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2023 , Vol. 63 >Issue 4: 505 - 520

DOI: https://doi.org/10.16511/j.cnki.qhdxxb.2023.25.026

综述

火焰面方法进展及在燃机燃烧室模拟中的挑战

  • 张归华 ,
  • 吴玉新 ,
  • 吴家豪 ,
  • 张扬 ,
  • 张海
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  • 清华大学 能源与动力工程系, 教育部热科学重点实验室, 北京 100084
张归华(1997-),男,博士研究生。

收稿日期: 2023-02-09

  网络出版日期: 2023-04-22

基金资助

国家科技重大专项资助项目(2019-I-0022-0021)

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State of the art and challenges of flamelet method in gas turbine combustor simulation

  • ZHANG Guihua ,
  • WU Yuxin ,
  • WU Jiahao ,
  • ZHANG Yang ,
  • ZHANG Hai
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  • Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China

Received date: 2023-02-09

  Online published: 2023-04-22

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摘要

现代燃气轮机燃烧室参数持续提高,燃料种类不断丰富,燃烧技术深入开发,这对燃机燃烧过程数值模拟方法的发展提出了更高的要求。火焰面方法兼具准确性和计算效率高的特点,是燃气轮机燃烧室成熟数值模拟方法的主要选择之一。该文针对燃气轮机燃烧室未来多工况、高参数、低污染的发展趋势,从火焰面方法在自适应湍流燃烧模型中的应用、进度变量的优化选择、湍流燃烧耦合模型以及火焰面方法在污染物预测中的应用等4个方面,回顾了火焰面方法的相关模型及适用范围,分析了该方法在燃气轮机燃烧室中的应用及面临的挑战。在此基础上,对火焰面方法在未来燃气轮机燃烧室模拟中的发展方向提出了针对性建议。

关键词： 燃料与燃烧; 火焰面方法; 燃气轮机; 进度变量; 多尺度多模式

本文引用格式

张归华 , 吴玉新 , 吴家豪 , 张扬 , 张海 . 火焰面方法进展及在燃机燃烧室模拟中的挑战[J]. 清华大学学报（自然科学版）, 2023 , 63(4) : 505 -520 . DOI: 10.16511/j.cnki.qhdxxb.2023.25.026

Abstract

[Significance] Given the consistent increase in the number of evaluation parameters, enrichment of fuel types in gas turbine combustors, and in-depth investigation of the combustion technology, the numerical simulation of combustion processes in gas turbines has become crucial. In various turbulent combustion models, the flamelet method couples numerous chemical components with a small number of scalars by preconstructing a table, which can reduce the number of transport equations to be solved while considering the detailed chemical reactions. The flamelet method, owing to its accuracy and computational efficiency, provides a primary alternative to numerical simulation for gas turbine combustors. [Progress] The present study reviews the advancement of flamelet methods. Subsequently, in view of the future development trend of gas turbine combustors with multiple working conditions, numerous parameters, and low pollution, we reviewed the relevant models and application scope of flamelet methods and analyzed their application and challenges in gas turbine combustors considering the following four aspects: the application of the flamelet method in an adaptive turbulent combustion model, optimized selection of progress variables, coupling with the turbulent model, and its application in pollution analysis. The application of the flamelet method in an adaptive turbulent combustion model includes its coupling with other turbulent combustion models and the development of a multi-region flamelet method. Toward this end, exploring appropriate identification techniques of different combustion modes is crucial, and the machine learning method is a robust tool to address this challenge. The optimized selection of progress variables involves multi-phase flow combustion and multi-fuel and multi-jet problems. However, a universal progress variable that can act as a representative of all problems is lacking. The flamelet method requires different expressions of progress variables in different problems. The development of universal optimization methods form the primary research aim. The coupling with the turbulent model mainly includes the presumed and transport probability density function methods; however, the balance of accuracy and computation cost remains to be elucidated. The application of the flamelet method in pollutant analysis requires solving additional transport equations of pollutants and modifying the expressions of source terms. [Conclusions and Prospects] Based on the review of previous literature, we recommend developing specific validation methods for each submodel in the flamelet method, performing further studies on the coupling effect of different submodels, and obtaining more data on real gas turbine combustion chambers to guide the development of a flamelet method suitable for real gas turbine combustion chambers.

