To qualify our models and our PRBM, we study two problems of design of laminated composite structures. As a result, the designer can interactively explore the design space. Integrated into a Parametric Knowledge Model (PKM) with other expert knowledge models, the PRBM makes the basis of an interactive method of design support.The PKM is processed by an evolutionary optimization method. In the case of dynamic behavior, the creeping becomes a conceptual issue.Secondly, a method mixing fractional derivatives and the Proper Generalized Decomposition (PGD) method allowed the creation of the PRBM. Some situations of static and dynamic behavior are studied. A new numerical procedure is proposed to allow engineers to handle each design parameter of a laminated composite structure, each at its relevant scale.First, the Parametric and Reduced Behavior Model (PRBM) is a separated model that enables reasoning based on1- A multiscale approach: the mechanical parameters of the structure are explicitly described as coming from the material quality of each fiber, the matrix, each layer and the topology of the laminate,2- A multiphysical approach: independently the mechanical behavior of each layer and each interface is processed, leading to the behavior of the laminate. The number of design solutions can be huge since the solution space is considerable.Standard CAE systems (CAD, Finite Element Simulation) do not provide an approach to explore these solution spaces efficiently and interactively. Therefore, he must simultaneously create a material and the product topology. The design process of laminated composites faces a major challenge: while an engineer designing a metallic based mechanical product is mainly focusing on the development of a shape that will guarantee a specific behavior, the engineer designing a composite based product must find the best combination of the shape-material structure. Two design problems are presented to illustrate the relevance of the approach when designing composite structures: one under a static load and the having a dynamic behavior. We present a decision support method that allow designers to have, both, a multiscale and a multiphysical view on the laminated structures that they are creating. Our approach is consisting in processing a Knowledge Model having a reduced and separated form. The numerical approach allows the engineer to explore interactively design spaces. Using an optimization approach based on an evolutionary algorithm coupled to a reduced order analysis, a decision support solution is detailed. This paper provides a possible procedure for engineers having a laminated composite product to create: it presents an approach that allows combining to usual morphological design parameters, specific variables that are typically the domain of composite experts, and manufacturing experts. Standard CAE systems (CAD, Finite Element Simulation) do not offer to the designer an approach to explore these solution spaces efficiently and interactively. The number of design solutions can be huge since the solution space is very large. The design process of laminated composites faces two challenges: the engineer designs the product and its morphology, but also, simultaneously, the material. The algorithm could therefore be a suitable choice for topology purposes whenever the laminate is subjected to a set of blending rules and no constraint violation is allowed. It is important to note that the optimization process is enhanced by manufacturing constraints (blending rules), which are fulfilled whenever a feasible solution exists. This algorithm is intrinsically discrete and, unlike most gradient-based techniques, is not affected by local minima. The final result is an even lighter laminate with a variable thickness distribution. Once the stacking sequence for the lightest constant-thickness laminate is determined, the second step is to perform a peeling-off process using a simulated annealing algorithm.
This A* search provides the non-local minimum solution (looking for the best ply orientations and the best core thickness) using a minimum number of finite element method (FEM) evaluations. The first step seeks to obtain the optimal stacking sequence for a laminate, using a blind A* searching scheme over an incremental decision tree. This paper proposes a method to design optimal composite sandwich panels subjected to multiple blending rules and external forces.
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