Parallel Genetic Algorithms in the Optimization of Composite Structures

Abstract

Genetic Algorithms (GAs) are a powerful technique for search and optimization problems, and are particularly useful in the optimization of composite structures. The search space for an optimal composite structure is generally discontinuous and strongly multimodal, with the possibility for many local sub-optimal solutions or even singular extrema. These facts severely limit gradient-type approaches to optimization, bringing this broad class of problems under scrutiny for application of GAs. Examples described here of the successful use of parallel GAs to design composite structures by the authors include energy-absorbing laminated beams [1], airfoils with tailored bending-twisting coupling [2], and flywheel structures [3]. Optimal design of laminated composite beams was performed using a GA with a specialized finite element model to design material stacking sequences to maximize the mechanical energy absorbed before fracture. An initial GA approach to the optimal design of a specialized, idealized composite airfoil is now being refined for a practical application. The optimum stacking sequence to produce a desired twisting response while minimizing weight, maximizing in-plane stiffness and maintaining acceptable stress levels is determined. The GA has also been used to maximize the Specific Energy Density (SED) of composite flywheels. SED is defined as the amount of rotational energy stored per unit mass. Optimization of SED was achieved by allowing the GA to search for various flywheel shapes and allowing the GA to pick material sequences along the radius of the flywheel.KeywordsAutomated DesignGenetic AlgorithmsComposite MaterialLaminated StructureOptimization