Numerical Detection of Carcinogenic Hydrocarbons Emission by Aircraft Gas Turbine Engines Combustion Chambers

Aeronautical and Space-Rocket Engineering


Аuthors

Semenikhin A. S.*, Matveev S. G.**, Gurakov N. I.***, Idrisov D. V.****, Matveev S. S.*****, Didenko A. A.******

Samara National Research University named after Academician S.P. Korolev, Samara, Russia

*e-mail: semenikhin.as@ssau.ru
**e-mail: msg@ssau.ru
***e-mail: gurakov.ni@ssau.ru
****e-mail: idrisov.dv@ssau.ru
*****e-mail: matveev@ssau.ru
******e-mail: didenko.aa@ssau.ru

Abstract

Aircraft engines environmental characteristics improving an up-to-date task on aviation impact minimizing on the environment. Among the aviation kerosene combustion products, carcinogenic polycyclic aromatic hydrocarbons (PAH) and sooty solid particles, such as microparticles and clusters, for which PAH are the basic reactants, may pose a particular threat to humans. Benzo(a)pyrene (C20H12) is considered to be the most carcinogenic PAH. For this reason, it serves as an indicator of the carcinogenic activity of the environment. As of today, the existing semi-empirical models for predicting benzo(a)pyrene emissions by aircraft engines are severely limited by the specific designs and operating conditions. Thus, the PAH concentration detection method elaboration, which does not require experimental studies, for environmental characteristics assesment of the projects being designed is up-to-date. The PAH forming kinetic mechanisms depend on many factors. That is why, the PAH emissions by the GTE combustion chambers (CC) predicting is feasible only with concurrent application of the gas dynamics (CFD) numerical simulation and detailed chemical kinetics. In view of technical limitations, this problem is being solved with combined modeling techniques, where the of CFD calculations results with a simplified description of chemical processes are employed to represent the computational domain as a sequence of chemical reactors (Chemical Reactor Network - CRN) with idealized gas dynamics for kinetic calculations in a 0D- or 1D- formulation. Combined technique has been successfully applied to calculate the concentrations of carbon monoxide and nitrogen oxides, but its application to solving the practical problem of determining the emission of PAH by the combustion chambers of the stock GTEs is not available in the accessible literature. With the view of the above said, the purpose of this work consists in testing the combined CFD/CRN modeling with of TS-1 kerosene submodels (kinetic combustion model “A17” and model fuel UM1) to compute the benzo(a)pyrene emissions by the GTE СС. To validate the performed computations, the data from the experimental study of a tubular combustion chamber model, a prototype of a stock product, are applied. The article solves the corresponding problems of the 3D-modeling anddescribes the process of setting up the ANSYS Fluent submodels to describe kerosene combustion. The CFD computations results are used to build the Fluent-CRN and CFD-Energico-Chemkin reactor models. The semi-automated CFD-Energico-Chemkin algorithms allowed creating a reactor model of 25 reactors and computing benzo(a)pyrene concentrations with an accuracy comparable to the experimental one. The limited number of reactors does not allow describing combustion processes in detail in the entire volume of the GTE combustion chamber. That is why the results of modeling are mainly determined by the fact to what extent the applied algorithms allow highlighting the specific combustion zones, i.e. local conditions determining the PAH synthesis and burning-out. The Fluent-CRN models describe combustion chamber by dint of several hundred reactors. The widely used algorithm envolving the temperature distribution and the mean mixture fraction concentration from the PAH approach (solution of the averaged Navier-Stokes equations) to turbulence modeling did not produce satisfactory results, and the calculated PAH concentrations were underestimated by many orders of magnitude. At the same time, the LES approach (large eddy simulation) application in the CFD modeling of combustion chamber working processes and the subsequent construction of Fluent-CRN reactor models with account for pulsations of the mean mixture fraction gave the values of the PAH concentrations approaching the experimental ones. The latter allows inferring on the rationality of further development of this approach and corresponding submodels. 

Keywords:

emission of deleterious pollutants, chemical reactor network, CRN, combustion chamber, gas turbine engine, polycyclic aromatic hydrocarbons (PAH), benz(a)pyrene

