Skip to main content
Log in

Multidisciplinary design optimization of underwater glider for improving endurance

  • Research Paper
  • Published:
Structural and Multidisciplinary Optimization Aims and scope Submit manuscript

Abstract

Underwater glider (UG) is widely applied for long-term ocean observation, the gliding range of which is mainly influenced by its design. In this paper, the design parameters that have obvious influence on the gliding range, including the buoyancy factor, compressibility of the pressure hull, hydrodynamic coefficients, and motion parameters, are selected based on the gliding range model of UG. Due to their complicate coupling relationship in the design of the UG, the multidisciplinary optimization (MDO) design framework integrating the collaborative optimization (CO) method and approximate model technology is adopted to optimize the key parameters by taking the gliding range as the optimization target. The results show that the optimization leads to an increase of the gliding range of Petrel-L as much as 83.3% when the hotel load is 0.5 W, which is verified by the sea trial. The optimization is applicable to other types of underwater gliders.

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

Access this article

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

Instant access to the full article PDF.

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
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

References

  • Alexandrov NM, Hussaini MY (1997) Multidisciplinary design optimization: state of the art siam. J Control Optim 1:941–946

    Google Scholar 

  • Andrew S, Scott KJ, Smith RN (2016) Enabling persistent autonomy for underwater gliders with ocean model predictions and terrain based navigation. Front Robot AI 3:23

    Google Scholar 

  • Barros EAD, Dantas JLD (2012) Effect of a propeller duct on AUV maneuverability. Ocean Eng 42:61–70

    Article  Google Scholar 

  • Bidoki M, Mortazavi M, Sabzehparvar M (2018) A new multidisciplinary robust design optimization framework for an autonomous underwater vehicle in system and tactic design. Proc IME M J Eng Marit Environ 233(3):918–936

    Google Scholar 

  • Bloebaum CL, Hajela P, Sobieszczanski-Sobieski J (1992) Non-hierarchic system decomposition in structural optimization. Eng Optim 19(3):171–186

    Article  Google Scholar 

  • Chen X, Wang P, Zhang D, Dong H (2018) Gradient-based multidisciplinary design optimization of an autonomous underwater vehicle. Appl Ocean Res 80:101–111

    Article  Google Scholar 

  • Chittick IR, Martins JRRA (2009) An asymmetric suboptimization approach to aerostructural optimization. Optim Eng 10(1):133–152

    Article  MathSciNet  Google Scholar 

  • Cramer EJ, Dennis JEJ, Frank PD, Lewis RM, Shubin GR (1994) Problem formulation for multidisciplinary optimization. SIAM J Optim 4(4):754–776

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  • Eriksen CC et al (2001) Seaglider: a long-range autonomous underwater vehicle for oceanographic research. IEEE J Ocean Eng 26:424–436

    Article  Google Scholar 

  • Forrester A, Sobester A, Keane AJ (2008) Engineering design via surrogate modelling world healtha practical guide. American Institute of Aeronautics & Astronautics, Chichester

  • Fu X, Lei L, Yang G, Li B (2018) Multi-objective shape optimization of autonomous underwater glider based on fast elitist non-dominated sorting genetic algorithm. Ocean Eng 157:339–349

    Article  Google Scholar 

  • Gao T, Wang Y, Pang Y, Cao J (2016) Hull shape optimization for autonomous underwater vehicles using CFD. Eng Appl Comput Fluid Mech 10(1):599–607

    Google Scholar 

  • Graver JG (2005) Underwater gliders: dynamics, control and design. Ph.D dissertation, Princeton University

  • Haftka RT (1985) Simultaneous analysis and design. AIAA Journal 23(7):1099–1103

  • He Y, Song B, Dong H (2018) Multi-objective optimization design for the multi-bubble pressure cabin in BWB underwater glider. Int J Naval Archit Ocean Eng 10(4):439–449

    Article  Google Scholar 

  • Huang Z, Liu Y, Zheng H, Wang S, Ma J, Liu Y (2018) A self-searching optimal ADRC for the pitch angle control of an underwater thermal glider in the vertical plane motion. Ocean Eng 159:98–111

    Article  Google Scholar 

  • Jenkins SA et al. (2003) Underwater glider system study. Tech. Rep, Scripps Institution of Oceanography, San Diego

  • Kim HM, Michelena NF, Papalambros PY, Jiang T (2003) Target cascading in optimal system design. Trans ASME J Mech Des 125(3):474–480

    Article  Google Scholar 

  • Leonard NE, Graver JG (2001) Model-based feedback control of autonomous underwater gliders. IEEE J Ocean Eng 26(4):633–645

    Article  Google Scholar 

  • Li W, Jia YJ, Wen Y, Li LX (2016) An improved collaborative optimization for multidisciplinary problems with coupled design variables. Adv Eng Softw 102:134–141

    Article  Google Scholar 

  • Li B, Pang Y, Cheng Y, Zhu X (2017) Collaborative optimization for ring-stiffened composite pressure hull of underwater vehicle based on lamination parameters. Int J Naval Archit Ocean Eng 9(4):373–381

    Article  Google Scholar 

  • Li C, Wang P, Dong H, Wang X (2018) A simplified shape optimization strategy for blended-wing-body underwater gliders. Struct Multidiscip Optim 58(5):2189–2202

    Article  Google Scholar 

  • Liu X, Yuan Q, Zhao M, Cui W, Ge T (2017) Multiple objective multidisciplinary design optimization of heavier-than-water underwater vehicle using CFD and approximation model. J Mar Sci Technol (Jpn) 22(1):135–148

