Numerical Prediction of CO and NOx Combustion Pollutants Based on the Coupled SATES-FGM-CRN Method

  • CHEN Tao ,
  • ZHU Rui ,
  • HAN Xingsi
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  • College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

网络出版日期: 2025-07-04

基金资助

This work was financially supported by the National Natural Science Foundation of China (No. 52376114 and No. 92041001), the Jiangsu Provincial Natural Science Foundation (BK20200069), and the National Science and Technology Major Project (J2019-III-0015-0059).

版权

Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2025

Numerical Prediction of CO and NOx Combustion Pollutants Based on the Coupled SATES-FGM-CRN Method

  • CHEN Tao ,
  • ZHU Rui ,
  • HAN Xingsi
Expand
  • College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Online published: 2025-07-04

Supported by

This work was financially supported by the National Natural Science Foundation of China (No. 52376114 and No. 92041001), the Jiangsu Provincial Natural Science Foundation (BK20200069), and the National Science and Technology Major Project (J2019-III-0015-0059).

Copyright

Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2025

摘要

本研究采用新型SATES(自适应湍流模拟)-FGM(火焰面生成流形)-CRN(化学反应器网络)耦合方法,对甲烷/空气湍流扩散火焰(Sandia Flame D)中CO与NOx的燃烧污染物进行耦合数值预测。基于可实现的k-ε和BSL k-ω两种基础湍流模型构建了SATES计算框架。通过将两种SATES模型与两种RANS模型分别耦合FGM燃烧模型,对比分析了燃烧场与CO污染物分布的预测精度。进一步利用CRN方法,基于SATES-FGM获取的非定常高精度燃烧场结果,建立了多尺度多规则的NOx分布特征构建方法。研究结果表明:SATES-FGM方法能够准确预测湍流扩散火焰,在SATES框架下提升了不同RANS模型对流动形态的敏感性。但在主燃区预测仍存在较大偏差。该方法对自由射流湍流火焰流场具有高效精确的模拟能力,对CO等伴随燃烧过程生成的污染物具有良好的预测效果。SATES-CRN耦合方法可准确预测NOx等燃烧后污染物,其中CRN分区数量可根据燃烧室特征进行适应性调整。过量反应分区不仅会降低计算效率,还会导致NOx生成量预测偏差。非定常SATES-CRN耦合方法更适用于复杂分区规则。本研究构建的SATES-FGM-CRN耦合预测方法,为同时预测CO与NOx污染物分布提供了一种新颖高效的解决途径。

本文引用格式

CHEN Tao , ZHU Rui , HAN Xingsi . Numerical Prediction of CO and NOx Combustion Pollutants Based on the Coupled SATES-FGM-CRN Method[J]. 热科学学报, 2025 , 34(4) : 1512 -1526 . DOI: 10.1007/s11630-025-2119-0

Abstract

This study employs a new SATES (Self-Adaptive Turbulence Eddy Simulation)-FGM (Flamelet Generated Manifold)-CRN (Chemical Reactor Network) coupling method to numerically predict the combustion pollutions of CO and NOx together in a methane/air turbulent diffusion flame (Sandia Flame D). Two SATES models are developed based on the underlying realizable k-ε and BSL k-ω turbulence models. The prediction accuracy of the combustion field and the CO pollutant distribution are compared and analyzed by coupling two SATES models and two RANS (Reynolds-Averaged Navier-Stokes) models with FGM combustion model. Furthermore, CRN is utilized to construct the NOx distribution characteristics for different scales and rules using the unsteady high-fidelity combustion field results obtained from SATES-FGM. The results demonstrate that SATES-FGM can accurately predict the turbulent diffusion flame and improve the sensitivity of different RANS models to flow patterns in the framework of the SATES method. However, the results show a large deviation in predicting the main combustion zone. The SATES-FGM method can efficiently and accurately simulate flow fields of the free-jet turbulent flame. Additionally, it performs well in predicting the pollution products associated with combustion process, such as CO, while the SATES-CRN coupling method can accurately predict the post-combustion pollutants like NOx. The number of CRN zones can be adjusted to fit the combustor. Excessive reaction zones not only reduce the efficiency but also result in a deviation in the NOx prediction. The unsteady SATES-CRN coupling method is better suited for complex partitioning rules. The developed SATES-FGM-CRN method can offer a new and efficient approach to simultaneously predict the distributions of CO and NOx pollutions.

