Applied Composite Materials

, Volume 17, Issue 2, pp 159–173 | Cite as

Optimum Structural and Manufacturing Design of a Braided Hollow Composite Part

  • Hossein GhiasiEmail author
  • Larry Lessard
  • Damiano Pasini
  • Maxime Thouin


Simultaneous material consolidation and shaping, as performed in manufacturing of composite materials, causes a strong interconnection between structural and manufacturing parameters which makes the design process complicated. In this paper, the design of a carbon fiber bicycle stem is examined through the application of a multi-objective optimization method to illustrate the interconnection between structural and manufacturing objectives. To demonstrate the proposed method, a test case dealing with the design of composite part with complex geometry, small size and hollow structure is described. Bladder-assisted Resin Transfer Molding is chosen as the manufacturing method. A finite element model of the stem is created to evaluate the objectives of the structural design, while a simplified 2D model is used to simulate the flow inside the preform during the injection process. Both models are formulated to take into account the variation of fiber orientation, thickness and fiber volume fraction as a function of braid diameters, injection pressure and bladder pressure. Finally, a multiobjective optimization method, called Normalized Normal Constraint Method, is used to find a set of solutions that simultaneously optimizes weight, filling time and strength. The solution to the problem is a set of optimum designs which represent the Pareto frontier of the problem. Pareto frontier helps to gain insight into the trade-off among objectives, whose presence and importance is confirmed by the numerical results presented in this paper.


Optimum design Composite material Resin Transfer Molding Multiobjective optimization Bicycle stem 


