Advertisement

Structural and Multidisciplinary Optimization

, Volume 59, Issue 5, pp 1417–1438 | Cite as

A multi-level optimization technique based on fuel consumption and energy index in early-stage ship design

  • Hassan Zakerdoost
  • Hassan GhassemiEmail author
Research Paper
  • 125 Downloads

Abstract

Reducing lifetime fuel consumption (LFC) and energy efficiency design index (EEDI) are two of the main concerns of shipping industry in recent years. This paper presents a multi-disciplinary and multi-level optimization scheme-based software (HPS-MOP2) to design a hull–propeller system simultaneously from the LFC and EEDI point of view in early-stage ship design. Calculations of the ship resistance and propeller performance are essential to optimize the ship hull–propeller system. Two numerical methods with variable fidelity, non-uniform rational basis spline (NURBS) geometry modelling technique and new version of multi-objective evolutionary algorithm based on decomposition (MOEA/D) are three main parts of the proposed methodology. A bulk carrier propelled by a well-known propeller is used as a base model in three different study cases based on specific fuel oil consumption (SFOC) curves provided by the engine manufacturers Wartsila, MAN and Caterpillar. The presented results illustrate that the employed approach may achieve cost- and energy-efficient designs.

Keywords

EEDI LFC Multi-point optimization Hull–propeller system Ship resistance Propeller efficiency 

Abbreviations

Acronym

LFC

Lifetime fuel consumption

EEDI

Energy efficiency design index

NURBS

Non-uniform rational basis spline

BEM

Boundary element method

SFOC

Specific fuel oil consumption

MOP

Multi-objective optimization problem

CFD

Computational fluid dynamics

MOEA/D

Multi-objective evolutionary algorithm based on decomposition

OC

Operating condition

MCR

Maximum continuous rating

SFC

Specific fuel consumption

CS

Compromise solution

IS

Initial solution

HPS

Hull–propeller system

MEPC

Marine Environment Protection Committee

LHS

Latin hypercube sampling

MDO

Multi-disciplinary design optimization

DRA

Dynamical resource allocation

Nomenclatures

L

Length of ship

d

Draft of ship

Z

Propeller number of blades

EAR

Expanded area ratio of propeller

BN

Beaufort number

T

Propeller thrust

KT

Thrust coefficient

ηo

Propeller open water efficiency

N

Propeller rotating speed

PO

Atmosphere pressure

K

Keller’s coefficient (0 < K < 0.2)

V

Ship speed

PE

Effective power

w

Wake fraction

wi

Weight coefficient

DWT

Deadweight tonnage of ship

\( {\overline{R}}_{\mathrm{AW}} \)

Mean added resistance

RWM

Wave-making resistance

RCW

Calm water resistance

QPC

Quasi-propulsive coefficient

B

Breadth of ship

D

Propeller diameter

P/D

Pitch ratio of propeller

Fn

Froude number

RT

Ship total resistance in waves

Q

Propeller torque

KQ

Torque coefficient

J

Advance coefficient (J = VA/ND)

VA

Advance velocity

PV

Vapour pressure

ρ

Fluid density

PB

Brake power

ηH

Hull efficiency

t

Thrust deduction factor

Δ

Ship displacement

LWT

Lightweight tonnage of ship

S(w) 

