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Journals / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi / 2024 / Cilt: 39 Sayı: 1

Differential diffusion and pressure effects on heavily sooting 2D Kerosene/Air diffusion flames

Yüksek derecede kurum üreten 2B Gazyağı/Hava difüzyon alevleri üzerinde diferansiyel yayılımın ve basıncın etkileri

Ayşe KORUCU
Richard MİLLER
Pages
91–100
Publication Date
2023-08-21
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

For the aim of verifying the applicability of the unity Le assumption for Kerosene/Air flames comparisons between unity and non-unity Lewis (Le) number flame predictions must possess statistically similar trends in not only the flame structure but also the soot properties. 1, 5 10 and 35 atm analyses of 2D DNS flame predictions of the RGL and the IGL EOS models have unveiled that the EOS coupled models with the unity-Le number mis-predicts the soot properties and the mean flame temperatures.

📌 3 Key Takeaways

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Objective & Hypothesis:For heavily sooting Kerosene/Air flames the ideal gas law (IGL) and a real gas (RGL) equation of state (EOS) models have been employed to study the assumption of the unity Lewis (Le) number effects on the soot production/oxidation processes for four different operating pressures.
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Key Findings & Data:An MPI FORTRAN code containing a semi-global soot production/oxidation model for a reduced Kerosene/Air mechanism (29-step, 10 species) has been used to create 2B DSS data.
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Conclusion & Impact:For the aim of verifying the applicability of the unity Le assumption for Kerosene/Air flames comparisons between unity and non-unity Lewis (Le) number flame predictions must possess statistically similar trends in not only the flame structure but also the soot properties. 1, 5 10 and 35 atm analyses of 2D DNS flame predictions of the RGL and the IGL EOS models have unveiled that the EOS coupled models with the unity-Le number mis-predicts the soot properties and the mean flame temperatures.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Gazyağı · kurum · DNS

Abstract

For heavily sooting Kerosene/Air flames the ideal gas law (IGL) and a real gas (RGL) equation of state (EOS) models have been employed to study the assumption of the unity Lewis (Le) number effects on the soot production/oxidation processes for four different operating pressures. An MPI FORTRAN code containing a semi-global soot production/oxidation model for a reduced Kerosene/Air mechanism (29-step, 10 species) has been used to create 2B DSS data. For the aim of verifying the applicability of the unity Le assumption for Kerosene/Air flames comparisons between unity and non-unity Lewis (Le) number flame predictions must possess statistically similar trends in not only the flame structure but also the soot properties. 1, 5 10 and 35 atm analyses of 2D DNS flame predictions of the RGL and the IGL EOS models have unveiled that the EOS coupled models with the unity-Le number mis-predicts the soot properties and the mean flame temperatures.

Özet

Bu çalısmada, dört farklı ortam basıncında kurum, oluşum ve yıkım süreçlerini incelemek amacıyla, yoğun kurum üreten Gazyağı/Hava alevleri, gerçek gaz (GG) ve ideal gaz (İG) hal denklemleri ve Lewis (Le) sayısının bir olarak kabul edildiği modeller ele alınmıştır. Yarı-genel kurum oluşum ve yıkım modelini içeren indirgenmiş Gazyağı/Hava mekanizması (29-adım, 10 çeşit gaz) 2 boyutlu (2B) Direk Sayısal Simülasyon (DNS) verilerini oluşturmak için MPI FORTRAN ile kodu yazılmış bir program kullanılmıştır. Le sayısının bire eşit kabul edildiği alev tahminlerinin, Le sayısının bire eşit olmadığı (genelleştirilmiş difüzyon) durumların sayısal sonuçlarından elde edilen alev yapısı ve kurum özelliklerinin istatiksel olarak benzerlik sağlayıp sağlamadığı araştırılmıştır. Bu bağlamda yapılan çalışmanın sonucunda, ortam basınçları 1, 5, 10 ve 35 atm olan Le sayısının bir olarak kabul edildiği GGLE ve İGLE modelleri ile üretilmiş 2B DNS alev tahminlerinin kurum özelliklerinin ve alev yapılarının yanlış hesaplanmasına yol açtığı belirlenmiştir.

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Cite This Article

KORUCU, A., MİLLER, R. (2023). Differential diffusion and pressure effects on heavily sooting 2D Kerosene/Air diffusion flames. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 39 Sayı: 1, 91–100. https://ajindex.com/articles/958612

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References (8)

  1. Foster J. (2009). A priori anlaysis of subgrid scalar phenomena and mass diffusion vectors in turbulent Hydrogen-Oxygen flames, Master’s thesis, Clemson University, Clemson, SC, USA Foster J. (2011). On simulation and modeling of turbulent non-premixed reacting shear flames at low and high pressure, Doctoral thesis., Clemson University, Clemson, SC, USA. Garnier E., Adams N., & Sagaut P. (2009). Large eddy simulation for compressible flows. Springer, USA. doi:10.1007/978-90-481-2819-8
  2. Germano M., Piomelli U., Moin P., & Cabot W.H. (1991). A dynamic subgrid-scale eddy viscosity model. Phys. of Fluids, 3, 1760–1765. doi: 10.1063/1.857955 Harstad K.G, Miller R.S, & Bellan J. (1997). Efficient high-pressure state equations. American Institute of Chemical Engineers Journals, 43, 1605-1610. doi: 10.1002/aic.690430624 Hewitt G.F. and J.C. Vassilicos (2005), Prediction of Turbulent Flow. Cambridge University Press Press, 2005.
  3. Kennedy I. M. (1997). Models of soot formation and oxidation. Prog. Energy Combust. Sci., 23, 95–132. doi: /10.1016/S0360-1285(97)00007-5
  4. Korucu A. (2016). Analysis of high Pressure H2/O2, H2/Air and Kerosene/Air reacting shear flows, Doctoral thesis, Clemson University, Clemson, SC, USA. Korucu A. & Miller R. (2018). Unity lewis number effects at atmospheric pressure kerosene/air flames. In: 14th International Combustion Symposium (INCOS2018);
  5. Karabuk, Turkey. Korucu A. & Miller R. (2019). Numerical analysis of real gas and pressure effects on 2D Kerosene/Air shear flames. In: 22nd Congress on Thermal Science and Technology (CTST 2019);
  6. Kocaeli, Turkey: 2019.
  7. Lignell, D.O., Chen, J.H, Smith, P.J., Lu, T.F., & Law, C.K. (2007). Direct numerical simulation of soot formation and transport in non-premixed turbulent ethylene flames. In: 5th US Combustion Meeting 1, (pp 520-554).
  8. San Diego, CA, USA. Malik N., Lovas T., & Mauss F. (2011). The effect of preferential diffusion on the soot initiation process in ethylene diffusion flames, Flow, Turbulence and Combustion, 87, 293-312. doi: 10.1007/s10494-011-9347-y. Martin M.P., Piomelli U., & Candler G.V. (2000). Subgrid-scale models for compressible large-eddy simulation. Theo. and Comp. Fluid Dyn., 13, 361–376. doi: 10.1007/PL00020896 Mauss F., Netzell K., & Lehtiniemi H. (2006). Aspects of modeling soot formation in turbulent diffusion flames, Combustion Science and Technology, 178, 1871 -1885. doi: 10.1080/00102200600790888 Meier W., Vyrodov A.O., Bergmann V., & Stricker W. (1996). Simultaneous ra