A Coruña, Spain
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Diaz J.,Structural Mechanics Group | Hernandez S.,Structural Mechanics Group
Aerospace Science and Technology | Year: 2010

In this work an uncertainty quantification procedure and a robust design method are applied to the thermal design of a skin panel and a wing box section. The uncertainty quantification method selected is based on Monte Carlo simulations and a set of common design parameters have been considered and formulated with random values. Numerical results show that the most significant randomness comes from thermal loads and also that the amount of uncertainty decreases from input to output. On the other hand, the Taguchi's method of robust design has been applied to obtain the most appropriate values of a set of control factors in several design situations. In this case, the results show an improvement in the response of the components, maintaining a low dependence on input value variations and producing designs that increase the quality level. © 2010 Elsevier Masson SAS. All rights reserved.


Costas M.,Structural Mechanics Group | Diaz J.,Structural Mechanics Group | Romera L.,Structural Mechanics Group | Hernandez S.,Structural Mechanics Group
International Journal of Mechanical Sciences | Year: 2014

This paper applies surrogate-based multi-objective optimization techniques to a crashworthiness problem in which the impact performance of a frontal crash absorber made of steel and a glass-fiber reinforced polyamide is optimized. Two well known crashworthiness indicators are considered as contrasting objective functions: the Specific Energy Absorption (SEA) and the Load Ratio (LR), whose responses are approximated by multiple types of surrogate models due to their computational cost and their noise levels. These models are quadratic and cubic polynomials, Gaussian process (kriging) and multivariate adaptive regression splines (MARS). The finite element model includes strain-rate sensitive properties, which is verified with experimental data from a drop-tower test. The thickness of the different parts, the geometry of the cross-section and the offsets of the reinforcement parts are chosen as design variables. Pareto solution is obtained after both models are verified. Results show improvements in both functions by almost 50% compared to the original design. © 2014 Elsevier Ltd.

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