Advertisement

Multi-objective Optimization of A-Class Catamaran Foils Adopting a Geometric Parameterization Based on RBF Mesh Morphing

  • Marco Evangelos Biancolini
  • Ubaldo Cella
  • Alberto Clarich
  • Francesco Franchini
Chapter
Part of the Computational Methods in Applied Sciences book series (COMPUTMETHODS, volume 49)

Abstract

The design of sailing boats appendages requires taking in consideration a large amount of design variables and diverse sailing conditions. The operative conditions of dagger boards depend on the equilibrium of the forces and moments acting on the system. This equilibrium has to be considered when designing modern fast foiling catamarans, where the appendages accomplish both the tasks of lifting up the boat and to make possible the upwind sailing by balancing the sail side force. In this scenario, the foil performing in all conditions has to be defined as a trade-off among contrasting needs. The multi-objective optimization, combined with experienced aerodynamic design, is the most efficient strategy to face these design challenges. The development of an optimization environment has been considered in this work to design the foils for an A-Class catamaran. This study, in particular, focuses on the geometric parameterization strategy combined with a mesh morphing method based on Radial Basis Functions, and managed through the workflow integration within the optimization environment.

Keywords

Multi-objective optimization Mesh morphing Radial basis functions Foiling catamarans Aerodynamic design 

References

  1. Biancolini ME (2014) RBF morph mesh morphing ACT extension for ANSYS mechanical. In: Automotive simulation world congress, Tokyo, October 2014Google Scholar
  2. Biancolini ME et al Industrial application of the meshless morpher RBF morph to a motorbike windshield optimisation. In: 4th European automotive simulation conference, Munich, Germany, 6–7 July 2009Google Scholar
  3. Bonci M, Viviani, M, Broglia R, Dubbioso G (2015) Method for estimating parameters of practical ship manoeuvring models based on the combination of RANSE computations and system identification. In: Applied ocean research, vol. 52. August 2015, pp 274–294Google Scholar
  4. Caughey DA (2011) Introduction to aircraft stability and control. Course Notes for M&AE 5070, Cornell University, New York, pp 14853–7501Google Scholar
  5. Cella U, Groth C, Biancolini ME (2016) Geometric parameterization strategies for shape optimization using RBF mesh morphing. In: Advances on mechanics, design engineering and manufacturing, pp 537–545, September 2016Google Scholar
  6. Cella U, Salvadore F, Ponzini R (2016) Coupled sail and appendage design method for multihulls based on numerical optimisation. PRACE—EU SHAPE Project Final Report, 5th July 2016Google Scholar
  7. Claughton AR, Shenoi R, Wellicome JF (1998) Sailing yacht design: theory. Addison Wesley, LongmanGoogle Scholar
  8. Clarich A et al Ottimizzazione della regolazione di una vela rigida per catamarani da regata mediante modeFRONTIER e ANSYS. In: ANSYS User Group Meeting. Italy, June 2013Google Scholar
  9. Hoerner SF (1965) Fluid-dynamic drag, Hoerner fluid dynamics. Hoerner, Bakersfield, CA (US)Google Scholar
  10. Jakobsson S, Amoignon O (2007) Mesh deformation using radial basis functions for gradient-based aerodynamic shape optimization. Comput Fluids 36(6):1119–1136CrossRefGoogle Scholar
  11. Larsson L, Eliansson RE (1997) Principle of sailing yacht design. Adlard Coles Nautical, London, UKGoogle Scholar
  12. Sheahan M (2013) High-speed sailing. Ingenia, Royal Academy of Engineering, Issue 57Google Scholar
  13. Stroligo M (2015) Preliminary design investigation for the development of new hull shapes for America’s cup class catamaran AC-62. In: International CAE conference 2015, Verona, Italy, 19–20 October 2015Google Scholar
  14. Vernengo G (2014) Design by optimization of ship hull forms. New perspectives through full parametric modelling and multi-objective optimization. In: modeFRONTIER International Users Meeting, 2014, ItalyGoogle Scholar
  15. Viola IM, Biancolini ME, Sacher M, Cella U (2015) A CFD–based wing sail optimization method coupled to a VPP. In: 5th high performance yacht design international conference, 8–12 March 2015, Auckland (NZ)Google Scholar
  16. Quagliarella D, Périaux J, Poloni C, Winter G (1996) Genetic algorithms and evolution strategy in engineering and computer science: recent advances and industrial applications, Chap. 13, pp 267–288. John Wiley & Sons, Chichester, UKGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Marco Evangelos Biancolini
    • 1
  • Ubaldo Cella
    • 1
    • 2
  • Alberto Clarich
    • 3
  • Francesco Franchini
    • 4
  1. 1.University of Rome “Tor Vergata”RomeItaly
  2. 2.Design MethodsMessinaItaly
  3. 3.ESTECOTriesteItaly
  4. 4.EnginSoftFlorenceItaly

Personalised recommendations