References

  1.  Lukachev SV, Matveev SG, Orlov MYu. Vybros kantserogenov pri szhiganii uglevodorodnykh topliv (Carcinogen emissions from hydrocarbon fuel combustion). Samara: SSAU; 2007. 160 p.
  2.  Orlov MY, Zrelov VA, Orlova EV. Statistic data application for narrow-body aircraft engines combustion chambers preliminary design. Aerospace MAI Journal. 2022;29(4):151-160. DOI: 10.34759/vst-2022-4-151-160
  3.  Tkachenko AY. Working fluid mathematical model for the gas turbine engine thermo-gas-dynamic design. Aerospace MAI Journal. 2021;28(4):180-191. DOI: 10.34759/vst-2021-4-180-191
  4.  Koval' SN, Badernikov AV., Shmotin YN, Pyatunin KR. Digital twin technology application while gas turbine engines development. Aerospace MAI Journal. 2021;28(3):139-145. DOI: 10.34759/vst-2021-3-139-145
  5.  Wen Z, Yun S, Thomson MJ, Lightstone MF. Modeling soot formation in turbulent kerosene/air jet diffusion flames. Combustion and Flame. 2003;135(3):323-340. DOI: 10.1016/S0010-2180(03)00179-2
  6.  Griga AD, Ivanitsky MS. Determination of benz(a)pyrene in the flue gases of combustion chamber of gas turbine. Vestnik Voronezhskogo gosudarstvennogo tekhnicheskogo universiteta. 2014;10(5):86-88.
  7.  Grigor'ev AV, Mitrofanov VA, Rudakov OA, Salivon ND. Teoriya kamery sgoraniya (Combustion chamber theory). St. Petersburg: Nauka; 2010. 227 p.
  8.  Pelevin VS., Aleksentsev AA, Filinov EP, Komisar YV. Impurities in aviation fuel effect on the working process parameters and effectiveness indicators of gas turbine engines and power plants. Aerospace MAI Journal. 2022;29(4):186-195. DOI: 10.34759/vst-2022-4-186-195
  9.  Kalyakina KA, Kalyakin AV, Faizullin RR, Egorov MA. Decarbonization of air transportation through the use of sustainable aviation fuels (SAF). Nauchnyi vestnik UI GA. 2022;(14):37-43.
  10.  Kozlov VE, Lebedev AB, Sekundov AN. et al. Application of reactor models to calculate emission characteristics of diffusion and homogeneous combustion chambers. In: Trudy TsIAM. No. 1347 “Ekologicheskie problemy aviatsii”. Sbornik statei. Moscow: Torus Press; 2010. p. 321-338.
  11.  Kutlumukhamedov AR, Skiba DV, Bakirov FB. A review of works dedicated to the assessment of carbon monoxide emissions from gas turbine combustion chambers using reactor network models developed on the basis of the three-dimensional simulation results. Vestnik UGATU. 2022;26(1):69–80. DOI: 10.54708/19926502_2022_2619569
  12.  Chechet IV. Metodika opredeleniya emissii kantserogennykh aromaticheskikh uglevodorodov kamerami sgoraniya gazoturbinnykh dvigateley i ustanovok. Ph.D. Thesis. Samara University; 2018. 149 p.
  13.  Xin S, Wang W, Yang F. et al. Soot and PAH formation in laminar diffusion flames of RP-3 jet kerosene and its surrogates at preheat temperature. Fuel. 2024;361:130735. DOI: 10.1016/j.fuel.2023.130735
  14.  Semenikhin AS, Idrisov DV, Chechet IV. et al. Kinetic model and kerosene surrogate for calculating the emission of carcinogenic hydrocarbons by gas turbine engines. Vestnik Samarskogo universiteta. Aerokosmicheskaya tekhnika, tekhnologii i mashinostroenie. 2022;21(3):58–68. DOI: 10.18287/2541-7533-2022-21-3-58-68
  15.  Kim D, Martz J, Violi A. A surrogate for emulating the physical and chemical properties of conventional jet fuel. Combustion and Flame. 2014;161(6):1489–1498. DOI: 10.1016/j.combustflame.2013.12.015
  16.  Matveev SG, Chechet IV, Abrashkin VYu, Semenov AV. Formation of cancerogenic pah in the turbulent diffusive flame. Izvestiya Samarskogo nauchnogo tsentra Rossiiskoi akademii nauk. 2013;15 6-4):881–885.
  17.  ANSYS Fluent 21.2 User Guide. Canonsburg, PA: ANSYS Inc. 2021.
  18.  Gurakov NI, Morales MH, Zubrilin IA. et al. A study on the geometric characteristic influence on the liquid fuel flow in a three-way pressure-swirl atomizer. Journal of Physics: Conference Series. 2021. Vol. 1891. The International Conference on Aviation Motors (ICAM 2020; 18-21 May 2021, Moscow, Russia). No.1:012021. DOI: 10.1088/1742-6596/1891/1/012021
  19.  Snegirev AYu. Vysokoproizvoditel'nye vychisleniya v fizike. Chislennoe modelirovanie turbulentnykh techenii (High performance computing in physics. Numerical modeling of turbulent flows), St. Petersburg: Politekhnicheskii universitet; 2008. 143 p.
  20.  Oijen JA, Goey LPH. Modelling of premixed laminar flames using flamelet-generated manifolds. Combustion Science and Technology. 2000;161(1):113-137. DOI: 10.1080/00102200008935814
  21.  Baklanov AV. Temperature Field Change at the Multi-Nozzle Combustion Chamber Outlet at Various Engine Operating Modes. Aerospace MAI Journal. 2024;31(2):116-123. URL: https://vestnikmai.ru/publications.php?ID=180654
  22.  Baklanov AV. Fuel combustion efficiency ensuring in low-emission combustion chamber of gas turbine engine under various climate conditions. Aerospace MAI Journal. 2022;29(1):144-155. DOI: 10.34759/vst-2022-1-144-155
  23.  Energico 18.2. User Guide. San Diego: ANSYS Inc. 2017.
  24.  Stagni A, Cuoci A, Frassoldati A. et al. A fully coupled, parallel approach for the post-processing of CFD data through reactor network analysis. Computers & Chemical Engineering. 2014;60:197-212. DOI: 10.1016/j.compchemeng.2013.09.002

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