A CFD study on the correlation between the skew angle and blade number of hydrodynamic performance of a submarine propeller

  • Rahim MalmirEmail author
Technical Paper


In the present study, the correlation between skew angle and blade number on the hydrodynamic performance of a submarine propeller is numerically investigated using computational fluid dynamics. For this purpose, three different blade numbers (3, 5 and 7 blades) and four different skew angles which vary from 0° to 52° are considered based on the INSEAN E1619 propeller model as the main geometry. Three-dimensional numerical simulation is based on Unsteady Reynolds-Averaged Navier–Stokes equations combined with SST kω turbulence model. The hydrodynamic coefficients and efficiency are compared against the experimental and numerical results at various advance coefficients (J), and good agreement is achieved. Based on the results, by increasing the blade number, hydrodynamic coefficients are improved. The interaction between 7 blades dissipates the negative wake region in locations near the propeller blades which leads to produce higher hydrodynamic efficiency compared to other propellers. The maximum torque coefficient is generated by the propeller with 7 blades which is enhanced by about 11.8% compared to the propeller with 3 blades at J = 0.88. In addition, lower skew angle gives slightly higher performance than the high skew angle propeller. In overall, hydrodynamic efficiency of the propeller with a skew angle equal to 0° is enhanced by about 19.4% compared to the propeller with skew angles equal to 52° at J = 0.88.


Propeller Skew angle Blade number Hydrodynamic Computational fluid dynamics (CFD) 

List of symbols


Italian ship model basin


David Taylor model basin


Moving reference frame


Torque coefficient


Thrust coefficient


Dimensionless wall distance


Fluid density (kg/m3)


Advance velocity (m/s)


Kronecker delta


Diameter (mm)


Chord length (mm)


Hydrodynamic efficiency


Advance coefficient


Velocity (m/s)


Viscosity (kg/m s)


Compliance with ethical standards

Conflict of interest

The author declares that he has no conflict of interest.