  1. 1.
    Potter, K.: Resin transfer molding, London, New York, Chapman & Hall (1997)Google Scholar
  2. 2.
    Le Riche, R., Saouab, A., Breard, J.: Coupled compression RTM and composite layup optimization. Comp. Sc. and Tech. 63(15), 2277–2287 (2003)CrossRefGoogle Scholar
  3. 3.
    Park, C.H., Lee, W., Han, W.S., Vautrin, A.: Weight minimization of composite laminated plates with multiple constraints. Compo. Sc. Tech. 63(7), 1015–1026 (2003)CrossRefGoogle Scholar
  4. 4.
    Park, C.H., Lee, W., Han, W.S., Vautrin, A.: Multiconstraint optimization of composite structures manufactured by resin transfer molding process. J. Compo. Mat. 39(4), 347–374 (2005)CrossRefGoogle Scholar
  5. 5.
    Ghiasi, H., Pasini, P., Lessard, L.: Pareto frontier for simultaneous structural and manufacturing optimization of a composite part. Struc. Multidisc. Optim. (2009). doi: 10.1007/s0015800903664 Google Scholar
  6. 6.
    Lehmann, U., Michaeli, W.: Improved processing of resin transfer molding for the production of hollow parts with inflatable bladders. In: Proceedings of the 42nd International SAMPE Symposium and Exhibition 42(1): 13–23 (1997)Google Scholar
  7. 7.
    Thouin, M.: Design of a carbon fiber bicycle stem using an internal bladder and resin transfer molding. M.Eng. Thesis, McGill University (2004)Google Scholar
  8. 8.
    Lessard, L., Nemes, J., Lizotte, P.: Utilization of FEA in the design of composite bicycle frames. J. Composites 26(1), 72–74 (1995)CrossRefGoogle Scholar
  9. 9.
    Lizotte, P.: Stress analysis and fabrication of composite monocoque bicycle frames. M.Eng. Thesis, McGill University (1996)Google Scholar
  10. 10.
    Van der Aa, H.C.E.: Re-design and manufacturing of a composite monocoque bicycle frame. Joint Technical Report, McGill University and T.U. Eindhoven, Netherlands (1997)Google Scholar
  11. 11.
    ANSYS theory reference, Release 11.0: documentation for ANSYS, ANSYS, Inc.Google Scholar
  12. 12.
    Boccard, A., Lee, W.I., Springer, G.S.: Model for determining the vent locations and the fill time of resin transfer molds. J. Compo. Mat. 29, 306–333 (1995)Google Scholar
  13. 13.
    Chan, A.W., Larive, D.E., Morgan, R.J.: Anisotropic permeability of fiber preforms: constant flow rate measurement. J Compo. Mat. 27(10), 996–1008 (1993)CrossRefGoogle Scholar
  14. 14.
    Miettinen, K.: Nonlinear multiobjective optimization. Kluwer Academic Publishers, Boston (1999)zbMATHGoogle Scholar
  15. 15.
    Deb, K.: Multi-objective optimization using evolutionary algorithms. John Wiley & Sons, LTD, Chichester, New York, Weinheim, Brisbane, Singapore, Toronto (2001)zbMATHGoogle Scholar
  16. 16.
    Marler, R.T., Arora, J.S.: Survey of multiobjective optimization methods. Struct. Multidisc. Optim. 26, 369–395 (2004)CrossRefMathSciNetGoogle Scholar
  17. 17.
    Walker, M., Reiss, T., Adali, S.: Multiobjective design of laminated cylindrical shells for maximum torsional and axial buckling loads. Compu. Struc. 62(2), 237–242 (1997)zbMATHCrossRefGoogle Scholar
  18. 18.
    Deka, D.J., Sandeep, G., Chakraborty, D., Dutta, A.: Multiobjective optimization of laminated composites using finite element method and genetic algorithm. J Reinf. Plast. Compo. 24(3), 273–285 (2005)CrossRefGoogle Scholar
  19. 19.
    Mohan Rao, A.R., Arvind, N.: A scatter search algorithm for stacking sequence optimisation of laminate composites. Compo. Struc 70, 383–402 (2005)CrossRefGoogle Scholar
  20. 20.
    Abouhamze, M., Shakeri, M.: Multi-objective stacking sequence optimization of laminated cylindrical panels using a genetic algorithm and neural networks. Compo. Struc. 81(2), 253–263 (2007)CrossRefGoogle Scholar
  21. 21.
    Wang, B.P., Costin, D.P.: Optimum design of a composite structure with three types of manufacturing constraints. AIAA J. 30(6), 1667–1669 (1992)CrossRefADSGoogle Scholar
  22. 22.
    Henderson, J.L., Gurdal, Z., Loos, A.C.: Combined structural and manufacturing optimization of stiffened composite panels. J of Aircraft 36(1), 246–254 (1999)CrossRefGoogle Scholar
  23. 23.
    Saravanos, D.A., Chamis, C.C.: Multiobjective shape and material optimization of composite structures including damping. AIAA 30(3), 805–813 (1992)CrossRefADSGoogle Scholar
  24. 24.
    Kere, P., Lento, J.: Design optimization of laminated composite structures using distributed grid resources. Compo. Struc. 71(3–4), 435–438 (2005)CrossRefGoogle Scholar
  25. 25.
    Suresh, S., Sujit, P.B., Rao, A.K.: Particle swarm optimization approach for multi-objective composite box-beam design. Compo. Struc. 81(4), 598–605 (2007)CrossRefGoogle Scholar
  26. 26.
    Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)CrossRefGoogle Scholar
  27. 27.
    Pelletier, J.L., Vel, S.S.: Multi-objective optimization of fiber reinforced composite laminates for strength, stiffness and minimal mass. Compu. Struc. 84, 2065–2080 (2006)CrossRefGoogle Scholar
  28. 28.
    Omkar, S.N., Mudigere, D., Naik, G.N., Gopalakrishnan, S.: Vector evaluated particle swarm optimization (VEPSO) for multi-objective design optimization of composite structures. Compu. Struc. 86, 1–14 (2008)CrossRefGoogle Scholar
  29. 29.
    Messac, A., Ismail-Yahaya, A., Mattson, C.A.: The normalized normal constraint, method for generating the Pareto frontier. Struc. Multidisc. Optim. 25(2), 86–98 (2003)CrossRefMathSciNetGoogle Scholar
  30. 30.
    Luersen, M.A., Le Riche, R.: Globalized Nelder-Mead method for engineering optimization. Compu. Struc. 82, 2251–2260 (2004)CrossRefGoogle Scholar
  31. 31.
    Ghiasi, H., Pasini, D., Lessard, L.: Constrained globalized Nelder-Mead method for simultaneous structural and manufacturing optimization of a composite bracket. J. Compo. Mat. 42(7), 717–736 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Hossein Ghiasi
    • 1
    Email author
  • Larry Lessard
    • 1
  • Damiano Pasini
    • 1
  • Maxime Thouin
    • 1
  1. 1.Department of Mechanical EngineeringMcGill UniversityMontrealCanada

Personalised recommendations