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Analysis of Supersonic Axisymmetric Air Intake in Off-Design Mode

Conference paper
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Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 680)

Abstract

The most important issue in the design of a perspective aircraft is the development of a highly efficient power plant. One of the factors affecting its efficiency is the choice of air intake. The interest in this task is due to the fact that the operation of the air intake control program in various flight modes has a huge impact on the performance of the air intake device and, as a result, the power plant as a whole. The choice of the regulatory program is one of the most important types of work at the stage of forming the initial data when designing the power plants of aircraft (Bakulev et al. in Theory, calculation and design of aircraft engines and power plants, MAI, Moscow, 2013). The use of numerical modeling to solve various gas-dynamic problems allows us to expand the research range, and therefore, significantly reduce the number of experiments when practicing an air intake device. One of these tasks is to determine the characteristics of an air intake device in a wide range of flight speeds of aircraft. In this paper, we consider a supersonic axisymmetric three-shock air intake device of an external type of compression, numerical simulation of which was carried out in an application package for various operating modes. Based on the results of numerical modeling of the air intake device, a comparison is made to verify the design model, a solution is obtained to determine the optimum point for minimum losses in the off-design operation mode of the air intake device by changing the position of the central body without changing its geometry.

Keywords

Shock wave Air intake CFD 

References

  1. 1.
    Bakulev VI, Golubev VA, Nechaev YN (2013) Theory, calculation and design of aircraft engines and power plants. MAI, Moscow, p 688Google Scholar
  2. 2.
    Sazonov AI (2011) Design and operation of aircraft engines, lecture notes. UVAU GA (I), p 8Google Scholar
  3. 3.
    Nechaev YK, Fedorov RM, Kotovsky VKh, Polyak VA (2005) Theory of aircraft engines. VVIA named prof. Zhukovskiy NE, pp 47–64Google Scholar
  4. 4.
    Akopov MG, Snipes BI, Dolgachev VG. Gas dynamics. Mashinostroenie, pp 56–712Google Scholar
  5. 5.
    Kandasamy R, Gunasekaran K, Sulaiman HH (2011) Scaling group transformation on fluid flow with varible steam conditions. Int J Non-Linear Mech 46(7):976–985CrossRefGoogle Scholar
  6. 6.
    Luers AS (2003) Flow control techniques in a Serpentine inlet. Springer, V.25(5):325Google Scholar
  7. 7.
    Gea LM, Nyugen S (2015) CFD simulation of S-duct test case using overset meshes. Springer 35(2):569Google Scholar
  8. 8.
    Andersson B, Andersson R, Sudio R. Computational fluid dynamics for engineers. Cambridge University Press, p 86Google Scholar
  9. 9.
    Molchanov AM (2019) Thermophysics and fluid dynamics. OSF Preprints, p 160Google Scholar
  10. 10.
    Molchanov AM (2019) Numerical method for solving the Navier-Stokes equations. OSF Preprints, p 139Google Scholar
  11. 11.
    Tarik AS (2010) Engineering thermodynamics. Publishing ApS, p 104Google Scholar
  12. 12.
    Nag PK (2006) Basic and applied thermodynamics. McGraw Hill, p 81Google Scholar
  13. 13.
    ANSYS Inc. (2010) ANSYS modeling and meshing guide. ANSYS release 13.0. Documentation Inc., p 280Google Scholar
  14. 14.
    Fletcher K (1991) Computational methods in fluid dynamics: part 2. Mir, p 512Google Scholar
  15. 15.
    Farrashkhalvat M, Miles JP (2003) Basic structured grid generation with an introduction to unstructured grid generation. Laserwords Private Limited, Oxford (India), p 242Google Scholar
  16. 16.
    Egorov IN, Kuzmenko ML, Shmotin YN (2005) Increasing of air engine efficiency basing on optimization technology. Int Semin—Aero India 2005, Bangalore 57(1):58–72Google Scholar

Copyright information

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Moscow Aviation InstituteMoscowRussia

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