  1. 1.
    Elghorab MA, Aly AAEA, Elwetedy AS, Kotb MA (2013) Experimental study of open water non-series marine propeller performance. In: Proceedings of world academy of science, engineering and technology, no. 78Google Scholar
  2. 2.
    Nouri NM, Mohammadi S (2016) A multi-objective approach for determining the number of blades on a NACA marine propeller. Brodogr Teor Praksa Brodogr Pomor teh 67(2):15–32Google Scholar
  3. 3.
    Balaras E, Schroeder S, Posa A (2015) Large-eddy simulations of submarine propellers. J Ship Res 59(4):227–237CrossRefGoogle Scholar
  4. 4.
    Da-Qing LI (2006) Validation of RANS predictions of open water performance of a highly skewed propeller with experiments. J Hydrodyn Ser B 18(3):520–528CrossRefGoogle Scholar
  5. 5.
    Hayati AN, Hashemi SM, Shams M (2012) A study on the effect of the rake angle on the performance of marine propellers. Proc Inst Mech Eng Part C J Mech Eng Sci 226(4):940–955CrossRefGoogle Scholar
  6. 6.
    Ji B, Luo X, Wang X, Peng X, Wu Y, Xu H (2011) Unsteady numerical simulation of cavitating turbulent flow around a highly skewed model marine propeller. J Fluids Eng 133(1):011102CrossRefGoogle Scholar
  7. 7.
    Peng HH, Qiu W, Ni S (2013) Effect of turbulence models on RANS computation of propeller vortex flow. Ocean Eng 72:304–317CrossRefGoogle Scholar
  8. 8.
    Rhee SH, Koutsavdis E (2005) Two-dimensional simulation of unsteady marine propulsor blade flow using dynamic meshing techniques. Comput Fluids 34(10):1152–1172CrossRefGoogle Scholar
  9. 9.
    Chen B (1999) Computational fluid dynamics of four-quadrant marine-propulsor flow. J Ship Res 43(4):218–228Google Scholar
  10. 10.
    Kawamura T (2006) Simulation of unsteady cavitating flow around marine propeller using a RANS CFD code. In: 6th International symposium on cavitation, Wageningen, NederlandGoogle Scholar
  11. 11.
    Rhee SH, Joshi S (2005) Computational validation for flow around a marine propeller using unstructured mesh based Navier–Stokes solver. JSME Int J Ser B Fluids Therm Eng 48(3):562–570CrossRefGoogle Scholar
  12. 12.
    Hayati AN, Hashemi SM, Shams M (2013) A study on the behind-hull performance of marine propellers astern autonomous underwater vehicles at diverse angles of attack. Ocean Eng 59:152–163CrossRefGoogle Scholar
  13. 13.
    Nouri NM, Mohammadi S (2018) Numerical investigation of the effects of camber ratio on the hydrodynamic performance of a marine propeller. Ocean Eng 148:632–636CrossRefGoogle Scholar
  14. 14.
    Wang LZ, Guo CY, Su YM, Wu TC (2018) A numerical study on the correlation between the evolution of propeller trailing vortex wake and skew of propellers. Int J Nav Archit Ocean Eng 10(2):212–224CrossRefGoogle Scholar
  15. 15.
    Chase N, Carrica PM (2013) Submarine propeller computations and application to self-propulsion of DARPA Suboff. Ocean Eng 60:68–80CrossRefGoogle Scholar
  16. 16.
    Wang Y, Abdel-Maksoud M, Song B (2017) Simulating marine propellers with vortex particle method. Phys Fluids 29(1):017103CrossRefGoogle Scholar
  17. 17.
    Hong Y, Wilson PA, He XD, Wang RG (2017) Numerical analysis and performance comparison of the same series of composite propellers. Ocean Eng 144:211–223CrossRefGoogle Scholar
  18. 18.
    Posa A, Balaras E (2018) Large-Eddy Simulations of a notional submarine in towed and self-propelled configurations. Comput Fluids 165:116–126MathSciNetCrossRefGoogle Scholar
  19. 19.
    Felli M, Di Felice F, Guj G, Camussi R (2006) Analysis of the propeller wake evolution by pressure and velocity phase measurements. Exp Fluids 41(3):441–451CrossRefGoogle Scholar
  20. 20.
    Paik BG, Kim J, Park YH, Kim KS, Yu KK (2007) Analysis of wake behind a rotating propeller using PIV technique in a cavitation tunnel. Ocean Eng 34(3-4):594–604CrossRefGoogle Scholar
  21. 21.
    Jang H, Mahesh K (2013) Large eddy simulation of flow around a reverse rotating propeller. J Fluid Mech 729:151–179CrossRefGoogle Scholar
  22. 22.
    Di Felice F, Felli M, Liefvendahl M, Svennberg U (2009) Numerical and experimental analysis of the wake behavior of a generic submarine propeller. In: Proceedings of the first international symposium on marine propulsors SMP’09, Trondheim, NorwayGoogle Scholar
  23. 23.
    Özden MC, Gürkan AY, Özden YA, Canyurt TG, Korkut E (2016) Underwater radiated noise prediction for a submarine propeller in different flow conditions. Ocean Eng 126:488–500CrossRefGoogle Scholar
  24. 24.
    Watanabe T, Kawamura T, Takekoshi Y, Maeda M, Rhee SH (2003) Simulation of steady and unsteady cavitation on a marine propeller using a RANS CFD code. In: Proceedings of the fifth international symposium on cavitationGoogle Scholar
  25. 25.
    Fatahian E, Nichkoohi AL, Fatahian H (2019) Numerical study of the effect of suction at a compressible and high Reynolds number flow to control the flow separation over Naca 2415 airfoil. Prog Comput Fluid Dyn Int J 19(3):170CrossRefGoogle Scholar
  26. 26.
    Fatahian H, Fatahian E, Nimvari ME (2018) Improving efficiency of conventional and square cyclones using different configurations of the laminarizer. Powder Technol 339:232–243CrossRefGoogle Scholar
  27. 27.
    Fatahian H, Salarian H, Eshagh Nimvari M, Fatahian E (2018) Numerical study of suction and blowing approaches to control flow over a compressor cascade in turbulent flow regime. Int J Automot Mech Eng. CrossRefGoogle Scholar
  28. 28.
    Martínez-Calle J, Balbona-Calvo L, González-Pérez J, Blanco-Marigorta E (2002) An open water numerical model for a marine propeller: a comparison with experimental data. ASME 2002 Joint US-European fluids engineering division conference, American Society of Mechanical EngineersGoogle Scholar
  29. 29.
    Benini E (2004) Significance of blade element theory in performance prediction of marine propellers. Ocean Eng 31(8-9):957–974CrossRefGoogle Scholar
  30. 30.
    Menter FR (1994) Two-equation Eddy-viscosity turbulence models for engineering applications. AIAA J 32(8):1598–1605CrossRefGoogle Scholar
  31. 31.
    Huang S, Zhu XY, Guo CY, Chang X (2007) CFD simulation of propeller and rudder performance when using additional thrust fins. J Mar Sci Appl 6(4):27–31CrossRefGoogle Scholar
  32. 32.
    Kim MC, Chun HH, Kang YD (2004) Design and experimental study on a new concept of Preswirl stator as an efficient energy-saving device for slow speed full body ship. Trans Soc Nav Archit Mar Eng 112:111–121Google Scholar
  33. 33.
    Boucetta D, Imine O (2016) Numerical simulation of the flow around marine propeller series. J Phys Sci Appl 6(3):55–61Google Scholar
  34. 34.
    Ekinci S (2011) A practical approach for design of marine propellers with systematic propeller series. Brodogradnja: Teorija i praksa brodogradnje i pomorske tehnike 62(2):123–129Google Scholar
  35. 35.
    Gaafary M, El-Kilani H, Moustafa M (2011) Optimum design of B-series marine propellers. Alex Eng J 50(1):13–18CrossRefGoogle Scholar
  36. 36.
    Molland AF, Carlton J (2012) Marine propellers and propulsion. Butterworth-Heinemann 6(1):79–82Google Scholar
  37. 37.
    Ismail KAR, Rosolen CVAG (2019) Effects of the airfoil section, the chord and pitch distributions on the aerodynamic performance of the propeller. J Braz Soc Mech Sci Eng 41(3):131. CrossRefGoogle Scholar
  38. 38.
    Ghassemi H, Ghadimi P (2011) Hydrodynamic efficiency improvement of the high skew propeller for the underwater vehicle under surface and submerged conditions. J Ocean Univ China 10(4):314–324CrossRefGoogle Scholar

Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringImam Khomeini University of Maritime SciencesNowshahrIran

Personalised recommendations