Skip to main content
SpringerLink
Log in

Reacting LES@2030: Near Diskless and Near Real-Time Computing for Design?

  • Chapter
  • First Online:
Whither Turbulence and Big Data in the 21st Century?

  • 2034 Accesses

Abstract

The combustion research and design community is diverse and geographically distributed. It aims to provide a predictive understanding of the complex multiphysics, and multiscale processes that are present in a variety of systems such as transportation, propulsion, and power systems. Challenges involve treatment of turbulence, advanced fuels, multiphase flows, and catalytic systems, to name a few. A key objective is the construction of predictive models that can ultimately be assembled into engineering design tools for development and optimization of device-scale combustion systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. J.C. Bennett, H. Abbasi, P.-T. Bremer, R. Grout, A. Gyulassy, T. Jin, S. Klasky, H. Kolla, M. Parashar, V. Pascucci, et al., Combining in-situ and in-transit processing to enable extreme-scale scientific analysis, in 2012 International Conference for High Performance Computing, Networking, Storage and Analysis (SC) (Institute of Electrical and Electronics Engineers (IEEE), New Jersey 2012), pp. 1–9

    Google Scholar 

  2. J.H. Chen, Combustion co-design center: exascale simulation of combustion in turbulence application/proxy deep dive. Tech. Rep., The Technical Report Number SAND2012-8619C, Sandia National Laboratories, 2012

    Google Scholar 

  3. J.H. Chen, A. Choudhary, B. De Supinski, M. DeVries, E. Hawkes, S. Klasky, W. Liao, K. Ma, J. Mellor-Crummey, N. Podhorszki, et al., Terascale direct numerical simulations of turbulent combustion using S3D. Comput. Sci. Discov. 2 (1), 015001 (2009)

    Google Scholar 

  4. M. Colket, J. Heyne, M. Rumizen, J.T. Edwards, M. Gupta, W.M. Roquemore, J.P. Moder, J.M. Tishkoff, C. Li, An overview of the national jet fuels combustion program. AIAA-2016-0177, 1–24 (2016)

    Google Scholar 

  5. E.P.N. Duque, B.J. Whitlock, C.P. Stone, R. Ranjan, S. Menon, The impact of in situ data processing and analytics upon weak scaling of CFD solvers and workflows, in 27th International Conference on Parallel Computational Fluid Dynamics (2015), pp. 1–8

    Google Scholar 

  6. T. Echekki, E. Mastorakos, Turbulent Combustion Modeling: Advances, New Trends and Perspectives, vol. 95 (Springer Science & Business Media, New York, 2010)

    MATH  Google Scholar 

  7. N. Fabian, K. Moreland, D. Thompson, A.C. Bauer, P. Marion, B. Geveci, M. Rasquin, K.E. Jan, The paraview coprocessing library: a scalable, general purpose in situ visualization library, in 2011 IEEE Symposium on Large Data Analysis and Visualization (LDAV) (Institute of Electrical and Electronics Engineers (IEEE), New Jersey, 2011), pp. 89–96

    Book  Google Scholar 

  8. X. Guo, M. Lange, G. Gorman, L. Mitchell, M. Weiland, Developing a scalable hybrid MPI/OpenMP unstructured finite element model. Comput. Fluids 110, 227–234 (2015)

    Article  Google Scholar 

  9. E.R. Hawkes, O. Chatakonda, H. Kolla, A.R. Kerstein, J.H. Chen, A petascale direct numerical simulation study of the modelling of flame wrinkling for large-eddy simulations in intense turbulence. Combust. Flame 159 (8), 2690–2703 (2012)

    Article  Google Scholar 

  10. J. Janicka, A. Sadiki, M. Schäfer, C. Heeger, Flow and Combustion in Advanced Gas Turbine Combustors (Springer Science & Business Media, New York 2012)

    Google Scholar 

  11. J. Jeffers, J. Reinders, Intel Xeon Phi Coprocessor High-Performance Programming (Newnes, Elsevier Inc., New York, 2013)

    Google Scholar 

  12. G. Lacaze, A. Misdariis, A. Ruiz, J.C. Oefelein, Analysis of high-pressure diesel fuel injection processes using LES with real-fluid thermodynamics and transport. Proc. Combust. Inst. 35, 1603–1611 (2015 )

