Global laminate optimization on geometrically partitioned shell structures

Abstract

A method aimed at the optimization of locally varying laminates is investigated. The structure is partitioned into geometrical sections. These sections are covered by global plies. A variable-length representation scheme for an evolutionary algorithm is developed. This scheme encodes the number of global plies, their thickness, material, and orientation. A set of genetic variation operators tailored to this particular representation is introduced. Sensitivity information assists the genetic search in the placement of reinforcements and optimization of ply angles. The method is investigated on two benchmark applications. There it is able to find significant improvements. A case study of an airplane's side rudder illustrates the applicability of the method to typical engineering problems.

Definition and representation of stiffened shell structures in the context of an integrated development process

“…Further, the laminate type implies relevant laminate design criteria and sizing methods. The design of stacking sequences is an important step during design (Keller, 2011(Keller, , 2010Lopez et al, 2009). Further, stacking sequences are subject to process restrictions.…”

Towards an Automated Optimization of Laminated Composite Structures: Hierarchical Zoning Approach with Exact Blending Rules

“…2. Note that patch concept had been considered in the literature already [13,14,15], albeit with different purposes. Every patch is characterized only by its width and the connected set of zones it covers (patches covering all zones will be refered to as having no boundary or continuous).…”

“…Probabilities (15,16) were measured via Monte-Carlo methodology using sufficiently large (10 8 ) sample of uniformly distributed points. It turns out that probability (15) is zero with high confidence level (all points, sampled from…”

A Global Optimization Approach Applied to Structural Dynamic Updating

“…Within the stochastic methods are also the sub-class of evolutionary methods, such as Genetic Algorithms (GA), and Simulated Annealing (SA), used by Sonmez [11] to obtain multi optimal shapes for two-dimensional structures subject to quasi-static loads and restraints, and Venanzi e Materazzi [12] to optimize wind-excited structures. The hybridization of a genetic algorithm and a nonsmooth proximal bundle method is used in Auvinen et al [13] to minimize the weight of a forest machine, and Keller [14] applied evolutionary algorithms to a case study of an air-plane's side rudder.…”