Skip to main content

Advertisement

SpringerLink
Log in

Investigation and optimization of appendage influence on the hydrodynamic performance of AUVs

  • Original article
  • Published:
Journal of Marine Science and Technology Aims and scope Submit manuscript

Abstract

Navigational range is an important attribute of autonomous underwater vehicles (AUVs), and drag reduction efforts have been pursued to improve overall efficiency. Improved efficiency results in a more capable vehicle over all. Historically, the majority of research focused on drag reduction has been concentrated on the optimization of vehicle hull geometry. The influence of the hull appendages on drag, however, has been largely ignored owing to their smaller size. In this study, the impacts of appendage size and position on vehicle drag are investigated using a computational fluid dynamics method. The results indicate that appendages increase more drag because of their impact on the development of turbulence. The investigation of the interactions between multiple appendages fixed on a vehicle hull shows that optimization is necessary for drag reduction. This paper presents an arrangement optimization method for AUV appendages based on the Kriging approximation model and the multi-island genetic algorithm. The results of the optimization show that appendage influence on hydrodynamic performance is directly proportional to its size, and that a distributed arrangement is beneficial for drag reduction.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Yamamoto I (2015) Research on next autonomous underwater vehicle for longer distance cruising. IFAC-PapersOnLine 48(2):173–176

    Article  Google Scholar 

  2. Vasudev K, Sharma R, Bhattacharyya S (2014) A CAGD + CFD integrated optimization model for design of AUVs. In: IEEE OCEANS 2014, TAIPEI, pp 1–8

  3. Stevenson P, Furlong M, Dormer D (2007) AUV shapes-combining the practical and hydrodynamic considerations. In: IEEE OCEANS 2007, Europe, pp 1–6

  4. Schweyher H, Lutz T, Wagner S (1996) An optimization tool for axisymmetric bodies of minimum drag. In: 2nd international airship conference, Stuttgart/Friedrichshafen, pp 1–8

  5. Myring DF (1976) A theoretical study of body drag in subcritical axisymmetric flow. Aeronaut Q 27(3):186–194

    Article  Google Scholar 

  6. Gao T et al (2016) Hull shape optimization for autonomous underwater vehicles using CFD. Eng Appl Comput Fluid Mech 10(1):601–609

    Google Scholar 

  7. Allen B, Vorus WS, Prestero T (2000) Propulsion system performance enhancements on REMUS AUVs. In: IEEE OCEANS 2000 MTS/IEEE conference and exhibition, pp 1869–1873

  8. Groves NC, Huang TT, Chang MS (1989) Geometric characteristics of DARPA suboff models: (DTRC Model Nos. 5470 and 5471). David Taylor Research Center, Bremerton

    Google Scholar 

  9. OpenCFD OpenFOAM (2012) The open source CFD toolkit user guide. OpenFOAM Foundation, Dordrecht

    Google Scholar 

  10. Wu X et al (2015) An effective CFD approach for marine-vehicle maneuvering simulation based on the hybrid reference frames method. Ocean Eng 109:83–92

    Article  Google Scholar 

  11. Dantas JLD, Barros EAd (2013) Numerical analysis of control surface effects on AUV manoeuvrability. Appl Ocean Res 42:168–181

    Article  Google Scholar 

  12. Gao T et al (2018) A time-efficient CFD approach for hydrodynamic coefficient determination and model simplification of submarine. Ocean Eng 154:16–26

    Article  Google Scholar 

  13. Liu H-L, Huang TT (1998) Summary of DARPA SUBOFF experimental program data. DTIC Document, pp 1–28

  14. Wang G et al (2007) Dynamics simulation and optimization of multibody system with random parameters. In: International conference on mechanical engineering and mechanics 2007, pp 1019–1023

  15. Ahmadi M et al (2005) Application of the central composite design and response surface methodology to the advanced treatment of olive oil processing wastewater using Fenton’s peroxidation. J Hazard Mater 123(1):187–195

    Article  Google Scholar 

  16. Hedayat AS, Sloane NJA, Stufken J (1999) Orthogonal arrays: theory and applications. Springer Science & Business Media, Berlin

    Book  MATH  Google Scholar 

  17. Fang K-T et al (2000) Uniform design: theory and application. Technometrics 42(3):237–248

    Article  MathSciNet  MATH  Google Scholar 

  18. Tang B (2008) Latin hypercube designs. In: Ruggeri F, Kenett RS, Faltin FW (eds) Encyclopedia of statistics in quality and reliability. Wiley, Chichester

    Google Scholar 

  19. Park J-S (1994) Optimal latin-hypercube designs for computer experiments. J Stat Plan Inference 39(1):95–111

    Article  MathSciNet  MATH  Google Scholar 

  20. Wang W et al (2011) Parameters optimization of laser shot peening based on multi-island genetic algorithm. Appl Mech Mater 43:387–390

    Article  Google Scholar 

  21. Hu X et al (2014) Optimization design of satellite separation systems based on multi-island genetic algorithm. Adv Space Res 53(5):870–876

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by The National Key Research and Development Program of China (Grant number 2016YFC0300802), and the State Key Laboratory of Robotics of China (Grant number 2017-Z08).

Author information

Authors and Affiliations

  1. State key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China

    Yaxing Wang & Yuangui Tang

  2. Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, 150001, China

    Ting Gao & Yongjie Pang

Authors
  1. Yaxing Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ting Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yongjie Pang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuangui Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yaxing Wang.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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). https://doi.org/10.1007/s00773-018-0558-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00773-018-0558-y

Keywords

Search

Navigation