This research work investigated the axial crushing behavior of a circular aluminum extrusion in alloy AA6063-T5 filled with polymeric foam and a glass-fiber structure. The components were experimentally tested under quasi-static and impact loading conditions supported by a material testing campaign. Energy absorption, crush force efficiency and specific energy absorption were experimentally measured in order to assess the performance of a design proposal. Besides, the interaction effects between the different materials has been analyzed in depth and compared to the results for aluminum foam filled extrusions available in the literature. The confinement effect of the foam on the glass fiber plates has been found to have a very remarkable contribution to the energy absorption levels of the component, whereas a negligible foam-extrusion interaction was observed due to the gaps in the initial geometry of the specimen. The investigated component show an overall good performance, specially in terms of crush force efficiency. However, the specific energy absorption of the component was reduced by approximately 10 % compared to the aluminum extrusion alone.

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Fuel efficiency and occupant safety are two of the most important concerns in the automotive industry nowadays. Encouraged by the importance of this field of study, this research attempts an improvement in the crashworthiness of a vehicle crash absorber. This component consists in a square hollow steel tube filled with a honeycomb structure made of glass-fiber reinforced polyamide. Surrogate-based optimization techniques are used. The three objective functions chosen-mass, absorbed energy and peak load-are approximated by two different models: multivariate adaptive regression splines and gaussian process (kriging). The thickness of both parts, the shape of the honeycomb and its height are selected as design variables. Two preliminary analyses of the specimen are performed: the computation of the interaction effect and a comparison of a hollow tube with the specimen. From the results of multi-objective crashworthiness optimization two Pareto frontiers are obtained, one for the absorbed energy and mass, and another one for the absorbed energy and peak load. The results achieved show great improvements on all objective functions compared to the original design. The peak load is reduced by 37% on a specimen with similar mass and absorbed energy, and the specific energy absorbed is increased by 39.5% for a specimen with a similar peak load to the one from the initial model.

This investigation focuses on the multiobjective optimization of a crash box subjected to static loading by using a validated numerical model and an analytical approach. The crash box is made with a unique combination of three materials: an aluminium tube filled with polyethylene terephthalate (PET) foam and a glass-fibre reinforced polymer (GFRP) skeleton. A finite element model was calibrated based on the results obtained in a material testing campaign using appropriate constitutive equations. A J2-plasticity model was used for the material behaviour of the aluminium alloy, and the PET foam was modelled using Deshpande and Fleck's model. Regarding the short-fibres GFRP, a Voce plasticity model was fitted to the experimental data. After a successful validation of the finite element model, the filled aluminium tube was subjected to a structural optimization to achieve the best crash performance. Three relevant design variables were selected: the thickness of the outer aluminium cylinder, the thickness of the GFRP and the density of the PET foam, the last being related to the crushing strength of the foam. Given the high computational cost of each finite element model, a multi-adaptive regression splines metamodel was fitted to a large-scale sampling. Optimum pairs were obtained for the absorbed energy, the specific energy absorption, the peak load and the mass of the com- the component over the design region selected for the optimization, and was also used for its optimization with satisfactory results.

Please cite this article as: Paz, J., Díaz, J., Romera, L., Costas, M., Size and shape optimization of aluminum tubes with GFRP honeycomb reinforcements for crashworthy aircraft structures, Composite Structures (2015), doi: http:// dx. AbstractCrashworthiness optimization of aircraft and automotive structures has become one the main research targets for their respective leading industries. The following research proposes a new design of an aircraft's vertical strut. The design consists of a hollow aluminum square tube with a glass-fiber reinforced polymer honeycomb-shaped inner structure. Size and shape surrogate-based optimization techniques are used, with the thicknesses of both materials, cell size and cell shape as design variables. The objective function chosen for the single-objective optimization is the specific energy absorption, while the metrics for the multi-objective optimization are the peak force, mass, absorbed energy and the specific energy absorption. An improvement of 22% of the specific energy absorption with low peak force values is obtained from the single-objective optimization by significantly changing all design variables. Two Pareto fronts have been obtained from the multi-objective optimization confronting, the specific energy absorption against the peak force and the mass against the energy absorbed. When compared to the baseline model, the optimized models show substantial improvement, increasing the specific energy absorption by 65% or reducing the peak force by over 55%. It has been observed an important effect of the cell shape on the model's performance.

In the field of automotive safety, the lightweight design of crash absorbers is an important research topic with a direct effect on the occupant safety levels. The design of these absorbers usually requires an optimization of their crashworthiness, which can include multi-objective and reliability-based optimization techniques. This process is very time-consuming, and in spite of the continuous growing of computational power, the problem needs a reliable solving scheme. The use of surrogate models and parallel computing are suitable alternatives to deal with this issue. However, the strongly non-linear response functions obtained from the finite element simulations need careful treatment. This work contributes with the application of a surrogate-based reliability-based design optimization method to an original design of a crash absorber made of metal and a glass-fiber reinforced polymer which is subjected to a frontal impact. Multi-adaptive regression splines models are employed to emulate the original responses, and three different approaches in the sampling stage of M. Cid Montoya the method are compared. The absorbed energy and the mass of the element are considered as objective functions, while the peak value of the force transmitted to the occupants of the vehicle is the design constraint. A discussion of the employed materials is presented and the proposed approaches are compared. Finally, several Pareto fronts are obtained as a solution to the probabilistic problem. Results show that a combination of aluminum and glass fiber reinforced polymer is optimum for this problem, and some design rules are offered.

This research proposes a new design for a vertical strut used in aircraft fuselages. It