 1985. Some Basic Hypergeometric Orthogonal Polynomials that Generalize Jacobi Polynomials, American Mathematical Society, Providence.
   Google Scholar
• Baulch, D., Cobos, C., Cox, R., Esser, C., Frank, P., Just, T., Kerr, J., Pilling, M., Troe, J., Walker, R., and Warnatz, J. 1992. Evaluated kinetic data for combustion modelling. J Phys Chem Ref Data, 21(3), 411–734. doi: 10.1063/1.555908
   Web of Science ®Google Scholar
• Baulch, D.L. 2005. Evaluated kinetic data for combustion modeling: supplement II. J Phys Chem Ref Data, 34(3), 757–1397. doi: 10.1063/1.1748524
   Web of Science ®Google Scholar
• Bessler, W.G., Schulz, C., Sick, V., and Daily, J.W. (2003), A versatile modeling tool for nitric oxide LIF spectra. In Proceedings of the Third Joint Meeting of the US Sections of The Combustion Institute, p. P105.
   Google Scholar
• Correa, S.M. 1993. A review of NOx formation under gas-turbine combustion conditions. Combust Sci Technol, 87(1–6), 329–362. doi: 10.1080/00102209208947221
   Web of Science ®Google Scholar
• Davis, M.J., Liu, W., and Sivaramakrishnan, R. 2017. Global sensitivity analysis with small sample sizes: ordinary least squares approach. J Phys Chem A, 121(3), 553–570. doi: 10.1021/acs.jpca.6b09310
   PubMed Web of Science ®Google Scholar
• Faßheber, N., Dammeier, J., and Friedrichs, G. 2014. Direct measurements of the total rate constant of the reaction NCN+H and implications for the product branching ratio and the enthalpy of formation of NCN. Phys Chem Chem Phys, 16(23), 11647–11657. doi: 10.1039/C4CP01107D
   PubMed Web of Science ®Google Scholar
• Frenklach, M., Wang, H., and Rabinowitz, M.J. 1992. Optimization and analysis of large chemical kinetic mechanisms using the solution mapping method-combustion of methane. ‎Prog Energ Combust, 18(1), 47–73. doi: 10.1016/0360-1285(92)90032-V
   Web of Science ®Google Scholar
• Glarborg, P., Miller, J.A., Ruscic, B., and Klippenstein, S.J. 2018. Modeling nitrogen chemistry in combustion. ‎Prog Energ Combust, 67, 31–68. doi: 10.1016/j.pecs.2018.01.002
   Web of Science ®Google Scholar
• Göke, S., Schimek, S., Terhaar, S., Reichel, T., Göckeler, K., Krüger, O., Fleck, J., Griebel, P., and Paschereit, C.O. 2014. Influence of pressure and steam dilution on NOx and CO emissions in a premixed natural gas flame. J Eng Gas Turb Power, 136(9), 091508. doi: 10.1115/1.4026942
   Web of Science ®Google Scholar
• Goodwin, D., Moffat, H., and Speth, R. 2016. Cantera: an object-oriented software toolkit for chemical kinetics, thermodynamics, and transport processes. http://www.cantera.org.
