Advertisement

Towards Clean Propulsion with Synthetic Fuels: Computational Aspects and Analysis

  • Mathis BodeEmail author
  • Marco Davidovic
  • Heinz Pitsch
Conference paper

Abstract

In order to support sustainable powertrain concepts, synthetic fuels show significant potential to be a promising solution for future mobility. It was found that \(\mathrm {CO_2}\) emissions during the combustion process of synthetic fuels can be reduced compared to conventional fuels and that sustainable fuel production pathways exists. Furthermore, it is possible to burn some synthetic fuels soot-free, which indirectly also eliminates the well-known soot-\(\mathrm {NO}_x\) tradeoff. However, in order to use the full potential of the new fuels, optimization of currently used injection systems needs to be performed. This is still challenging since fundamental properties are not known and pollutant formation is a multi-physics, multi-scale process. Therefore, the high-fidelity simulation framework CIAO is improved and optimized for predictive simulations of multiphase, reactive injections in complex geometries. Due to the large separation of scales, these simulations are only possible with current supercomputers. This work discusses the computational performance of the high-fidelity simulations especially focusing on vectorization, scaling, and input/output (I/O) on Hazel Hen (Cray XC40) supercomputer at the High Performance Computing Center Stuttgart (HLRS). Moreover, the impact of different internal nozzle flow initial conditions is shown, the effect of different chemical mechanisms studied, and the predictability of soot emissions investigated. The Spray A case defined by the Engine Combustion Network (ECN) is used as the target case due to the availability of experimental data for this injector.

Keywords

Large eddy simulation Multiphase flow Reactive flow Complex boundaries Engine Combustion Network 

Notes

Acknowledgements

The authors gratefully acknowledge support by Stefan Andersson (Cray), Björn Dick (HLRS, University of Stuttgart), Philipp Offenhäuser (HLRS, University of Stuttgart), Andreas Ruopp (HLRS, University of Stuttgart), and Jens Henrik Göbbert (JSC, FZ Jülich). Additionally, funding by the Cluster of Excellence “Tailor-made Fuels from Biomass” and computing time on the national supercomputer Cray XC40 at the HLRS under the grant number GCS-MRES are acknowledged. Data and support provided by Honda R&D and Argonne National Laboratory (Advanced Photon Source) are also kindly acknowledged.

Supplementary material

466604_1_En_12_MOESM1_ESM.mp4 (2.3 mb)
Supplementary material 1 (mp4 2347 KB)
466604_1_En_12_MOESM2_ESM.mp4 (1.3 mb)
Supplementary material 2 (mp4 1357 KB)
466604_1_En_12_MOESM3_ESM.mp4 (2.4 mb)
Supplementary material 3 (mp4 2462 KB)
466604_1_En_12_MOESM4_ESM.mp4 (2 mb)
Supplementary material 4 (mp4 2027 KB)
466604_1_En_12_MOESM5_ESM.mp4 (1.2 mb)
Supplementary material 5 (mp4 1191 KB)
466604_1_En_12_MOESM6_ESM.mp4 (1.8 mb)
Supplementary material 6 (mp4 1885 KB)
466604_1_En_12_MOESM7_ESM.mp4 (3.5 mb)
Supplementary material 7 (mp4 3633 KB)

Supplementary material 8 (mp4 3727 KB)