Key words： fuel and combustion; flamelet method; gas turbine; progress variable; multi-scale multi-regime

参考文献

[1] 李苏辉,张归华,吴玉新.面向未来燃气轮机的先进燃烧技术综述[J].清华大学学报(自然科学版), 2021, 61(12):1423-1437. LI S H, ZHANG G H, WU Y X. Advanced combustion technologies for future gas turbines[J]. Journal of Tsinghua University (Science and Technology), 2021, 61(12):1423-1437.(in Chinese)
[2] POPE S B. Small scales, many species and the manifold challenges of turbulent combustion[J]. Proceedings of the Combustion Institute, 2013, 34(1):1-31.
[3] PETERS N. Laminar diffusion flamelet models in non-premixed turbulent combustion[J]. Progress in Energy and Combustion Science, 1984, 10(3):319-339.
[4] POPE S B. PDF methods for turbulent reactive flows[J]. Progress in Energy and Combustion Science, 1985, 11(2):119-192.
[5] 王海峰,陈义良,刘明侯.湍流扩散燃烧的数值研究-PDF方法和火焰面模型的性能比较[J].工程热物理学报, 2005, 26(S1):241-244. WANG H F, CHEN Y L, LIU M H. Numerical investigations of turbulent nonpremixed combustion:Performance of PDF method and flamelet models[J]. Journal of Engineering Thermophysics, 2005, 26(S1):241-244.(in Chinese)
[6] COOK A W, RILEY J J, KOSáLY G. A laminar flamelet approach to subgrid-scale chemistry in turbulent flows[J]. Combustion and Flame, 1997, 109(3):332-341.
[7] PIERCE C D. Progress-variable approach for large-eddy simulation of turbulent combustion[D]. Stanford:Stanford University, 2001.
[8] PITSCH H, IHME M. An unsteady/flamelet progress variable method for LES of nonpremixed turbulent combustion[C]//43rd AIAA Aerospace Sciences Meeting and Exhibit. Reno, USA:AIAA, 2005:557.
[9] CARBONELL D, PEREZ-SEGARRA C D, COELHO P J, et al. Flamelet mathematical models for non-premixed laminar combustion[J]. Combustion and Flame, 2009, 156(2):334-347.
[10] PITSCH H. Unsteady flamelet modeling of differential diffusion in turbulent jet diffusion flames[J]. Combustion and Flame, 2000, 123(3):358-374.
[11] KIM S K, KIM Y. Assessment of the Eulerian particle flamelet model for nonpremixed turbulent jet flames[J]. Combustion and Flame, 2008, 154(1-2):232-247.
[12] VAN OIJEN J A, DE GOEY L P H. Modelling of premixed laminar flames using flamelet-generated manifolds[J]. Combustion Science and Technology, 2000, 161(1):113-137.
[13] MAAS U, POPE S B. Simplifying chemical kinetics:Intrinsic low-dimensional manifolds in composition space[J]. Combustion and Flame, 1992, 88(3-4):239-264.
[14] LAM S H, GOUSSIS D A. Understanding complex chemical kinetics with computational singular perturbation[J]. Symposium (International) on Combustion, 1989, 22(1):931-941.
[15] DE GOEY L P H, TEN THIJE BOONKKAMP J H M. A flamelet description of premixed laminar flames and the relation with flame stretch[J]. Combustion and Flame, 1999, 119(3):253-271.
[16] BONGERS H, VAN OIJEN J A, DE GOEY L P H. Intrinsic low-dimensional manifold method extended with diffusion[J]. Proceedings of the Combustion Institute, 2002, 29(1):1371-1378.
[17] BYKOV V, MAAS U. The extension of the ILDM concept to reaction-diffusion manifolds[J]. Combustion Theory and Modelling, 2007, 11(6):839-862.
[18] GICQUEL O, DARABIHA N, THÉVENIN D. Liminar premixed hydrogen/air counterflow flame simulations using flame prolongation of ILDM with differential diffusion[J]. Proceedings of the Combustion Institute, 2000, 28(2):1901-1908.
[19] FIORINA B, BARON R, GICQUEL O, et al. Modelling non-adiabatic partially premixed flames using flame-prolongation of ILDM[J]. Combustion Theory and Modelling, 2003, 7(3):449-470.
[20] FIORINA B, GICQUEL O, VERVISCH L, et al. Approximating the chemical structure of partially premixed and diffusion counterflow flames using FPI flamelet tabulation[J]. Combustion and Flame, 2005, 140(3):147-160.