   Google Scholar
• Grcar, J.F., Day, M.S., and Bell, J.B. 2006. A taxonomy of integral reaction path analysis. Combust Theor Model, 10(4), 559–579. doi: 10.1080/13647830600551917
   Web of Science ®Google Scholar
• Guo, H., Smallwood, G.J., Liu, F., Ju, Y., and Gülder, Ö.L. 2005. The effect of hydrogen addition on flammability limit and NOx emission in ultra-lean counterflow CH4/air premixed flames. Proc Combust Inst, 30(1), 303–311. doi: 10.1016/j.proci.2004.08.177
   Google Scholar
• Lamoureux, N., El Merhubi, H., Pillier, L., de Persis, S., and Desgroux, P. 2016. Modeling of NO formation in low pressure premixed flames. Combust Flame, 163, 557–575. doi: 10.1016/j.combustflame.2015.11.007
   Web of Science ®Google Scholar
• Lieuwen, T., Chang, M., and Amato, A. 2013. Stationary gas turbine combustion: technology needs and policy considerations. Combust Flame, 160(8), 1311–1314. doi: 10.1016/j.combustflame.2013.05.001
   Web of Science ®Google Scholar
• Lipardi, A.C., Versailles, P., Watson, G.M., Bourque, G., and Bergthorson, J.M. 2017. Experimental and numerical study on NOx formation in CH4-air mixtures diluted with exhaust gas components. Combust Flame, 179, 325–337. doi: 10.1016/j.combustflame.2017.02.009
   Web of Science ®Google Scholar
• Miller, J.A., and Bowman, C.T. 1989. Mechanism and modeling of nitrogen chemistry in combustion. ‎Prog Energ Combust, 15(4), 287–338. doi: 10.1016/0360-1285(89)90017-8
   Web of Science ®Google Scholar
• Moskaleva, L., and Lin, M. 2000. The spin-conserved reaction CH + N2 → H + NCN: A major pathway to prompt NO studied by quantum/statistical theory calculations and kinetic modeling of rate constant. Proc Combust Inst, 28(2), 2393–2401. doi: 10.1016/S0082-0784(00)80652-9
   Google Scholar
• Prager, J., Najm, H.N., Sargsyan, K., Safta, C., and Pitz, W.J. 2013. Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters. Combust Flame, 160(9), 1583–1593. doi: 10.1016/j.combustflame.2013.01.008
   Web of Science ®Google Scholar
• Reagan, M.T., Najm, H., Pebay, P., Knio, O., and Ghanem, R. 2005. Quantifying uncertainty in chemical systems modeling. Int J Chem Kinet, 37(6), 368–382. doi: 10.1002/kin.20081
   Web of Science ®Google Scholar
• Rokke, P.E., Hustad, J.E., Rokke, N.A., and Svendsgaard, O.B. (2003), Technology update on gas turbine dual fuel, dry low emission combustion systems. In Proceedings of ASME Turbo Expo, American Society of Mechanical Engineers, pp. GT2003–38112. doi: 10.1115/GT2003-38112
   Google Scholar
• Schofield, K. 2012. Large scale chemical kinetic models of fossil fuel combustion: adequate as engineering models - No More, No Less. Energ Fuel, 26(9), 5468–5480. doi: 10.1021/ef300858s
   Web of Science ®Google Scholar
• Sheen, D.A., and Wang, H. 2011. The method of uncertainty quantification and minimization using polynomial chaos expansions. Combust Flame, 158(12), 2358–2374. doi: 10.1016/j.combustflame.2011.05.010
   Web of Science ®Google Scholar
• Slavinskaya, N.A., Abbasi, M., Starcke, J.H., Whitside, R., Mirzayeva, A., Riedel, U., Li, W., Oreluk, J., Hegde, A., Packard, A., Frenklach, M., Gerasimov, G., and Shatalov, O. 2017. Development of an uncertainty quantification predictive chemical reaction model for syngas combustion. Energ Fuel, 31(3), 2274–2297. doi: 10.1021/acs.energyfuels.6b02319
   Web of Science ®Google Scholar
• Smith, G.P., Golden, D.M., Frenklach, M., Moriarty, N.W., Eiteneer, B., Goldenberg, M., Bowman, C.T., Hanson, R.K., Song, S., Gardiner, W.C.J., Lissianski, V.V., and Qin, Z. (1999), ‘GRI-Mech 3.0ʹ, http://www.me.berkeley.edu/gri_mech/.
   Google Scholar
• Smith, R.C. 2013. Uncertainty Quantification: Theory, Implementation, and Applications, Computational Science and Engineering, SIAM, Philadelphia.
   Google Scholar
• Smolyak, S.A. (1963), Quadrature and interpolation formulas for tensor products of certain classes of functions. In Doklady Akademii Nauk, Vol. 148, Russian Academy of Sciences, pp. 1042–1045.
   Google Scholar
• Tomlin, A.S. 2006. The use of global uncertainty methods for the evaluation of combustion mechanisms. Reliab Eng Syst Saf, 91, 1219–1231. doi: 10.1016/j.ress.2005.11.026
   Web of Science ®Google Scholar
• Tsang, W., and Hampson, R.F. 1986. Chemical kinetic data base for combustion chemistry. Part I. methane and related compounds. J Phys Chem Ref Data, 15(3), 1087–1279. doi: 10.1063/1.555759
   Web of Science ®Google Scholar
• Turányi, T., and Tomlin, A.S. 2016. Analysis of Kinetic Reaction Mechanisms, Springer, Berlin. doi: 10.1007/978-3-662-44562-4
   Google Scholar
• University of California at San Diego. 2005. Chemical-Kinetic Mechanisms for Combustion Applications. San Diego Mechanism web page. Mechanical and Aerospace Engineering (Combustion Research). http://combustion.ucsd.edu
   Google Scholar
• University of California at San Diego. 2016. Chemical-Kinetic Mechanisms for Combustion Applications. San Diego Mechanism web page. Mechanical and Aerospace Engineering (Combustion Research). http://combustion.ucsd.edu
   Google Scholar
• Versailles, P. 2017a. CH Formation in Premixed Flames of C1–C4 Alkanes: Assessment of Current Chemical Modelling Capability against Experiments, PhD thesis, McGill University.