参考文献

[1] Wright I.G., Gibbons T.B., Recent developments in gas turbine materials and technology and their implications for syngas firing. International Journal of Hydrogen Energy, 2007, 32(16): 3610–3621.
[2] Bauer H.J., New low emission strategies and combustor designs for civil aeroengine applications. Progress in Computational Fluid Dynamics, 2004, 4(3–5): 130–142.
[3] Wang C., Yue Z., Zhao Y., et al., Numerical simulation of the high-boosting influence on mixing, combustion and emissions of high-power-density engine. Journal of Thermal Science, 2023, 32(3): 933–946. 
[4] Ren Z., Lu Z., Hou L., et al., Numerical simulation of turbulent combustion: Scientific challenges. Science China Physics, Mechanics & Astronomy, 2014, 57(8): 1495–1503.
[5] Chaouat B., The state of the art of hybrid RANS/LES modeling for the simulation of turbulent flows. Flow, Turbulence and Combustion, 2017, 99(2): 279–327.
[6] Rezaeiha A., Montazeri H., Blocken B., CFD analysis of dynamic stall on vertical axis wind turbines using Scale-Adaptive Simulation (SAS): Comparison against URANS and hybrid RANS/LES. Energy Conversion and Management, 2019, 196: 1282–1298.
[7] Luo G., Dai H., Dai L., et al., Review on large eddy simulation of turbulent premixed combustion in tubes. Journal of Thermal Science, 2020, 29(4): 853–867.
[8] Syawitri T.P., Yao Y.F., Chandra B., et al., Comparison study of URANS and hybrid RANS-LES models on predicting vertical axis wind turbine performance at low, medium and high tip speed ratio ranges. Renewable Energy, 2021, 168: 247–269.
[9] Sagaut P., Large eddy simulation for incompressible flows: an introduction. Third ed., Springer Science & Business Media, Berlin, 2005.
[10] Kawai S., Larsson J., Wall-modeling in large eddy simulation: length scales, grid resolution, and accuracy. Physics of Fluids, 2012, 24(1): 015105.
[11] Hanjalić K., Kenjereš S., Some developments in turbulence modeling for wind and environmental engineering. Journal of Wind Engineering and Industrial Aerodynamics, 2008, 96(10–11): 1537–1570.
[12] Spalart P.R., Detached-eddy simulation. Annual Review of Fluid Mechanics, 2009, 41(1): 181–202.
[13] Tessicini F., Temmerman L., Leschziner M.A., Approximate near-wall treatments based on zonal and hybrid RANS-LES methods for LES at high Reynolds numbers. International Journal of Heat and Fluid Flow, 2006, 27(5): 789–799.
[14] Girimaji S.S., Partially-averaged Navier-Stokes model for turbulence: A Reynolds-averaged Navier-Stokes to direct numerical simulation bridging method. Journal of Applied Mechanics, 2006, 73(3): 413–421.
[15] Chaouat B., Schiestel R., Hybrid RANS/LES simulations of the turbulent flow over periodic hills at high Reynolds number using the PITM method. Computers & Fluids, 2013, 84: 279–300.
[16] Han X.S., Krajnović S., An efficient very large eddy simulation model for simulation of turbulent flow. International Journal for Numerical Methods in Fluids, 2013, 71(11): 1341–1360.
[17] Han X.S., Krajnović S., Validation of a novel very large eddy simulation method for simulation of turbulent separated flow. International Journal for Numerical Methods in Fluids, 2013, 73(5): 436–461.
[18] Han X.S., Krajnović S., Very-large-eddy simulation based on k-ω model. AIAA Journal, 2015, 53(4): 1103–1108.
[19] Speziale C.G., Turbulence modeling for time-dependent RANS and VLES: A review. AIAA Journal, 1998, 36(2): 173–184.
[20] Xia Z.Y., Han X.S., Mao J.K., Assessment and validation of very-large-eddy simulation turbulence modeling for strongly swirling turbulent flow. AIAA Journal, 2020, 58(1): 148–163.
[21] Pope S.B., Ren Z., Efficient implementation of chemistry in computational combustion. Flow, Turbulence and Combustion, 2009, 82(4): 437–453.
[22] Wang H., Zhou H., Ren Z., et al., Transported PDF simulation of turbulent CH4/H2 flames under MILD conditions with particle-level sensitivity analysis. Proceedings of the Combustion Institute, 2019, 37(4): 4487–4495.
[23] Ren Z., Goldin G.M., Hiremath V., et al., Simulations of a turbulent non-premixed flame using combined dimension reduction and tabulation for combustion chemistry. Fuel, 2013, 105: 636–644.
[24] Van Oijen J.A., Donini A., Bastiaans R.J.M., et al., State-of-the-art in premixed combustion modeling using flamelet generated manifolds. Progress in Energy and Combustion Science, 2016, 57: 30–74.
