Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-19T14:13:15.451Z Has data issue: false hasContentIssue false
  • English
  • Français

Blending design of composite panels with lamination parameters

Published online by Cambridge University Press:  30 August 2016

P. Jin ,
X. Zhong ,
J. Yang  and
Z. Sun
P. Jin*
Affiliation:
School of Civil Engineering and Architecture Xi'an University of Technology Xi'an China
X. Zhong
Affiliation:
School of Aeronautics Northwestern Polytechnical University Xi'an China
J. Yang
Affiliation:
School of Aeronautics Northwestern Polytechnical University Xi'an China
Z. Sun
Affiliation:
School of Aeronautics Northwestern Polytechnical University Xi'an China
*
nwpu-jinpeng@163.com
Get access Rights & Permissions [Opens in a new window]

Abstract

In this paper, a new optimisation method incorporating lamination parameters and a guide-based blending model is proposed. Lamination parameters for a guide laminate and ply number of each panel are employed as design variables for optimisation with a parallel real-coded genetic algorithm incorporating structure behaviour and manufacturing constraints. During the optimisation process, with a form of least squares fitting adopted, another genetic algorithm is used to obtain the guide stacking sequence of the guide laminate from the guide lamination parameters, and then the laminate configurations of each panel are obtained from the guide stacking sequence and number of plies for each panel. The proposed framework is demonstrated via design of an 18-panel horseshoe configuration, where each panel is optimised individually with a buckling constraint. Numerical results indicate that the present algorithm is capable of obtaining fully blended designs.