Energy spectrum of the sea

RV

Viscous resistance

ηS

Transmission efficiency

ηRR

Relative rotative efficiency

Notes

References

  1. Abt C, Harries S (2007) A new approach to integration of CAD and CFD for naval architects 6th COMPIT. Cortona:467–479Google Scholar
  2. Abt C, Harries S, Heimann J, Winter H (2003) From redesign to optimal hull lines by means of parametric modeling. In: 2nd Intl. Conf. Computer Applications and Information Technology in the Maritime IndustriesGoogle Scholar
  3. Ayob M (2011) Development of an optimization framework for the design of high speed planing Craft PhD ThesisGoogle Scholar
  4. Bensow RE, Vesting F (2011) Propeller optimisation considering sheet cavitation and hull interaction. paper presented at the Second International Symposium on Marine Propulsors, HamburgGoogle Scholar
  5. Bertetta D, Brizzolara S, Gaggero S, Viviani M, Saviob L (2012) CPP propeller cavitation and noise optimization at different pitches with panel code and validation by cavitation tunnel measurements. Ocean Engineering 53:177–195CrossRefGoogle Scholar
  6. Bolbot V, Papanikolaou A (2016) Parametric, multi-objective optimisation of ship's bow for the added resistance in waves. Ship Technol Res 63:171–180CrossRefGoogle Scholar
  7. Buhaug Ø et al (2009) Second IMO GHG study 2009; International Maritime Organization (IMO). In, London, UKGoogle Scholar
  8. Campana EF, Peri D, Tahara Y, Stern F (2006) Shape optimization in ship hydrodynamics using computational fluid dynamics. Comput Methods Appl Mech Eng 196:634–651CrossRefzbMATHGoogle Scholar
  9. Carlton J (2012) Marine propellers and propulsion. Butterworth-Heinemann, OxfordGoogle Scholar
  10. Caterpillar (2010) Caterpillar Inc.: Caterpillar 3208 Marine engine specification sheetGoogle Scholar
  11. Dambrine J, Pierre M, Rousseaux G (2016) A theoretical and numerical determination of optimal ship forms based on Michell’s wave resistance. ESAIM: Control, Optimisation and Calculus of Variations 22:88–111MathSciNetzbMATHGoogle Scholar
  12. Diez M, Serani A, Iemma U, Campana EF (2014) A fish shoal algorithm for global derivative-free simulation-based ship design optimization. In: Proceedings of the 17th numerical towing tank symposium-NuTTSGoogle Scholar
  13. Diez M, Campana EF, Stern F (2018) Stochastic optimization methods for ship resistance and operational efficiency via CFD. Struct Multidiscip Optim 57:735–758MathSciNetCrossRefGoogle Scholar
  14. Epps BP, Kimball RW (2013) Unified rotor lifting line theory. J Ship Res 57:181–201CrossRefGoogle Scholar
  15. Gaggero S, Gonzalez-Adalid J, Sobrino MP (2016) Design of contracted and tip loaded propellers by using boundary element methods and optimization algorithms. Appl Ocean Res 55:102–129CrossRefGoogle Scholar
  16. Gaggero S et al (2017) Efficient and multi-objective cavitating propeller optimization: an application to a high-speed craft. Appl Ocean Res 64:31–57CrossRefGoogle Scholar
  17. Garg N, Kenway GK, Lyu Z, Martins JR, Young YL (2015) High-fidelity hydrodynamic shape optimization of a 3-D hydrofoil. J Ship Res 59:209–226CrossRefGoogle Scholar
  18. Ghassemi H, Ghadimi P (2008) Computational hydrodynamic analysis of the propeller–rudder and the AZIPOD systems. Ocean Eng 35:117–130CrossRefGoogle Scholar
  19. Ghassemi H, Kohansal A (2010) Hydrodynamic analysis of non-planing and planing hulls by BEM. Scientia Iranica Transaction B, Mech Eng 17:25–41zbMATHGoogle Scholar
  20. Ghassemi H, Zakerdoost H (2017) Ship hull–propeller system optimization based on the multi-objective evolutionary algorithm. Proc Inst Mech Eng C J Mech Eng Sci 231:175–192CrossRefGoogle Scholar
  21. Ghose J, Gokarn R (2004) Basic ship propulsion. Allied Publishers, New DelhiGoogle Scholar
  22. Ginnis A, Feurer C, Belibassakis K, Kaklis P, Kostas K, Gerostathis T, Politis C A (2011) CATIA® ship-parametric model for isogeometric hull optimization with respect to wave resistance. In: Proceedings of International Conference on Computer Application in Shipbuilding.Google Scholar
  23. Giselle Fernández-Godino M, Park C, Kim N-H, Haftka RT (2016) Review of multi-fidelity models arXiv preprint arXiv:160907196Google Scholar
  24. Haftka RT, Sobieszczanski-Sobieski J, Padula SL (1992) On options for interdisciplinary analysis and design optimization Structural Optimization 4:65–74Google Scholar
