Global/Local Iteration for Blended Composite Laminate Panel Structure Optimization Subproblems

Composite panel structure optimization is commonly decomposed into panel optimization subproblems. Previous work applied a guide based design approach to the problem for a structure where the local loads were assumed to be fixed for each panel throughout the design process. This paper examines the application of guide based design to a more realistic representation of the structure where the local loads for each panel are determined through a global level analysis that is coupled with the stacking sequence for every design panel. A small problem is selected for which an exhaustive search of the subproblem design space verifies the optimality of the solution found through the global/local iteration process introduced in this work. The efficient discovery of solutions to these guide based design subproblems creates an opportunity to incorporate the solutions into a global level optimization process. A parallel genetic algorithm is proposed to control global optimization in which evaluating the fitness of each member of the population requires the solution of a guide based design subproblem where parallelism is solely within fitness evaluations. Results are presented for a wingbox design problem and compared with known solutions for the same problem to demonstrate weight reductions in a problem thought to already be near optimally solved

Multiscale composite optimization with design guidelines

http://www.emse.fr/~leriche/Full_Paper_Irisarri_Le_Riche_final.pdfInternational audienceComposites show two distinctive features that affect the way in which they are optimized. Firstly, manufacturing strongly interacts with structural performance. Secondly, composites can be described at different scales. This article summarizes contributions that address both features. It is shown how design guidelines can be accounted for in laminate blended design through stacking sequence tables and specialized evolutionary algorithms. It is also explained how the optimization can be made more efficient by simultaneously working at the ply and laminate levels

Automation of optimal laminate design

Composite laminates are in widespread use in the aerospace industry. As well as sa tisfying strength and stiffness criteria, the final laminate design has to be manufacturable in terms of compatibility between adjacent panels, thus introducing conflicting constraints on the allowed laminate stacking sequences. An attempt to automate the laminate design process is described. The method uses a mixture of a genetic algorithm and heuristics to satisfy the various design and manufacturing constraints. Multiple zones are allowed, where each zone defines a panel together with a set of applied loads. Guide laminates and a blending methodology allow each zone to share common plies. This creates ply continuity across the structure and avoids the scenario seen in other laminate optimisation tools where each optimised zone contains unrelated laminates which are not practical from a manufacturing perspective

Stacking sequence and shape optimization of laminated composite plates via a level-set method

International audienceWe consider the optimal design of composite laminates by allowing a variable stacking sequence and in-plane shape of each ply. In order to optimize both variables we rely on a decomposition technique which aggregates the constraints into one unique constraint margin function. Thanks to this approach, a rigorous equivalent bi-level optimization problem is established. This problem is made up of an inner level represented by the combinatorial optimization of the stacking sequence and an outer level represented by the topology and geometry optimization of each ply. We propose for the stacking sequence optimization an outer approximation method which iteratively solves a set of mixed integer linear problems associated to the evaluation of the constraint margin function. For the topology optimization of each ply, we lean on the level set method for the description of the interfaces and the Hadamard method for boundary variations by means of the computation of the shape gradient. Numerical experiments are performed on an aeronautic test case where the weight is minimized subject to different mechanical constraints, namely compliance, reserve factor and buckling load

A novel parallel method for layup optimization of composite structures with ply drop-offs

This paper presents a novel parallel optimization method for obtaining blended layups of composite laminates which closely match target lamination parameters. Firstly, a guide-based adaptive genetic algorithm (GAGA) which stochastically searches the layups is developed. Then the parallel optimization method DLBB-GAGA is developed by combining GAGA and a dummy layerwise branch and bound method (DLBB) which performs logic-based search in a parallel computation, during which optimization information is shared between the two methods. The combination of these two different methods gives the parallel DLBB-GAGA method the advantages of both, enhancing the searching ability for the blended layup optimization. The superiority of the parallel DLBB-GAGA method is demonstrated through comparisons between the three methods, and it is concluded that the method is particularly effective for practical design where more layup design constraints are considered