[21] VAN OIJEN J A, DE GOEY L P H. Modelling of premixed counterflow flames using the flamelet-generated manifold method[J]. Combustion Theory and Modelling, 2002, 6(3):463-478.
[22] VAN OIJEN J A, DONINI A, BASTIAANS R J M, et al. State-of-the-art in premixed combustion modeling using flamelet generated manifolds[J]. Progress in Energy and Combustion Science, 2016, 57:30-74.
[23] NGUYEN P D, VERVISCH L, SUBRAMANIAN V, et al. Multidimensional flamelet-generated manifolds for partially premixed combustion[J]. Combustion and Flame, 2010, 157(1):43-61.
[24] 赵庆忠,叶桃红,吴玉欣.基于混合物分数和反应进度变量的二维火焰面模型[J].燃烧科学与技术, 2013, 19(2):181-186. ZHAO Q Z, YE T H, WU Y X. Two-dimensional flamelet model based on mixture fraction and progress variable[J]. Journal of Combustion Science and Technology, 2013, 19(2):181-186.(in Chinese)
[25] WU Y X, CAO C M, YE T H, et al. A new multi-dimensional flamelet generated manifolds approach for approximating partially premixed flame structure[J]. Journal of Thermal Science and Technology, 2015, 10(1):JTST0017.
[26] 张健,张琪,杨天威,等.发动机湍流燃烧多物理耦合建模和仿真进展[J].航空发动机, 2022, 48(3):42-51. ZHANG J, ZHANG Q, YANG T W, et al. Progress of multi-physical coupling modeling and simulation of engine turbulent combustion[J]. Aeroengine, 2022, 48(3):42-51.(in Chinese)
[27] WU H, SEE Y C, WANG Q, et al. A Pareto-efficient combustion framework with submodel assignment for predicting complex flame configurations[J]. Combustion and Flame, 2015, 162(11):4208-4230.
[28] WU H, MA P C, JARAVEL T, et al. Pareto-efficient combustion modeling for improved CO-emission prediction in LES of a piloted turbulent dimethyl ether jet flame[J]. Proceedings of the Combustion Institute, 2019, 37(2):2267-2276.
[29] XU C, AMEEN M M, SOM S, et al. Dynamic adaptive combustion modeling of spray flames based on chemical explosive mode analysis[J]. Combustion and Flame, 2018, 195:30-39.
[30] RIETH M, CHEN J Y, MENON S, et al. A hybrid flamelet finite-rate chemistry approach for efficient LES with a transported FDF[J]. Combustion and Flame, 2019, 199:183-193.
[31] WU H, IHME M. Compliance of combustion models for turbulent reacting flow simulations[J]. Fuel, 2016, 186:853-863.
[32] HU Y, KUROSE R. Large-eddy simulation of turbulent autoigniting hydrogen lifted jet flame with a multi-regime flamelet approach[J]. International Journal of Hydrogen Energy, 2019, 44(12):6313-6324.
[33] WEN X, LUO Y J, LUO K, et al. LES of pulverized coal combustion with a multi-regime flamelet model[J]. Fuel, 2017, 188:661-671.
[34] YAMASHITA H, SHIMADA M, TAKENO T. A numerical study on flame stability at the transition point of jet diffusion flames[J]. Symposium (International) on Combustion, 1996, 26(1):27-34.
[35] FIORINA B, GICQUEL O, VERVISCH L, et al. Approximating the chemical structure of partially premixed and diffusion counterflow flames using FPI flamelet tabulation[J]. Combustion and Flame, 2005, 140(3):147-160.
[35] KNUDSEN E, PITSCH H. A general flamelet transformation useful for distinguishing between premixed and non-premixed modes of combustion[J]. Combustion and Flame, 2009, 156(3):678-696.
[36] KNUDSEN E, PITSCH H. Capabilities and limitations of multi-regime flamelet combustion models[J]. Combustion and Flame, 2012, 159(1):242-264.
[37] IHME M, SEE Y C. Large-eddy simulation of a turbulent lifted flame in a vitiated co-flow[C]//47th AIAA Aerospace Sciences Meeting Including The New Horizons Forum and Aerospace Exposition. Orlando, Florida:AIAA, 2009:239.
[38] HOU L Y, NIU D S, REN Z Y. Partially premixed flamelet modeling in a hydrogen-fueled supersonic combustor[J]. International Journal of Hydrogen Energy, 2014, 39(17):9497-9504.