  25. Han S, Lee Y-S, Choi YB (2012) Hydrodynamic hull form optimization using parametric models. J Mar Sci Technol 17:1–17CrossRefGoogle Scholar
  26. Hart CG, Vlahopoulos N (2010) An integrated multidisciplinary particle swarm optimization approach to conceptual ship design. Struct Multidiscip Optim 41:481–494CrossRefGoogle Scholar
  27. He J, Chen H, Yu H, Xiong X, Fan S (2017) Sun R Resistance optimization of a cruise ship using a hybrid approach. In: The 27th International Ocean and Polar Engineering Conference, International Society of Offshore and Polar EngineersGoogle Scholar
  28. Hock J, Goh C, Li Y (2016) Hybrid evolutionary shape manipulation for efficient hull form design optimisationGoogle Scholar
  29. IMO Note by International Maritime Organization (2009) In: Second IMO GHG Study,Google Scholar
  30. IMO Note by International Maritime Organization (2012) In: Guidelines for the development of a SEEMP, MEPC63/23, Annex 9Google Scholar
  31. Jiang J, Cai H, Ma C, Qian Z, Chen K, Wu P (2018) A ship propeller design methodology of multi-objective optimization considering fluid–structure interaction. Eng Appl Computa Fluid Mech 12:28–40Google Scholar
  32. Kamarlouei M, Ghassemi H, Aslansefat K, Nematy D (2014) Multi-objective evolutionary optimization technique applied to propeller design acta polytechnica hungarica:11Google Scholar
  33. Kim H, Yang C, Löhner R, Noblesse FA (2008) practical hydrodynamic optimization tool for the design of a monohull ship. In: Intl Conf. Society Offshore & Polar EngineeringGoogle Scholar
  34. Kong Y-M, Choi S-H, Song J-D, Yang B-S (2006) OPTSHIP: a new optimization framework and its application to optimum design of ship structure. Struct Multidiscip Optim 32:397–408CrossRefGoogle Scholar
  35. Kostas K, Ginnis A, Politis C, Kaklis P (2015) Ship-hull shape optimization with a T-spline based BEM–isogeometric solver. Comput Methods Appl Mech Eng 284:611–622MathSciNetCrossRefzbMATHGoogle Scholar
  36. Lackenby H (1950) On the systematic geometrical variation of ship forms. Trans INA 92:289–316Google Scholar
  37. Leotardi C, Serani A, Iemma U, Campana EF, Diez M (2016) A variable-accuracy metamodel-based architecture for global MDO under uncertainty. Struct Multidiscip Optim 54:573–593MathSciNetCrossRefGoogle Scholar
  38. Liu S, Papanikolaou A (2016) Fast approach to the estimation of the added resistance of ships in head waves. Ocean Eng 112:211–225CrossRefGoogle Scholar
  39. MAN (2009) Man Diesel and Turbo, MAN B&W: 6S90ME-C7 Project guide, electronically controlled two-stroked engines, 5 Edn., 5 edn., Teglholmsgade 41, DK-2450 Copenhagen, DenmarkGoogle Scholar
  40. Mizzi K, Demirel YK, Banks C, Turan O, Kaklis P, Atlar M (2017) Design optimisation of Propeller Boss Cap Fins for enhanced propeller performance. Appl Ocean Res 62:210–222CrossRefGoogle Scholar
  41. Nelson M, Temple D, Hwang J, Young Y, Martins J, Collette M (2013) Simultaneous optimization of propeller–hull systems to minimize lifetime fuel consumption. Appl Ocean Res 43:46–52CrossRefGoogle Scholar
  42. OpenNurbs (2018) https://www.rhino3d.com/opennurbs. Accessed 3 July 2018
  43. Papanikolaou A (2014) Ship design: methodologies of preliminary design. SpringerGoogle Scholar
  44. Park J-H, Choi J-E, Chun H-H (2015a) Hull-form optimization of KSUEZMAX to enhance resistance performance. Int J Nav Archit Ocean Eng 7:100–114CrossRefGoogle Scholar
  45. Park J-y, Peric M, Park D (2015b) An optimization process for propeller design and its application based on CFD. In: The Twenty-fifth International Ocean and Polar Engineering Conference, International Society of Offshore and Polar EngineersGoogle Scholar
  46. Percival S, Hendrix D, Noblesse F (2001) Hydrodynamic optimization of ship hull forms. Appl Ocean Res 23:337–355CrossRefGoogle Scholar
  47. Pérez F, Suárez JA, Clemente JA, Souto A (2007) Geometric modelling of bulbous bows with the use of non-uniform rational B-spline surfaces. J Mar Sci Technol 12:83–94CrossRefGoogle Scholar
  48. Peri D, Rossetti M, Campana EF (2001) Design optimization of ship hulls via CFD techniques. J Ship Res 45:140–149Google Scholar
  49. Piegl L, Tiller W (2012) The NURBS book. Springer Science & Business Media, BerlinzbMATHGoogle Scholar
