The intake manifold structural improvements of the dynamic supercharging air system of the piston engine adapted for aviation application

DOI: 10.34759/vst-2022-4-161-171

Аuthors

Baryshnikov S. I.^*, Kostyuchenkov A. N., Zelentsov A. A.

Central Institute of Aviation Motors named after P.I. Baranov, CIAM, 2, Aviamotornaya str., Moscow, 111116, Russia

*e-mail: stanislawish@ya.ru

Abstract

There is a demand nowadays for small aircraft engines of a power up to 500 hp. Piston engines possess competitive edge in this category due to their light weight, low fuel consumption and decent weight-to-power ratio.

The most feasible way of ensuring this demand consists in converting automobile engines to aviation application and standards. Aviation engines are running for the most part at greater crankshaft rotation frequency and higher loads. It leads to the necessity for conventional systems alteration, including inlet manifold.

Earlier, the adapted piston engine was developed. In the framework of the engine-demonstrator, the input manifold, ensuring dynamic supercharging, was installed. Its size and shape were non-optimal from the gas exchange viewpoint. That is why structural refining of the manifold was required.

The greatest problem with the conventional manifold consisted in the uneven power distribution among the cylinders, due to the difference in filling up to 20% from the average value. The manifold was being designed for the lab tests as well, and fitted poorly the aircraft layout.

The purpose of the presented research consisted in equalizing mass flow through each cylinder with achievement of more even filling, which would ensure more even operation. It was desirable as well to ensure more aerodynamic shape and minimize pressure losses.

The core method of flow analyzing in manifold was the 3D CFD modeling. The non-stationary RANS model with realizable k-epsilon turbulence model and enhanced EWT was employed.

The main problems, such as dead zones in the back part of the manifold, the swirl in the front one and mutual effect of the branch pipes were determined by the geometry analyzing.

The following solutions were applied: the dead zone filling; the front part expansion for the swirl dissipation, and separators introduction. Each solution was applied iteratively with the search of preferable dimension and geometry up to the potential solutions exhaustion.

The resulting manifold design allowed achieving 50% and 30% reduction of maximum and average air consumption correspondingly. More aerodynamic shape was achieved. Pressure losses changes were within the error margins.

Keywords:

gas turbine engines of narrow-body aircraft, combustion chamber workflow, gorenje technologies DOC, TAPS, RQL

References

1. Kuznetsov G.A., Kudryavtsev I.V., Krylov E.D. Inzhenernyi zhurnal: Nauka i innovatsii, 2018,
   9(81). DOI: 10.18698/2308-6033-2018-9-1801
2. Kuznetsov G.A. Bespilotnye letatel’nye apparaty s porshnevymi dvigatelyami. Komponovki i konstruktsii (Unmanned aviation vehicles with piston engines. Layouts and Structures), Moscow, Sputnik+ Company, 2010, 193 p.
3. Novichkov N.N. Bespilotnye letatel’nye apparaty mira: spravochnik (Unmanned aviation vehicles of the world: Reference Guide), Moscow, IA ARMS-TASS, 2012, 456 p.
4. Gordin M.V., Finkel’berg L.A., Semenov P.V. Aviatsionnye dvigateli, 2020, no. 1(6), pp. 7-14. DOI: 10.54349/26586061_2020_1_7
5. Chainov N.D., Krasnokutskii A.N., Myagkov L.L. Konstruirovanie i raschet porshnevykh dvigatelei (Piston engines design and calculation), Moscow, MGTU im. N.E. Baumana, 2018, 536 p.
6. Piancastelli L., Cassani S. On the Conversion of Automotive Engines for General Aviation. ARPN Journal of Engineering and Applied Sciences, 2017, vol. 12, no. 13, pp. 4196-4203. URL: http://www.arpnjournals.org/jeas/research_papers/rp_2017/jeas_0717_6190.pdf
7. Knepp J., Mullen R. Conversion of Production Automotive Engines for Aviation Use. SAE International Journal of Aerospace, Technical Paper 932606. DOI: 10.4271/932606
8. Finkel’berg L.A., Kostyuchenkov A.N., Zelentsov A.A. Aviatsionnye dvigateli, 2020, no. 1(6), pp. 15-22. DOI: 10.54349/26586061_2020_1_15
9. Matiukhin L.M. The fuel molar weight impact on filling, and indicator indices of a piston combustion engine. Aerospace MAI Journal, 2019, vol. 26, no. 3, pp. 113-123.
10. Moshkov P.A., Samokhin V.F. Experimental determination of piston engine share in the light propeller aircraft power plant total noise. Aerospace MAI Journal, 2016, vol. 23, no. 2, pp. 50-61.
11. RED-aircraft, https://red-aircraft.com/
12. Hiereth H., Prenninger P. Charging the Internal Combustion Engine. Springer-Verlag, Wien, 2007, 283 p.
13. Raimbault V., Migaud J., Chalet D., Bargende M. et al. Resonance Charging Applied to a Turbo Charged Gasoline Engine for Transient Behavior Enhancement at Low Engine Speed. 13th International Conference on Engines & Vehicles (21-25 June 2015; Port Jefferson, NY, USA). SAE Technical paper 2017-24-0146, 2017. DOI: 10.4271/2017-24-0146
14. Kavtaradze R.Z. Teoriya porshnevykh dvigatelei. Spetsial’nye glavy (Piston engine theory. Special chapters), 2nd ed., Moscow, MGTU im. N.E. Baumana, 2016, 589 p.
15. Pletcher R.H., Tannehill J.C., Anderson D.A. Computational Fluid Mechanics and Heat Transfer. CRC Press; 3rd edition, 2011, 774 p.
16. Durbin P.A., Petterson-Reif B.A. Statical theory and modeling for turbulent flows. John Wiley and Sons, West Sussex, United Kingdom, 2010, 374 p. DOI: 10.1002/9780470972076
17. Shih T.-H., Liou W.W., Shabbir A., Yang Z., Zhu J. A new k— е eddy viscosity model for high Reynolds number turbulent flows. Computers & Fluids, 1995, vol. 24, no. 3, pp. 227–238. DOI: 10.1016/0045-7930(94)00032-T
18. Kader B. Temperature and Concentration Profiles in Fully Turbulent Boundary Layers. International Journal of Heat and Mass Transfer, 1981, vol. 24, no. 9, pp. 1541–1544. DOI: 10.1016/0017-9310 (81)90220-9
19. Wolfshtein M. The velocity and temperature distribution in one-dimensional flow with turbulence augmentation and pressure gradient. International Journal of Heat and Mass Transfer, 1969, vol. 12,
    3, pp. 301–318. DOI: 10.1016/0017-9310 (69)90012-X
20. Ansys Fluent. © ANSYS, Inc. Southpointe, 2600 ANSYS Drive Canonsburg, PA 15317. Customer ID: 1039481.