   Google Scholar
• Versailles, P., Durocher, A., Bourque, G., and Bergthorson, J.M. (2018), Nitric oxide formation in lean, methane-air stagnation flames at supra-atmospheric pressures. Proc Combust Inst, 37(1), 711–718. doi: 10.1016/j.proci.2018.05.060
   Google Scholar
• Versailles, P., Watson, G.M.G., Durocher, A., Bourque, G., and Bergthorson, J.M. 2017b. Thermochemical mechanism optimization for accurate predictions of CH concentrations in premixed flames of C1-C3 alkane fuels. J Eng Gas Turb Power. doi: 10.1115/1.4038416
   Web of Science ®Google Scholar
• Versailles, P., Watson, G.M.G., Lipardi, A.C.A., and Bergthorson, J.M. 2016. Quantitative CH measurements in atmospheric-pressure, premixed flames of C1-C4 alkanes. Combust Flame, 165, 109–124. doi: 10.1016/j.combustflame.2015.11.001
   Web of Science ®Google Scholar
• Wang, H., and Sheen, D.A. 2015. Combustion kinetic model uncertainty quantification, propagation and minimization. ‎Prog Energ Combust, 47, 1–31. doi: 10.1016/j.pecs.2014.10.002
   Web of Science ®Google Scholar
• Watson, G.M.G., Versailles, P., and Bergthorson, J.M. 2016. NO formation in premixed flames of C1-C3 alkanes and alcohols. Combust Flame, 169, 242–260. doi: 10.1016/j.combustflame.2016.04.015
   Web of Science ®Google Scholar
• Watson, G.M.G., Versailles, P., and Bergthorson, J.M. 2017. NO formation in rich premixed flames of C1-C4 alkanes and alcohols. Proc Combust Inst, 36(1), 627–635. doi: 10.1016/j.proci.2016.06.108
   Web of Science ®Google Scholar
• Wiener, N. 1938. The Homogeneous Chaos. Am J Math, 60(4), 897–936. doi: 10.2307/2371268
   Google Scholar
• Winokur, J., Kim, D., Bisetti, F., Le Maître, O.P., and Knio, O.M. 2016. Sparse pseudo spectral projection methods with directional adaptation for uncertainty quantification. J Sci Comput, 68(2), 596–623. doi: 10.1007/s10915-015-0153-x
   Web of Science ®Google Scholar
• Xiu, D. 2010. Numerical Methods for Stochastic Computations: A Spectral Method Approach, Princeton university press, Princeton.
   Google Scholar
• Zádor, J., Zsély, I.G., Turányi, T., Ratto, M., Tarantola, S., and Saltelli, A. 2005. Local and global uncertainty analyses of a methane flame model. J Phys Chem A, 109(43), 9795–9807. doi: 10.1021/jp053270i
   PubMed Web of Science ®Google Scholar
• Zhang, Y., Mathieu, O., Petersen, E.L., Bourque, G., and Curran, H.J. 2017. Assessing the predictions of a NOx kinetic mechanism on recent hydrogen and syngas experimental data. Combust Flame, 182, 122–141. doi: 10.1016/j.combustflame.2017.03.019
   Web of Science ®Google Scholar
• Zhou, C.-W., Li, Y., O’Connor, E., Somers, K.P., Thion, S., Keesee, C., Mathieu, O., Petersen, E.L., DeVerter, T.A., Oehlschlaeger, M.A., et al. 2016. A comprehensive experimental and modeling study of isobutene oxidation. Combust Flame, 167, 353–379. doi: 10.1016/j.combustflame.2016.01.021
   Web of Science ®Google Scholar
• Zsély, I.G., Zádor, J., and Turányi, T. 2008. Uncertainty analysis of NO production during methane combustion. Int J Chem Kinet, 40(11), 754–768. doi: 10.1002/kin.20373
   Web of Science ®Google Scholar