[25] Boucher A., Bertier N., Dupoirieux F., A method to extend flamelet manifolds for prediction of NOx and long time scale species with tabulated chemistry. International Journal of Sustainable Aviation, 2014, 1(2): 181–202.
[26] Hao N.T., A chemical reactor network for oxides of nitrogen emission prediction in gas turbine combustor. Journal of Thermal Science, 2014, 23(3): 279–284.
[27] Monaghan R.F., Tahir R., Cuoci A., et al., Detailed multi-dimensional study of pollutant formation in a methane diffusion flame. Energy & Fuels, 2012, 26(3): 1598–1611.
[28] Khodayari H., Ommi F., Saboohi Z., A review on the applications of the chemical reactor network approach on the prediction of pollutant emissions. Aircraft Engineering and Aerospace Technology, 2020, 92(4): 551–570.
[29] Ehrhardt K., Toqan P., Jansohn P., et al., Modeling of NOx reburning in a pilot scale furnace using detailed reaction kinetics. Combustion Science and Technology, 1998, 131: 131–146.
[30] Benedetto D., Pasini S., Falcitelli M., et al., NOx emission prediction from 3-D complete modelling to reactor network analysis. Combustion Science and Technology, 2000, 153(1): 279–294.
[31] Innocenti A., Andreini A., Bertini D., Turbulent flow-field effects in a hybrid CFD-CRN model for the prediction of NOx and CO emissions in aero-engine combustors. Fuel, 2018, 215: 853–864.
[32] Vashishtha A., Yousefian S., Goldin G., et al., CFD-CRN study of NOx formation in a high-pressure combustor fired with lean premixed CH4/H2-air mixtures. ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition, American Society of Mechanical Engineers Digital Collection, GT2020-14819, V04AT04A043.
[33] Ahmad N., Nairui L., Tariq M., et al., NOx emission prediction analysis and comparison in gas turbine combustor utilizing CFD and CRN combined approach. 2019 Sixth International Conference on Aerospace Science and Engineering (ICASE), Islamabad, Pakistan, 2019, 11: 12–14.
[34] Frassoldati A., Frigerio S., Colombo E., et al., Determination of NOx emissions from strong swirling confined flames with an integrated CFD-based procedure. Chemical Engineering Science, 2005, 60(4–6): 2851–2869.
[35] Lyra S., Cant R.S., Analysis of high pressure premixed flames using equivalent reactor networks for predicting NOx emissions. Fuel, 2013, 107: 261–268.
[36] Novosselov I.V., Malte P.C., Development and application of an eight-step global mechanism for CFD and CRN simulations of lean-premixed combustors. Journal of Engineering for Gas Turbines and Power, 2008, 130(2): 021502.
[37] Fichet V., Kanniche M., Plion P., et al., A reactor network model for predicting NOx emissions in gas turbines. Fuel, 2010, 89(9): 2202–2210.
[38] Fackler K.B., Karalus M.F., Novosselov I.V., et al., Experimental and numerical study of NOx formation from the lean premixed combustion of CH4 mixed with CO2 and N2. Journal of Engineering for Gas Turbines and Power, 2011, 133(12): 121502. 
[39] Shaheed R., Mohammadian A., Gildeh H.K., A comparison of standard k-ε and realizable k-ε turbulence models in curved and confluent channels. Environmental Fluid Mechanics, 2019, 19(2): 543–568.
[40] Bulat M.P., Bulat P.V., Comparison of turbulence models in the calculation of supersonic separated flows. World Applied Sciences Journal, 2013, 27(10): 1263–1266.
[41] Shih T.H., Liou W.W., Shabbir A., et al., A new k-ϵ eddy viscosity model for high Reynolds number turbulent flows - Model development and validation. Computers & Fluids, 1995, 24(3): 227-238.
[42] Menter F.R., Improved two-equation k-w turbulence models for aerodynamic flows. NASA, 1992, TM103975.
[43] Khosravi Nikou M.R., Ehsani M.R., Turbulence models application on CFD simulation of hydrodynamics, heat and mass transfer in a structured packing. International Communications in Heat and Mass Transfer, 2008, 35(9): 1211–1219.
[44] Menter F.R., Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal, 1994, 32(8): 1598–1605.
[45] Barlow R.S., Frank J.H., Effects of turbulence on species mass fraction in methane/air jet flames. Proceedings of the Combustion Institute, 1998, 27(1): 1087–1095.
[46] Elbahloul S., Rigopoulos S., Rate-controlled constrained equilibrium (RCCE) simulations of turbulent partially premixed flames (Sandia D/E/F) and comparison with detailed chemistry. Combustion and Flame, 2015, 162(5): 2256–2271.
[47] Gruber M.R., Nejadt A.S., Chen T.H., et al., Mixing and penetration studies of sonic jets in a Mach 2 freestream.  Journal of Propulsion and Power, 1995, 11(2): 315–323.
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