Keywords

Blendinglamination parametersptimisation
Type
Research Article
Information
The Aeronautical Journal , Volume 120 , Issue 1233 , November 2016 , pp. 1710 - 1725
Copyright
Copyright © Royal Aeronautical Society 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Ghiasi, H., Pasini, D. and Lessard, H. Optimum stacking sequence design of composite materials Part I: constant stiffness design. Composite Structures, 2009, 90, pp 1–11.CrossRefGoogle Scholar
2. Schmit, L.A. and Mehrinfar, M. Multilevel optimum design of structures with fibre composite stiffened panel components. AIAA Journal, 1982, 20, (1), pp 138–147.CrossRefGoogle Scholar
3. Liu, D., Toropov, V.V., Zhou, M., Barton, D.C. and Querin, O.M. Optimisation of blended composite wing panels using smeared stiffness technique and lamination parameters. 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and 6th AIAA Multidisciplinary Design Optimisation Specialist Conference. Orlando, Florida, US, 2010.Google Scholar
4. Liu, D., Toropov, V.V., Querin, O.M. and Barton, D.C. Bilevel optimization of blended composite wing panels. J Aircraft, 2011, 48, (1), pp 107–118.CrossRefGoogle Scholar
5. Riche, R.L. and Haftka, R.T. Optimization of laminate stacking sequence for buckling load maximisation by genetic algorithm. AIAA J, 1993; 31, (5), pp 951–956.CrossRefGoogle Scholar
6. Todoroki, A. and Haftka, R.T. Stacking sequence optimisation by a genetic algorithm with a new recessive gene like repair strategy. Composites Part B: Engineering, 1998, 29, (3), pp 277–285.CrossRefGoogle Scholar
7. Sivakumar, K., Iyengar, N. and Deb, K. Optimization of composite laminates with cutouts using genetic algorithm. Engineering Optimization, 2000, 32, (5), pp 635–657.CrossRefGoogle Scholar
8. Nagendra, S., Jestin, D., Gürdal, Z., Haftka, R.T. and Watson, L.T. Improved genetic algorithm for the design of stiffened composite panels. Computers and Structures, 1996, 58, (3), pp 543–555.CrossRefGoogle Scholar
9. Todoroki, A. and Haftka, R.T. Stacking sequence optimization by a genetic algorithm with a new recessive gene like repair strategy. Composites Part B: Engineering, 1998, 29, (3), pp 277–285.CrossRefGoogle Scholar
10. Diaconu, C.G. and Sekine, H. Layup optimization for buckling of laminated composite shells with restricted layer angles. AIAA Journal, 2004, 42, (10), pp 2153–2163.CrossRefGoogle Scholar
11. Herencia, J.E., Weaver, P.M. and Friswell, M.I. Initial sizing optimization of anisotropic composite panels with T-shaped stiffeners. Thin-Walled Structures, 2008, 46, pp 399–412.CrossRefGoogle Scholar
12. Khani, A., IJsselmuiden, S.T., Abdalla, M.M. and Gürdal, Z. Design of variable stiffness panels for maximum strength using lamination parameters. Composites Part B: Engineering, 2011, 42, pp 546–552.CrossRefGoogle Scholar
13. Setoodeh, S., Abdalla, M.M. and Gürdal, Z. Design of variable-stiffness laminates using lamination parameter. Composites Part B: Engineering, 2006, 37, pp 301–309.CrossRefGoogle Scholar
14. IJsselmuiden, S.T. Optimal Design of Variable Stiffness Composite Structures using Lamination Parameters. PhD Dissertation, 2011, Faculty of Aerospace Engineering, Delft University of Technology, The Netherlands.Google Scholar
15. Tsai, S.W. and Hahn, H.T. Introduction to Composite Materials. 1980, Technomic Publishing Co., Inc., Westport, Connecticut, US.Google Scholar
16. Miki, M. and Sugiyama, Y. Optimum design of laminated composite plates using lamination parameters. AIAA J, 1993, 31, pp 921–922.CrossRefGoogle Scholar
17. Fukunaga, H. and Vanderplaats, G.N. Stiffness optimization of orthotropic laminated composites using lamination parameters. AIAA J, 1991, 29, (4), pp 641–646.CrossRefGoogle Scholar
18. Diaconu, C.G., Sato, M. and Sekine, H. Feasible region in general design space of lamination parameters for laminated composites. AIAA J, 2002, 40, (3), pp 559–565.CrossRefGoogle Scholar
19. Bloomfield, M.W., Diaconu, C.G. and Weaver, P.M. On feasible regions of lamination parameters for lay-up optimization of laminated composites. Proceedings of the Royal Soc A, 2009, 465, pp 1123–1143.CrossRefGoogle Scholar
20. Yamazaki, K. Two-level optimisation technique of composite panels by genetic algorithm. Proceeding of 37th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Material Conference, 1996, Salt Lake City, Utah, US, pp 1882–1886.Google Scholar
21. Todoroki, A. and Sasai, M. Stacking sequence optimizations using GA with zoomed response surface on lamination parameters. Advanced Composite Materials, 2002, 11, (3), pp 299–318.CrossRefGoogle Scholar
22. Herencia, J.E., Haftka, R.T., Weaver, P.M. and Friswell, M.I. Lay-up optimization of composite stiffened panels using linear approximations in lamination spaces. AIAA J, 2008, 46, (9), 2387–2391.CrossRefGoogle Scholar
