Fibre architecture design of 3D woven composite with genetic algorithms: a unit cell based optimisation framework and performance assessment
Zeng, Xuesen and Long, Andew C.A. and Ashcroft, Ian and Potluri, Prasad (2015) Fibre architecture design of 3D woven composite with genetic algorithms: a unit cell based optimisation framework and performance assessment. In: 20th International Conference on Composite Materials, 19-24 July 2015, Copenhagen, Denmark.
Official URL: http://www.iccm20.org/fullpapers/file?f=zRDv7On0XQ
There are vast possibilities in fibre architecture design of 3D woven reinforcement. This paper considers the application of Genetic Algorithm (GA) in 3D woven composites optimisation. A set of real and integral variables, representing 3D fibre architecture, are formulated into a mixed integer Genetic Algorithm. The objective function is evaluated through automation of the unit cell based finite element analysis, by using the open source pre-processor TexGen and the commercial solver ABAQUS. The mixed integer Genetic Algorithm is adapted to a micro-population, aiming to improve computational efficiency. The study uses statistical tests to quantify the performance of the Genetic Algorithm schemes and the choice of parameters. The proposed approach was applied to the optimisation of 3D woven composites for maximum buckling resistance for the case of a landing gear brace. This study demonstrated that the optimisation converged to the optimum design within 20 iterations, considering 300 out of 7000 permissible solutions. In terms of buckling performance, the optimum design performed twice as well as cross-ply laminated composites and at least 50% better than known orthogonal 3D woven composites.
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