References

  1. 1.
    Engine combustion network (2018). https://ecn.sandia.gov
  2. 2.
  3. 3.
    National institute of standards and technology (2018). https://www.nist.gov
  4. 4.
    S.V. Apte, K. Mahesh, T. Lundgren, Accounting for finite-size effects in simulations of disperse particle-laden flows. Int. J. Multiph. Flow 34(3), 260–271 (2008)CrossRefGoogle Scholar
  5. 5.
    M. Bode, M. Davidovic, H. Pitsch, Multi-scale coupling for predictive injector simulations, in High-Performance Scientific Computing, ed. by E. Di Napoli, M.A. Hermanns, H. Iliev, A. Lintermann, A. Peyser (Springer, 2017), pp. 96–108Google Scholar
  6. 6.
    M. Bode, A. Deshmukh, J.H. Göbbert, H. Pitsch, Ciao: multiphysics, multiscale Navier-Stokes solver for turbulent reacting flows in complex geometries, in JUQUEEN Extreme Scaling Workshop 2016, ed. by D. Brömmel, W. Frings, B.J.N. Wylie (Springer, 2016), pp. 15–24Google Scholar
  7. 7.
    M. Bode, F. Diewald, D.O. Broll, J.F. Heyse, V. Le Chenadec, H. Pitsch, Influence of the injector geometry on primary breakup in diesel injector systems. SAE Technical Paper 2014-01-1427 (2014)Google Scholar
  8. 8.
    M. Bode, T. Falkenstein, M. Davidovic, H. Pitsch, H. Taniguchi, K. Murayama, T. Arima, S. Moon, J. Wang, A. Arioka, Effects of cavitation and hydraulic flip in 3-hole GDI injectors. SAE Int. J. Fuels Lubr. 10(2), 380–393 (2017)CrossRefGoogle Scholar
  9. 9.
    M. Bode, T. Falkenstein, V. Le Chenadec, S. Kang, H. Pitsch, T. Arima, H. Taniguchi, A new Euler/Lagrange approach for multiphase simulations of a multi-hole GDI injector. SAE Technical Paper 2015-01-0949 (2015)Google Scholar
  10. 10.
    M. Bode, T. Falkenstein, H. Pitsch, T. Kimijima, H. Taniguchi, T. Arima, Numerical study of the impact of cavitation on the spray processes during gasoline direct injection, in 13th Triennial International Conference on Liquid Atomization and Spray Systems (Tainan, Taiwan, 2015)Google Scholar
  11. 11.
    M. Bode, S. Satcunanathan, K. Maeda, T. Colonius, H. Pitsch, An equation of state tabulation approach for injectors with non-condensable gases: development and analysis, in 10th International Cavitation Symposium (Baltimore, USA, 2018)Google Scholar
  12. 12.
    S. Breitenfeld, J. Mainzer, R. Warren, File open, close, and flush performance issues in hdf5. White Paper (2018)Google Scholar
  13. 13.
    L. Cai, H. Pitsch, S.Y. Mohamed, V. Raman, J. Bugler, H. Curran, S. Mani Sarathy, Optimized reaction mechanism rate rules for ignition of normal alkanes. Combust. Flame 173, 468–482 (2016)CrossRefGoogle Scholar
  14. 14.
    M. Davidovic, T. Falkenstein, M. Bode, L. Cai, S. Kang, J. Hinrichs, H. Pitsch, LES of n-dodecane spray combustion using a multiple representative interactive flamelets model. Oil Gas Sci. Technol. Rev. IFP Energ. Nouv. 72(29) (2017)CrossRefGoogle Scholar
  15. 15.
    O. Desjardins, G. Blanquart, G. Balarac, H. Pitsch, High order conservative finite difference scheme for variable density low mach number turbulent flows. J. Comput. Phys. 227(15), 7125–7159 (2008)MathSciNetCrossRefGoogle Scholar
  16. 16.
    M. Germano, U. Piomelli, P. Moin, W.H. Cabot, A dynamic subgrid-scale eddy viscosity model. Phys. Fluids A Fluid Dyn. 3, 1760–1765 (1991)CrossRefGoogle Scholar
  17. 17.
    M. Gorokhovski, M. Herrmann, Modeling primary atomization. Annu. Rev. Fluid Mech. 40(1), 343–366 (2008)MathSciNetCrossRefGoogle Scholar
  18. 18.
    F. Hu, M.Y. Hussaini, J.L. Manthey, Low-dissipation and low-dispersion Runge-Kutta schemes for computational acoustics. J. Comput. Phys. 124(1), 177–191 (1996)MathSciNetCrossRefGoogle Scholar
  19. 19.
    A.L. Kastengren, F.Z. Tilocco, C.F. Powell, J. Manin, L.M. Pickett, R. Payri, T. Bazyn, Engine combustion network (ECN): measurements of nozzle geometry and hydraulic behavior. At. Sprays 22(12), 1011–1052 (2012)CrossRefGoogle Scholar
  20. 20.
    P. Marmottant, E. Villermaux, On spray formation. J. Fluid Mech. 498, 73–111 (2004)CrossRefGoogle Scholar
  21. 21.
    R.S. Miller, K. Harstad, J. Bellan, Evaluation of equilibrium and non-equilibrium evaporation models for many-droplet gas-liquid flow simulations. Int. J. Multiph. Flow 24(6), 1025–1055 (1998)CrossRefGoogle Scholar
  22. 22.
    M.E. Mueller, G. Blanquart, H. Pitsch, Hybrid method of moments for modeling soot formation and growth. Combust. Flame 156(6), 1143–1155 (2009)CrossRefGoogle Scholar
  23. 23.
    A. Omari, B. Heuser, S. Pischinger, Potential of oxymethylenether-diesel blends for ultra-low emission engines. Fuel 209, 232–237 (2017)CrossRefGoogle Scholar
  24. 24.
    M.A. Patterson, R.D. Reitz, Modeling the effects of fuel spray characteristics on diesel engine combustion and emissions. SAE Technical Paper 980131 (1998)Google Scholar
  25. 25.
    L.M. Pickett, C.L. Genzale, G. Bruneaux, L.M. Malbec, L. Hermant, C. Christiansen, J. Schramm, Comparison of diesel spray combustion in different high-temperature, high-pressure facilities. SAE Int. J. Engines 3(2), 156–181 (2010)CrossRefGoogle Scholar
  26. 26.
    J. Shinjo, A. Umemura, Detailed simulation of primary atomization mechanisms in Diesel jet sprays (isolated identification of liquid jet tip effects). Proc. Combust. Inst. 33(2), 2089–2097 (2011)CrossRefGoogle Scholar
  27. 27.
    S.A. Skeen, J. Manin, L.M. Pickett, Simultaneous formaldehyde plif and high-speed schlieren imaging for ignition visualization in high-pressure spray flames. Proc. Combust. Inst. 35(3), 3167–3174 (2015)CrossRefGoogle Scholar
  28. 28.
    D. Stanescu, W.G. Habashi, 2N-storage low dissipation and dispersion Runge-Kutta schemes for computational acoustics. J. Comput. Phys. 143(2), 674–681 (1998)CrossRefGoogle Scholar
  29. 29.
    T. Yao, Y. Pei, B.J. Zhong, S. Som, T. Lu, K. Hong Luo, A compact skeletal mechanism for n-dodecane with optimized semi-global low-temperature chemistry for diesel engine simulations. Fuel 191, 339–349 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute for Combustion TechnologyRWTH Aachen UniversityAachenGermany

Personalised recommendations