Optimum Stacking Sequence Design of a Blended Laminated Wing Structure using Permutation Genetic Algorithms

D. Liu*, V.V. Toropov**, D.C. Barton***, M. Zhou****
*-** School of Civil Engineering, University of Leeds, UK.
*** School of Mechanical Engineering, University of Leeds, UK.
**** Altair Engineering Inc., McCabe Way, Suite 100, Irvine, CA, USA.
Periodicity:March - May'2012
DOI : https://doi.org/10.26634/jste.1.1.1700

Abstract

The smeared stiffness-based method is examined for finding the best stacking sequence of laminated composite wing structures in a bi-level optimization process with blending and manufacturing constraints. At the global level optimization, the numbers of plies of the pre-defined angles (0, 90, 45 and -45 degrees) are design variables, buckling, strain and ply angle percentages are constraints and the weight is the objective function. Since the permutation Genetic Algorithm (permGA) operator changes the stacking sequence without changing the composition of the laminate in the composite laminate optimization problem, a permGA is an ideal tool to shuffle the plies to minimize the difference between the values of computed lamination parameters for a current stack and the ones coming from the top level, for which the lamination parameters are zeros due to homogeneity throughout the thickness of the laminate assumed in the top level optimization. This is embedded into an easy and efficient blending procedure applied at this level to achieve the global ply continuity. This multi-stage local optimization by permGAs is demonstrated by the optimization of the root part of a generic aircraft wing structure.

Keywords

Blending, Lamination Parameters, Optimization, Stacking Sequence, Laminated Composite.

How to Cite this Article?

Liu, D., Toropov, V.V., Barton, D.C., and Zhou, M. (2012). Optimum Stacking Sequence Design of a Blended Laminated Wing Structure using Permutation Genetic Algorithms. i-manager’s Journal on Structural Engineering, 1(1), 1-11. https://doi.org/10.26634/jste.1.1.1700

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