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With the rising popularity of endovascular aortic repair (EVAR) for aortic aneurysms and dissections, there is a crucial need for investigating the delayed appearance of post-EVAR complications such as stent-graft kinking, fracture and migration respectively. These complications have been noted to be influenced by the radial stiffness and bending flexibility attributes of stent-grafts. Auxetic designs with negative Poisson's ratio offer interesting advantages such as enhanced fracture toughness, superior indentation resistance and adaptive stiffness in response to intricate morphology for stenting applications over conventional stent designs. The objective of this study is to propose different auxetic stent candidates and to compare their mechanical performance with two conventional stent candidates for endovascular applications using numerical simulation through crimp/crushing tests for their radial stiffness and three-point bending/kinking tests for their flexibility, respectively. The results demonstrate that the novel hybrid auxetic designs (CRE and CSTAR) possess the best trade-off between radial stiffness and bending flexibility characteristics among all candidates for stent-graft applications.

International audience; The main goal of this study is to optimize the structural thickness distribution for improving the mechanical performance of composite structures manufactured by compression molding processes. During the preliminary preparation for optimization, a processing simulation program was developed to predict the fiber volume fraction and orientation using a Control Volume/Finite Element method. To verify the effects of the processing conditions on the mechanical properties, a few simple geometries and loading conditions were investigated. Considering the fiber state changes, the optimal thickness distributions of a plate in one- and two-dimension have been searched. Box's complex method was applied to solve the non-linear inequality constrained problem. (C) 2009 Elsevier Ltd. All rights reserved.

International audience; We suggest new approaches to reduce the number of fitness function evaluations in genetic algorithms (GAs) applied to multidisciplinary optimization of composite laminates. In the stacking sequence design of laminated structures, the design criteria are classified into two groups, which are layer combination dependent criteria and layer sequence dependent criteria. The memory approach is employed to lessen the number of fitness function evaluations for the identical design individuals that appear during the search. The permutation operator with local learning or random shuffling is applied to the same design individual to improve the fitness for layer sequence dependent criterion, while maintaining the same performance for layer combination dependent criterion. The numerical efficiency of the present method is validated by the sample problem of weight minimization of composite laminated plate under multiple design constraints.

A structure-process integrated optimization methodology is proposed considering both the structural properties and manufacturing process for the weight minimization of composite laminated plates manufactured by Resin Transfer Molding (RTM) process. In the optimization problem, the structural weight of composite structures is minimized under the stiffness constraint and the mold filling time constraint which is a part of process cycle time. With the results obtained, it is investigated how the weight and material cost are traded-off. The optimization methodology suggests a guide of material selection in the preliminary conceptual design stage.

A multi-objective optimization methodology is proposed which simultaneously considers the mechanical performance and the manufacturing cost from the early stage of design of composite laminated plates. Resin transfer molding process is chosen as the manufacturing process for its wide acceptance among industries. Interrelations between the structural parameters and the process parameters are identified. With proper assumptions, the multi-objective problem is formulated into a problem with a single objective function. As design variables, the stacking sequence of layers is investigated which minimizes the maximum displacement and the mold filling time. Injection gate location is also considered in order to minimize the mold filling time for a given structure geometry, material properties and loading condition. The genetic algorithm is adopted as the optimization scheme. The results from the sample problems illustrate usefulness of the developed methodology.

A multi-constraint optimization methodology for the design of composite laminated plates manufactured by Resin Transfer Molding (RTM) process is presented. As design constraints, both the manufacturing process requirement and the structural requirement were considered. The stacking sequence of layers and the thickness of the structure were optimized for a preassigned geometry of the structure, constituent materials and loading condition. As a structural requirement, either the stiffness constraint or strength constraint was selected. Such constraint was used as basis in the enhancement for the specific mechanical performance of composite structures. Maximum allowable mold filling time was assigned as a process requirement in the effort to increase productivity. The objective function was newly defined without introduction of any auxiliary parameters, such as scaling parameters, weighting coefficients and penalty parameters which are usually involved in multi-constraint or multi-objective optimization problems. As an optimization method, the genetic algorithm was used. The results for a sample problem show the validity of the proposed optimization methodology.

This paper presents and illustrates a straightforward method to determinate the concentration of the humidity in non steady and transient states in the core of the resin matrix composite panel exposed to cyclic temperature and moisture environmental conditions during a long time. In order to complete the previous studies, an analytical solution in transient state is proposed. Several examples are presented to demonstrate the assessment and performance in this method compared to the classical step-by-step integration.