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Optimization and Design of a Fully Instrumented Mach 12 Nozzle for the X3 Expansion Tube

  • P. ToniatoEmail author
  • D. E. Gildfind
  • P. A. Jacobs
  • R. G. Morgan
Conference paper

Abstract

This paper describes the optimization and design of a new Mach 12 hypersonic nozzle to be used in the X3 expansion tube. The contoured nozzle has been designed and built to accommodate large-scale models and reproduce constant Mach 12 flows to allow for scramjet testing. The requirements for this nozzle were a core flow of at least 300 mm and exit flow angles below 2°. A new optimization process has been developed, using a parallel Nelder-Mead method, and a new shape has been calculated where CFD analysis indicates the design objectives were successfully met. Off-design performance has been evaluated, and the nozzle has been shown to retain good core flow size, Mach number and low flow divergence for different inflow conditions.

Notes

Acknowledgements

This research is supported by an Australian Government Research Training Program (RTP) Scholarship and the Cooperative Research Centre for Space Environment Management (SERC Limited) through the Australian Government’s Cooperative Research Centre Programme. This research was undertaken with the assistance of resources from the National Computational Infrastructure (NCI), which is supported by the Australian Government. The authors finally wish to thank F. De Beurs and N. Duncan for technical assistance with the X3 hardware.

References

  1. 1.
    Doherty, L.J., Smart, M.K., and Mee, D.J. Experimental Testing of an Airframe Integrated 3-D Scramjet at True Mach 10 flight Conditions. in 19th AIAA International Space Planes and Hypersonic Systems and Technologies Conference. American Institute of Aeronautics and Astronautics (AIAA)Google Scholar
  2. 2.
    Wise, D., Experimental Investigation of a Three Dimensional Scramjet Engine at Hypervelocity Conditions. (University of Queensland, 2015). pp. 197–197Google Scholar
  3. 3.
    Sancho Ponce, J., Scramjet Testing at High Total Pressure. (University of Queensland, 2016)Google Scholar
  4. 4.
    Craddock, C.S., Computational Optimization of Scramjets and Shock Tunnel Nozzles. (University of Queensland, 1999)Google Scholar
  5. 5.
    Scott, M.P., Development and Modelling of Expansion Tubes. (University of Queensland, 2007)Google Scholar
  6. 6.
    Shope, F. Contour design techniques for super/hypersonic wind tunnel nozzles. in 24th AIAA Applied Aerodynamics Conference. American Institute of Aeronautics and Astronautics (AIAA)Google Scholar
  7. 7.
    R.S.M. Chue et al., Design of a Shock-Free Expansion Tunnel Nozzle in Hypulse. Shock Waves 13(4), 261–270 (2003)CrossRefGoogle Scholar
  8. 8.
    Erdos, J.I. and Bakos, R.J. Prospects for a quiet hypervelocity shock-expansion tunnel. in 25th Plasmadynamics and Lasers Conference. American Institute of Aeronautics and AstronauticsGoogle Scholar
  9. 9.
    McGilvray, M., Scramjet Testing at High Enthalpies in Expansion Tube Facilities. ( University of Queensland, 2008)Google Scholar
  10. 10.
    R.J. Gollan, P.A. Jacobs, About the formulation, verification and validation of the hypersonic flow solver Eilmer. Int. J. Numer. Meth. Fluids 73(1), 19–57 (2013)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Jacobs P. A., G.R.G.a.Z.F., Still Using Nenzf? That’s So 1960s, in International Workshop on Shock Tube Technologie. (Brisbane, 2011)Google Scholar
  12. 12.
    Wilcox, D. Formulation of the K-Omega turbulence model revisited, in 45th AIAA Aerospace Sciences Meeting and Exhibit. AIAAGoogle Scholar
  13. 13.
    Gupta, R. N., et al., A review of reaction rates and thermodynamic and transport properties for an 11-species air model for chemical and thermal nonequilibrium calculations to 30000 K, Technical Report NASA-RP-1232, NASA, (1990)Google Scholar
  14. 14.
    D. Lee, M. Wiswall, A parallel implementation of the simplex function minimization routine. Comput. Econ. 30(2), 171–187 (2007)CrossRefGoogle Scholar
  15. 15.
    R.G. Regis, C.A. Shoemaker, Constrained global optimization of expensive black box functions using radial basis functions. J. Glob. Optim. 31(1), 153–171 (2005)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • P. Toniato
    • 1
    Email author
  • D. E. Gildfind
    • 1
  • P. A. Jacobs
    • 1
  • R. G. Morgan
    • 1
  1. 1.School of Mechanical and Mining EngineeringUniversity of QueenslandSt Lucia, BrisbaneAustralia

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