[39] SHAN F L, ZHANG D R, HOU L Y, et al. Partially premixed combustion simulation using a novel transported multi-regime flamelet model[J]. Acta Astronautica, 2022, 191:245-257.
[40] GALASSI R M, CIOTTOLI P P, VALORANI M, et al. Local combustion regime identification using machine learning[J]. Combustion Theory and Modelling, 2022, 26(1):135-151.
[41] NIU Y S, VERVISCH L, TAO P D. An optimization-based approach to detailed chemistry tabulation:Automated progress variable definition[J]. Combustion and Flame, 2013, 160(4):776-785.
[42] MA L K. Computational modeling of turbulent spray combustion[D]. Gansu:National University of Defense Technology, China, 2016.
[43] LUO K, FAN J R, CEN K F. New spray flamelet equations considering evaporation effects in the mixture fraction space[J]. Fuel, 2013, 103:1154-1157.
[44] WATANABE J, YAMAMOTO K. Flamelet model for pulverized coal combustion[J]. Proceedings of the Combustion Institute, 2015, 35(2):2315-2322.
[45] BABA Y, KUROSE R. Analysis and flamelet modelling for spray combustion[J]. Journal of Fluid Mechanics, 2008, 612:45-79.
[46] GE H W, GUTHEIL E. Simulation of a turbulent spray flame using coupled PDF gas phase and spray flamelet modeling[J]. Combustion and Flame, 2008, 153(1-2):173-185.
[47] OLGUIN H, GUTHEIL E. Influence of evaporation on spray flamelet structures[J]. Combustion and Flame, 2014, 161(4):987-996.
[48] WANG Y C, CAI R P, SHAO C X, et al. A priori and a posteriori studies of a novel spray flamelet tabulation methodology considering evaporation effects[J]. Fuel, 2023, 331:125892.
[49] CAI R P, LUO K, GAO Z W, et al. Dual-scale flamelet/progress variable approach for prediction of polycyclic aromatic hydrocarbons formation under the condition of coal combustion[J]. Energy&Fuels, 2020, 34(8):10010-10018.
[50] HASSE C, PETERS N. Modelling of ignition mechanisms and pollutant formation in direct-injection diesel engines with multiple injections[J]. International Journal of Engine Research, 2005, 6(3):231-246.
[51] FELSCH C, GAUDING M, HASSE C, et al. An extended flamelet model for multiple injections in DI Diesel engines[J]. Proceedings of the Combustion Institute, 2009, 32(2):2775-2783.
[52] IHME M, SHUNN L, ZHANG J. Regularization of reaction progress variable for application to flamelet-based combustion models[J]. Journal of Computational Physics, 2012, 231(23):7715-7721.
[53] VASAVAN A, DE GOEY P, VAN OIJEN J. A novel method to automate FGM progress variable with application to igniting combustion systems[J]. Combustion Theory and Modelling, 2020, 24(2):221-244.
[54] SUTHERLAND J C, PARENTE A. Combustion modeling using principal component analysis[J]. Proceedings of the Combustion Institute, 2009, 32(1):1563-1570.
[55] NAJAFI-YAZDI A, CUENOT B, MONGEAU L. Systematic definition of progress variables and intrinsically low-dimensional, flamelet generated manifolds for chemistry tabulation[J]. Combustion and Flame, 2012, 159(3):1197-1204.
[56] COUSSEMENT A, GICQUEL O, PARENTE A. Kernel density weighted principal component analysis of combustion processes[J]. Combustion and Flame, 2012, 159(9):2844-2855.
[57] CHEN J, LIU M, CHEN Y L. Optimizing progress variable definition in flamelet-based dimension reduction in combustion[J]. Applied Mathematics and Mechanics, 2015, 36(11):1481-1498.
[58] 唐鹏.基于机器学习的火焰面建表标量优化和放热率模化研究[D].合肥:中国科学技术大学, 2021. TANG P. Study on the optimization of flamelet tabulated scalars and modeling of heat release rate based on machine learning[D]. Hefei:University of Science and Technology of China, 2021.(in Chinese)
[59] 张健,刘柽钰,杨涛.基于过程变量-火焰面模型的湍流燃烧大涡模拟[J].中国科学:物理学·力学·天文学, 2017, 47(7):070007. ZHANG J, LIU C Y, YANG T. Large-eddy simulation of turbulent combustion based on steady flamelet/progress variable approach[J]. Scientia Sinica (Physica, Mechanica&Astronomica), 2017, 47(7):070007.(in Chinese)
[60] BRADLEY D, KWA L K, LAU A K C, et al. Laminar flamelet modeling of recirculating premixed methane and propane-air combustion[J]. Combustion and Flame, 1988, 71(2):109-122.
[61] COOK A W, RILEY J J. A subgrid model for equilibrium chemistry in turbulent flows[J]. Physics of Fluids, 1994, 6(8):2868-2870.
[62] IHME M, SEE Y C. Prediction of autoignition in a lifted methane/air flame using an unsteady flamelet/progress variable model[J]. Combustion and Flame, 2010, 157(10):1850-1862.
[63] PIERCE C D, MOIN P. A dynamic model for subgrid-scale variance and dissipation rate of a conserved scalar[J]. Physics of Fluids, 1998, 10(12):3041-3044.
[64] KAUL C M, RAMAN V, KNUDSEN E, et al. Large eddy simulation of a lifted ethylene flame using a dynamic nonequilibrium model for subfilter scalar variance and dissipation rate[J]. Proceedings of the Combustion Institute, 2013, 34(1):1289-1297.
[65] PETERS N, WILLIAMS F A. Liftoff characteristics of turbulent jet diffusion flames[J]. AIAA Journal, 1983, 21(3):423-429.
[66] IHME M, PITSCH H. Prediction of extinction and reignition in nonpremixed turbulent flames using a flamelet/progress variable model:1. A priori study and presumed PDF closure[J]. Combustion and Flame, 2008, 155(1-2):70-89.
[67] MURTHY R V V S. Advanced flamelet modelling of turbulent nonpremixed and partialy premixed combustion[D]. Loughborough:Loughborough University, 2008.
[68] 唐军,宋文艳,肖隐利.采用不同建表方法的火焰面模型在燃烧室中的应用研究[J].推进技术, 2018, 39(8):1810-1820. TANG J, SONG W Y, XIAO Y L. Study of the application of flamelet models in combustor with different tabulation methods[J]. Journal of Propulsion Technology, 2018, 39(8):1810-1820.(in Chinese)
[69] KONG F F, LI T, CHENG C, et al. Modeling of spray flame in gas turbine combustors with LES and FGM[J]. Fuel, 2022, 325:124756.
[70] GUPTA A, ZHU J, ANAND M S, et al. A flame-generated-manifold chemistry based transport PDF model for gas-turbine combustor simulations[C]//52nd Aerospace Sciences Meeting. National Harbor, USA:AIAA, 2014:1028.
[71] POPOV P P. Alternatives to the beta distribution in assumed PDF methods for turbulent reactive flow[J]. Flow, Turbulence and Combustion, 2022, 108(2):433-459.
[72] CHEN J Y, CHANG W C. Flamelet and PDF modeling of CO and NOx emissions from a turbulent, methane hydrogen jet nonpremixed flame[J]. Symposium (International) on Combustion, 1996, 26(2):2207-2214.
[73] YAO Q, ZHANG Y, WANG X J, et al. Investigation of NOx emission under different burner structures with the optimized combustion model[J]. Neurocomputing, 2022, 482:224-235.
[74] YUNOKI K, KAI R, INOUE S, et al. Numerical simulation of CO formation and reduction on flame propagation due to heat loss through the cooled wall[J]. Energy, 2021, 236:121352.
[75] HONZAWA T, KAI R, OKADA A, et al. Predictions of NO and CO emissions in ammonia/methane/air combustion by LES using a non-adiabatic flamelet generated manifold[J]. Energy, 2019, 186:115771.
[76] REN Z Y, YANG H T, LU T F. Effects of small-scale turbulence on NOx formation in premixed flame fronts[J]. Fuel, 2014, 115:241-247.
[77] IHME M, PITSCH H. Modeling of radiation and nitric oxide formation in turbulent nonpremixed flames using a flamelet/progress variable formulation[J]. Physics of Fluids, 2008, 20(5):055110.
[78] MUELLER M E, PITSCH H. Large eddy simulation of soot evolution in an aircraft combustor[J]. Physics of Fluids, 2013, 25(11):110812.
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