    Article  Google Scholar 

  13. J.F. Lofstead, S. Klasky, K. Schwan, N. Podhorszki, C. Jin, Flexible IO and integration for scientific codes through the adaptable IO system (ADIOS), in Proceedings of the 6th International Workshop on Challenges of Large Applications in Distributed Environments (Association for Computing Machinery, New York, 2008), pp. 15–24

    Google Scholar 

  14. K.-L. Ma, C. Wang, H. Yu, A. Tikhonova, In-situ processing and visualization for ultrascale simulations. J. Phys.: Conf. Ser. 78, 012043 (2007). IOP Publishing

    Google Scholar 

  15. M. Masquelet, S. Menon, Y. Jin, R. Friedrich, Simulation of unsteady combustion in a LOX-GH2 fueled rocket engine. Aerosp. Sci. Technol. 13 (8), 466–474 (2009)

    Article  Google Scholar 

  16. S. Menon, Co emission and combustion dynamics near lean-blowout in gas turbine engines, in ASME Turbo Expo 2004: Power for Land, Sea, and Air (American Society of Mechanical Engineers, New York, 2004), pp. 153–160

    Google Scholar 

  17. J.C. Oefelein, V. Yang, Modeling high-pressure mixing and combustion processes in liquid rocket engines. J. Propul. Power 14 (5), 843–857 (1998)

    Article  Google Scholar 

  18. R. Ranjan, A. Panchal, G. Hannebique, S. Menon, Towards numerical prediction of jet fuels sensitivity of flame dynamics in a swirl spray combustion system, in 52nd AIAA Joint Propulsion Conference (Salt Lake City, 2016)

    Google Scholar 

  19. S. Saini, H. Jin, D. Jespersen, S. Cheung, J. Djomehri, J. Chang, R. Hood, Early multi-node performance evaluation of a knights corner (KNC) based NASA supercomputer, in Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International (Institute of Electrical and Electronics Engineers (IEEE), New Jersey 2015), pp. 57–67

    Google Scholar 

  20. J. Soumagne, J. Biddiscombe, J. Clarke, An HDF5 MPI virtual file driver for parallel in-situ post-processing, in Recent Advances in the Message Passing Interface (Springer-Verlag, Berlin Heidelberg 2010), pp. 62–71

    Google Scholar 

  21. S. Srinivasan, R. Ranjan, S. Menon, Flame dynamics during combustion instability in a high-pressure, shear-coaxial injector combustor. Flow Turbul. Combust. 94 (1), 237–262 (2015 )

    Article  Google Scholar 

  22. J. Tölke, M. Krafczyk, TeraFLOP computing on a desktop PC with GPUs for 3D CFD. Int. J. Comput. Fluid Dyn. 22 (7), 443–456 (2008)

    Article  MATH  Google Scholar 

  23. R. Yokota, L.A. Barba, A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems. Int. J. High Perform. Comput. Appl. 26 (4), 337–346 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, GA, USA

    S. Menon & R. Ranjan

  2. Sandia National Laboratories, Livermore, CA, USA

    J. C. Oefelein

Authors
  1. S. Menon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Ranjan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. C. Oefelein
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Menon .

Editor information

Editors and Affiliations

  1. Department of Mechanical and Materials Engineering, Queen’s University, Kingston, Ontario, Canada

    Andrew Pollard

  2. Department of Mechanical Engineering, Texas Tech University, Lubbock, Texas, USA

    Luciano Castillo

  3. Department of Mechanical Engineering, University of Rouen, Mont-Saint-Aignan, France

    Luminita Danaila

  4. College of Engineering and Computer Science, Syracuse University, Syracuse, New York, USA

    Mark Glauser

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Menon, S., Ranjan, R., Oefelein, J.C. (2017). Reacting LES@2030: Near Diskless and Near Real-Time Computing for Design?. In: Pollard, A., Castillo, L., Danaila, L., Glauser, M. (eds) Whither Turbulence and Big Data in the 21st Century?. Springer, Cham. https://doi.org/10.1007/978-3-319-41217-7_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-41217-7_29

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41215-3

  • Online ISBN: 978-3-319-41217-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation