Advertisement

Improving the hydrodynamic performance of the SUBOFF bare hull model: a CFD approach

  • Kambiz DivsalarEmail author
Research Paper
First Online:
  • 28 Downloads

Abstract

The main aims of this study are to investigate the hydrodynamic performance of an autonomous underwater vehicle (AUV), calculate its hydrodynamic coefficients, and consider the flow characteristics of underwater bodies. In addition, three important parts of the SUBOFF bare hull, namely the main body, nose, and tail, are modified and redesigned to improve its hydrodynamic performance. A three-dimensional (3D) simulation is carried out using the computational fluid dynamics (CFD) method. To simulate turbulence, the k–ω shear stress transport (SST) model is employed, due to its good prediction capability at reasonable computational cost. Considering the effects of the length-to-diameter ratio (LTDR) and the nose and tail shapes on the hydrodynamic coefficients, it is concluded that a hull shape with bullet nose and sharp tail with LTDR equal to 7.14 performs better than the SUBOFF model. The final proposed model shows lower drag by about 14.9% at u = 1.5 m·s−1. Moreover, it produces 8 times more lift than the SUBOFF model at u = 6.1 m·s−1. These effects are due to the attachment of the fluid flow at the tail area of the hull, which weakens the wake region.

Keywords

Autonomous underwater vehicle Computational fluid dynamics Hydrodynamic performance Drag Turbulence model Hull shape 

List of symbols

F

Body force

D

Diameter

y+

Dimensionless wall distance

CD

Drag coefficient

ρ

Fluid density

gi

Gravitational acceleration

δij

Kronecker delta

L

Length

LTDR

Length-to-diameter ratio

CL

Lift coefficient

Lm

Main body length

Ln

Nose length

CM

Pitching moment coefficient

P

Pressure

CP

Pressure coefficient

Re

Reynolds number

τij

Reynolds stress tensor

ω

Specific rate of dissipation

Lt

Tail length

k

Turbulent kinetic energy

u

Velocity

μ

Viscosity

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

References

  1. 1.
    Newman, P., Westwood, R., Westwood, J.: Market prospects for AUVs. Mar. Technol. Rep. 50, 1–15 (2007)Google Scholar
  2. 2.
    Wernli, R.L.: AUVs-the maturity of the technology. In: Oceans’ 99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and Exhibition. Conference Proceedings (IEEE Cat. No. 99CH37008), pp. 1–20 (1999)Google Scholar
  3. 3.
    Joung, T., Sammut, K., He, F., et al.: A study on the design optimization of an AUV by using computational fluid dynamic analysis. In: The Nineteenth International Offshore and Polar Engineering Conference. International Society of Offshore and Polar Engineers (2009)Google Scholar
  4. 4.
    De Barros, E.A., Pascoal, A., De Sá, E.: Progress towards a method for predicting AUV derivatives. In: Proceedings of IFAC Manoeuvring Control Marine Crafts, pp. 1–12 (2006)Google Scholar
  5. 5.
    Javaid, M.Y., Ovinis, M., Hashim, F.B., et al.: Effect of wing form on the hydrodynamic characteristics and dynamic stability of an underwater glider. Int. J. Nav. Arch. Ocean Eng. 9, 382–389 (2017)CrossRefGoogle Scholar
  6. 6.
    Stern, F., Yang, J., Wang, Z., et al.: Computational ship hydrodynamics: nowadays and way forward. Int. Shipbuild. Prog. 60, 93–105 (2013)Google Scholar
  7. 7.
    Lin, X., He, G., He, X., et al.: Hydrodynamic studies on two wiggling hydrofoils in an oblique arrangement. Acta Mech. Sin. 34, 446–451 (2018)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Lin, L.M., Zhong, X.F., Wu, Y.X.: Effect of perforation on flow past a conic cylinder at Re = 100: vortex-shedding pattern and force history. Acta Mech. Sin. 34, 238–256 (2018)CrossRefGoogle Scholar
  9. 9.
    Fatahian, E., Nichkoohi, A.L., Fatahian, H.: 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. 19, 170–179 (2019)CrossRefGoogle Scholar
  10. 10.
    Gao, T., Wang, Y., Pang, Y., et al.: Hull shape optimization for autonomous underwater vehicles using CFD. Eng. Appl. Comput. Fluid Mech. 10, 599–607 (2016)Google Scholar
  11. 11.
    Willy, C.J.: Attitude control of an underwater vehicle subjected to waves. Diss. Massachusetts Institute of Technology and Woods Hole Oceanographic Institution (1994)Google Scholar
  12. 12.
    Milgram, J.H.: Strip theory for underwater vehicles in water of finite depth. J. Eng. Math. 58, 31–50 (2007)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Jagadeesh, P., Murali, K.: RANS predictions of free surface effects on axisymmetric underwater body. Eng. Appl. Comput. Fluid Mech. 4, 301–313 (2010)Google Scholar
  14. 14.
    Jagadeesh, P., Murali, K., Idichandy, V.G.: Experimental investigation of hydrodynamic force coefficients over AUV hull form. Ocean Eng. 36, 113–118 (2009)CrossRefGoogle Scholar
  15. 15.
    Stevenson, P., Furlong, M., Dormer, D.: AUV shapes-combining the practical and hydrodynamic considerations. Oceans 2007-Europe. IEEE (2007)Google Scholar
  16. 16.
    Sarkar, T., Sayer, P.G., Fraser, S.M.: A study of autonomous underwater vehicle hull forms using computational fluid dynamics. Int. J. Numer. Methods Fluids 25, 1301–1313 (1997)CrossRefGoogle Scholar
  17. 17.
    Wei, Z., Yu, Q., Yang, S.: Analysis of the resistance performance for different types of AUVs based on CFD. Chin. J. Ship Res. 9, 28–37 (2014)Google Scholar
  18. 18.
    Mansoorzadeh, S., Javanmard, E.: An investigation of free surface effects on drag and lift coefficients of an autonomous underwater vehicle (AUV) using computational and experimental fluid dynamics methods. J. Fluid Struct. 51, 161–171 (2014)CrossRefGoogle Scholar
  19. 19.
    Yamamoto, I.: Research on next autonomous underwater vehicle for longer distance cruising. IFAC-PapersOnLine 48, 173–176 (2015)CrossRefGoogle Scholar
  20. 20.
    Nouri, N.M., Zeinali, M., Jahangardy, Y.: AUV hull shape design based on desired pressure distribution. J. Mar. Sci. Technol. 21, 203–215 (2016)CrossRefGoogle Scholar
  21. 21.
    Wang, Y., Gao, T., Pang, Y., et al.: Investigation and optimization of appendage influence on the hydrodynamic performance of AUVs. J. Mar. Sci. Technol. 24, 297–305 (2019)CrossRefGoogle Scholar
  22. 22.
    Groves, N.C., Huang, T.T., Chang, M.S.: Geometric characteristics of DARPA (Defense Advanced Research Projects Agency) SUBOFF models (DTRC model numbers 5470 and 5471). No. DTRC/SHD-1298-01. David Taylor Research Center Bethesda MD Ship Hydromechanics Dept (1989)Google Scholar
  23. 23.
    Huang, T.T., Liu, H.L., Groves, N.C.: Experiments of the DARPA (Defense Advanced Research Projects Agency) Suboff Program. No. DTRC/SHD-1298-02. David Taylor Research Center Bethesda MD Ship Hydromechanics Dept (1989)Google Scholar
  24. 24.
    Gao, T., Wang, Y., Pang, Y., et al.: A time efficient CFD approach for hydrodynamic coefficient determination and model simplification of submarine. Ocean Eng. 154, 16–26 (2018)CrossRefGoogle Scholar
  25. 25.
    Hayati, A.N., Hashemi, S.M., Shams, M.: A study on the behind-hull performance of marine propellers astern autonomous underwater vehicles at diverse angles of attack. Ocean Eng. 59, 152–163 (2013)CrossRefGoogle Scholar
  26. 26.
    Dantas, J.L.D., De Barros, E.A.: Numerical analysis of control surface effects on AUV manoeuvrability. Appl. Ocean Res. 42, 168–181 (2013)CrossRefGoogle Scholar
  27. 27.
    Wu, X., Wang, Y., Huang, C., et al.: An effective CFD approach for marine-vehicle maneuvering simulation based on the hybrid reference frames method. Ocean Eng. 109, 83–92 (2015)CrossRefGoogle Scholar
  28. 28.
    Shojaeefard, M.H., Khorampanahi, A., Mirzaei, M.: RANS study of Strouhal number effects on the stability derivatives of an autonomous underwater vehicle. J. Braz. Soc. Mech. Sci. 40, 124–137 (2018)CrossRefGoogle Scholar
  29. 29.
    Menter, F.R.: Two-equation eddy-viscosity turbulence models for engineering applications. AIAA J. 32, 1598–1605 (1994)CrossRefGoogle Scholar
  30. 30.
    Liu, H.L., Huang, T.T.: Summary of DARPA SUBOFF experimental program data. No. CRDKNSWC/HD-1298-11. Naval Surface Warfare Center Carderock Div Bethesda MD Hydrodynamics Directorate (1998)Google Scholar
  31. 31.
    Sakthivel, R., Vengadesan, S., Bhattacharyya, S.K.: Application of non-linear k–e turbulence model in flow simulation over underwater axisymmetric hull at higher angle of attack. J. Nav. Arch. Mar. Eng. 8, 149–163 (2011)CrossRefGoogle Scholar
  32. 32.
    Alin, N., Bensow, R.E., Fureby, C., et al.: Current capabilities of DES and LES for submarines at straight course. J. Ship Res. 54, 184–196 (2010)Google Scholar
  33. 33.
    Manshadi, M.D., Hejranfar, K., Farajollahi, A.H.: Effect of vortex generators on hydrodynamic behavior of an underwater axisymmetric hull at high angles of attack. J. Vis. 20, 559–579 (2017)CrossRefGoogle Scholar
  34. 34.
    Moonesun, M., Mahdian, A., Korol, Y.M., et al.: Optimum L/D for submarine shape. Indian J. Geo-Mar. Sci. 45, 38–43 (2016)Google Scholar
  35. 35.
    Singh, Y., Bhattacharyya, S.K., Idichandy, V.G.: CFD approach to modelling, hydrodynamic analysis and motion characteristics of a laboratory underwater glider with experimental results. J. Ocean Eng. Sci. 2, 90–119 (2017)CrossRefGoogle Scholar

Copyright information

© The Chinese Society of Theoretical and Applied Mechanics and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

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

Personalised recommendations

Cite article

Buy options