23. Liu, D., Toropov, V.V., Barton, D.C. and Querin, O.M. Weight and mechanical performance optimization of blended composite wing panels using lamination parameters. Structural and Multidisciplinary Optimization, 2015, 52, pp 549–562.CrossRefGoogle Scholar
24. Kameyama, M. and Arai, M. Optimal design of symmetrically laminated plates for damping characteristics using lamination parameters. Composite Structures, 2015, 132, pp 885–897.CrossRefGoogle Scholar
25. Scarth, C., Cooper, J.E., Weaver, P.M. and Gustavo, H.C.S. Uncertainty quantification of aeroelastic stability of composite plate wings using lamination parameters. Composite Structures, 2014, 116, pp 84–93.CrossRefGoogle Scholar
26. Bohrer, R.Z.G., Almeida, S.F.M. and Donadon, M.V. Optimization of composite plates subjected to buckling and small mass impact using lamination parameters. Composite Structures, 2015, 120, pp 141–152.CrossRefGoogle Scholar
27. Kristinsdottir, B.P., Zabinsky, Z.B., Tuttle, M.E. and Neogi, S. Optimum design of large composite panels with varying loads. Composite Structures, 2001, 51, pp 93–102.CrossRefGoogle Scholar
28. Liu, B. and Haftka, R.T. Composite wing structural design optimization with continuity constraints. Proceedings of the 42nd AIAA/ASME/ASCE/AHA/ACS Structures, Structural Dynamics and Material Conference, 2001, Seattle, Washington, US.CrossRefGoogle Scholar
29. Toropov, V.V., Jones, R. and Willment, T. Weight and manufacturability optimization of composite aircraft components based on a genetic algorithm. Proceedings of 6th World Congress of SMO, 2005, Brazil.Google Scholar
30. Soremekun, G., Gürdal, Z., Kassapoglou, C. and Toni, D. Stacking sequence blending of multiple composite laminates using genetic algorithms. Composite Structures, 2002, 56, pp 53–62.CrossRefGoogle Scholar
31. Adams, D.B., Watson, L.T., Gürdal, Z. and Anderson-Cook, C.M. Genetic algorithm optimization and blending of composite laminates by locally reducing laminate thickness. Advances in Engineering Software, 2004, 35, pp 35–43.CrossRefGoogle Scholar
32. Seresta, O., Abdalla, M.M. and Gürdal, Z. A genetic algorithm based blending scheme for design of multiple composite laminates. Proceedings of 50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 4-7 May 2009, Palm Springs, California, USA.CrossRefGoogle Scholar
33. Campen, J., Seresta, O. and Abdalla, M.M. General blending definitions for stacking sequence design of composite laminate structures. Proceedings of 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Material Conference, 2008, Schaumburg, Illinois, US.Google Scholar
34. Irisarri, F.X., Lasseigne, A., Leroy, F.H. and Riche, R.L. Optimal design of laminated composite structures with ply drops using stacking sequence tables. Composite Structures, 2014, 107, pp 559–569.CrossRefGoogle Scholar
35. Zein, S., Basso, P. and Grihon, S. A primal-dual backtracking optimisation method for blended composite structures. Structural and Multidisciplinary Optimization, 2012, 45, pp 669–680.CrossRefGoogle Scholar
36. Zein, S., Basso, P. and Grihon, S. A constraint satisfaction programming approach for computing manufacturable stacking sequences. Computers and Structures, 2014, 136, pp 56–63.CrossRefGoogle Scholar
37. Jing, Z., Fan, X.L. and Sun, Q. Global shared-layer blending method for stacking sequence optimisation design and blending of composite structures. Composites Part B: Engineering, 2015, 69, 181–190.CrossRefGoogle Scholar
38. Jing, Z., Fan, X.L. and Sun, Q. Stacking sequence optimisation of composite laminates for maximum buckling load using permutation search algorithm. Composite Structures, 2015, 121, pp 225–236.CrossRefGoogle Scholar
39. Yang, J.B., Song, B.F., Zhong, X.P. and Jin, P. Optimal design of blended composite laminate structures using ply drop sequence. Composite Structures, 2016, 135, pp 30–37.CrossRefGoogle Scholar
40. IJsselmuiden, S.T., Abdalla, M.M., Seresta, O. and Gürdal, Z. Multi-step blended stacking sequence design of panel assemblies with buckling constraints. Composites Part B: Engineering, 2009, 40, pp 329–336.CrossRefGoogle Scholar
41. Jin, P., Song, B.F. and Zhong, X.P. Structure optimisation of large composite wing with parallel genetic algorithm. J Aircr, 2011, 48, (6), pp 2145–2148.CrossRefGoogle Scholar
42. Jones, R.M. Mechanics of Composite Materials, 1999, Taylor & Francis, Inc., Philadelphia, Pennsylvania, US.Google Scholar
43. Deb, K. and Agrawal, R.B. Simulated binary crossover for continuous search space. Complex Systems, 1995, 9, (2), pp 115–148.Google Scholar
44. IJsselmuiden, S.T., Abdalla, M.M. and Gürdal, Z. Implementation of strength based failure criteria in the lamination parameter design space. AIAA J, 2008, 46, (7), pp 1826–1834.CrossRefGoogle Scholar
45. Erick, C.-P. Designing efficient and accurate parallel genetic algorithms. IlliGAL Report No. 99017, 1999, Illinois Genetic Algorithms Laboratory, Urbana, Illinois, US.Google Scholar