  50. Pinto A, Peri D, Campana EF (2007) Multiobjective optimization of a containership using deterministic particle swarm optimization. J Ship Res 51:217–228Google Scholar
  51. Priftis A, Papanikolaou A, Plessas T (2017) Parametric design and multiobjective optimization of containerships. J Ship Prod Des 33:46–59CrossRefGoogle Scholar
  52. Ship&Bunker (2017) IFO 380 price in Port Singapore. Rotterdam, Fujairah and Houston https://shipandbunker.com. Accessed 17 Dec 2017Google Scholar
  53. Strom-Tejsen J, Hugh Y. H. Yeh, Moran DD (1973) Added resistance in waves SNAME Transactions:109–143Google Scholar
  54. Tahara Y, Tohyama S, Katsui T (2006) CFD-based multi-objective optimization method for ship design. Int J Numer Methods Fluids 52:499–527CrossRefzbMATHGoogle Scholar
  55. Tahara Y, Peri D, Campana EF, Stern F (2008) Computational fluid dynamics-based multiobjective optimization of a surface combatant using a global optimization method. J Mar Sci Technol 13:95–116CrossRefGoogle Scholar
  56. Takekoshi Y et al (2005) Study on the design of propeller blade sections using the optimization algorithm. J Mar Sci Technol 10:70–81CrossRefGoogle Scholar
  57. Vesting F, Gustafsson R, Bensow RE (2016) Development and application of optimisation algorithms for propeller design. Ship Technol Res 63:50–69CrossRefGoogle Scholar
  58. Viana FA, Venter G, Balabanov V (2010) An algorithm for fast optimal Latin hypercube design of experiments. Int J Numer Methods Eng 82:135–156MathSciNetzbMATHGoogle Scholar
  59. Wartsila (2017) Wartsila 46F Project guide,. http://www.wartsila.com/en/engines/medium-speed-engines/Wartsila46F. Accessed 25 Dec 2017
  60. Wen AS, Mariyam S, Shamsuddin H, Samian Y (2006) Optimized NURBS ship hull fitting using simulated annealing. In: Computer graphics, imaging and visualisation, 2006 International Conference on, IEEE, pp 484–489Google Scholar
  61. Wilkins JR IV (2012) Propeller design optimization for tunnel bow thrusters in the bollard pull condition. Massachusetts Institute of Technology, CambridgeGoogle Scholar
  62. Yari E, Ghassemi H (2016) Hydrodynamic analysis of the surface-piercing propeller in unsteady open water condition using boundary element method. Int J Nav Archit Ocean Eng 8:22–37CrossRefGoogle Scholar
  63. Yuen TJ, Ramli R (2010) Comparision of computational efficiency of MOEA\D and NSGA-II for passive vehicle suspension optimization. In: ECMS,. pp 219–225Google Scholar
  64. Zakerdoost H, Ghassemi H (2018) Hydrodynamic multidisciplinary optimization of a container ship and its propeller using comprehensive HPSOP code 53 Scientific Journals of the Maritime University of Szczecin:48–56Google Scholar
  65. Zakerdoost H, Ghassemi H, Ghiasi M (2013) Ship hull form optimization by evolutionary algorithm in order to diminish the drag. J Mar Sci Appl 12:170–179CrossRefGoogle Scholar
  66. Zhang Q, Li H (2007) MOEA/D: a multiobjective evolutionary algorithm based on decomposition evolutionary computation. IEEE Transactions on 11:712–731Google Scholar
  67. Zhang B-J, Zhang S-L (2019) The optimization of the hull form with the minimum wave-making resistance based on potential flow theory. In: Research on ship design and optimization based on simulation-based design (SBD) technique. Springer, Berlin, pp 143–195CrossRefGoogle Scholar
  68. Zhang P, Zhu D-x, W-h L (2008) Parametric approach to design of hull forms. J Hydrodyn Ser B 20:804–810CrossRefGoogle Scholar
  69. Zhang Q, Liu W, Li H (2009) The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances. In: Evolutionary Computation, CEC’09. IEEE Congress on, 2009. IEEE, pp 203–208Google Scholar
  70. Zhang L, Zhang JN, Zou Y (2016) Multi-objective optimization method in the main dimensions of high performance ship based on current EEDI. In: The 26th International Ocean and Polar Engineering Conference,. International Society of Offshore and Polar EngineersGoogle Scholar
  71. Zhang S, Zhang B, Tezdogan T, Xu L, Lai Y (2017) Computational fluid dynamics-based hull form optimization using approximation method. Eng Appl Comput Fluid Mech 12:74–88Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Maritime EngineeringAmirkabir University of TechnologyTehranIran

Personalised recommendations