    Article  Google Scholar 

  • Luo W, Lyu W (2015) An application of multidisciplinary design optimization to the hydrodynamic performances of underwater robots. Ocean Eng 104(29):686–697

    Article  Google Scholar 

  • Martins JRRA, Lambe AB (2013) Multidisciplinary design optimization: a survey of architectures. AIAA J 51(9):2049–2075

    Article  Google Scholar 

  • Rudnick DL (2016) Ocean research enabled by underwater gliders. Annu Rev Mar Sci 8(3):519–541

    Article  Google Scholar 

  • Rudnick DL, Davis RE, Eriksen CC, Fratantoni DM, Perry MJ (2004) Underwater glider for ocean research. Mar Technol Soc J 38(2):73–84

    Article  Google Scholar 

  • Sang H, Zhou Y, Sun X, Yang S (2018) Heading tracking control with an adaptive hybrid control for under actuated underwater glider. ISA Trans 80:554–563

    Article  Google Scholar 

  • Sherman J, Davis RE, Owens WB, Valdes J (2001) The autonomous underwater glider “spray”. IEEE J Ocean Eng 26(4):437–446

    Article  Google Scholar 

  • Sobieszczanski-Sobieski J, Agte JS, Sandusky RR Jr (2000) Bi-level integrated system synthesis. AIAA J 38(1):164–172

    Article  Google Scholar 

  • Stommel H (1989) The Slocum mission. Oceanography 2:22–25

    Article  Google Scholar 

  • Sun C, Song B, Wang P, Wang X (2017) Shape optimization of blended-wing-body underwater glider by using gliding range as the optimization target. Int J Naval Archit Ocean Eng 9(6):693–704

    Article  Google Scholar 

  • Sun S, Song B, Wang P, Dong H, Chen X (2020) Shape optimization of underwater wings with a new multi-fidelity bi-level strategy. Struct Multidiscip Optim 6(1):319–341

    Article  Google Scholar 

  • Tang T, Li B, Fu X, Xi Y, Yang G (2018) Bi-directional evolutionary topology optimization for designing a neutrally buoyant underwater glider. Eng Optim 50(8):1270–1286

    Article  Google Scholar 

  • Wang Y, Yang S (2019) Glider. Encycl Ocean Eng. https://doi.org/10.1007/978-981-10-6963-5_48-1

  • Wang X, Song B, Wang P, Sun C (2018) Hydrofoil optimization of underwater glider using free-form deformation and surrogate-based optimization. Int J Naval Archit Ocean Eng 10(6):730–740

    Article  Google Scholar 

  • Webb DC, Simonetti PJ, Jones CP (2001) SLOCUM: an underwater glider propelled by environmental energy. IEEE J Ocean Eng 26(4):447–452

    Article  Google Scholar 

  • Xue D, Wu Z, Wang Y, Wang S (2018) Coordinate control, motion optimization and sea experiment of a fleet of Petrel-II gliders. Chin J Mech Eng 31(2):118–132

    Google Scholar 

  • Yang Y, Liu Y, Wang Y, Zhang H, Zhang L (2017) Dynamic modeling and motion control strategy for deep-sea hybrid-driven underwater gliders considering hull deformation and seawater density variation. Ocean Eng 143:66–78

    Article  Google Scholar 

  • Yang M, Wang Y, Wang S, Yang S, Song Y, Zhang L (2019) Motion parameter optimization for gliding strategy analysis of underwater gliders. Ocean Eng 191:106502

    Article  Google Scholar 

  • Yang M, Yang S, Wang Y, Liang Y, Wang S, Zhang L (2020) Optimization design of neutrally buoyant hull for underwater gliders. Ocean Eng 209:107512

    Article  Google Scholar 

  • Zhang D, Tang S, Che J (2015) Concurrent subspace design optimization and analysis of hypersonic vehicles based on response surface models. Aerosp Sci Technol 42:39–49

    Article  Google Scholar 

  • Zhang D, Song B, Wang P, Chen X (2017) Multidisciplinary optimization design of a new underwater vehicle with highly efficient gradient calculation. Struct Multidiscip Optim 55(4):1483–1502

    Article  MathSciNet  Google Scholar 

  • Zhang T, Zhou H, Wang J, Liu Z, Xin J, Pang Y (2019) Optimum design of a small intelligent ocean exploration underwater vehicle. Ocean Eng 184(5):40–58

    Article  Google Scholar 

Download references

Funding

This work was jointly supported by National Natural Science Foundation of China (Grant Nos. 51722508, and 11902219) and National Key R&D Program of China (Grant No. 2016YFC0301100); Natural Science Foundation of Tianjin City (Grant Nos. 18JCQNJC05100 and 18JCJQJC46400); and Aoshan Talent Cultivation Program (Grant No. 2017ASTCP-OE01) of Pilot National Laboratory for Marine Science and Technology (Qingdao).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wendong Niu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Replication of results

The results presented in this study can be replicated by implementing the formulas and data structures presented in this study. The code and data for producing the presented results will be made available by request.

Additional information

Responsible Editor: Ji-Hong Zhu

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, S., Yang, M., Niu, W. et al. Multidisciplinary design optimization of underwater glider for improving endurance. Struct Multidisc Optim 63, 2835–2851 (2021). https://doi.org/10.1007/s00158-021-02844-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00158-021-02844-z

Keywords

Navigation