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Aim of the current study is to design the extra frontal protection system of a car satisfying the requirements of directive 2005/66/EC of the European Parliament and of the Council. The car frontal protection system is treated as additional energy absorbing element. An analysis of a car-pedestrian crash situation is performed by use of explicit Finite Element Analysis solver and the following stiffness analysis with implicit Finite Element Analysis solver. For modeling response surface and search for optimal solution the LS-OPT software is utilized and some comparative simulations are performed by use of MATLAB. The experimental validation of the models designed is performed.

Optimal design of the frontal protection system of a car is considered. The study is focused on design of the fastening components. A simple theoretical estimate on deformation energy is given. The car-pedestrian collision situation is analyzed by use of the LS-DYNA explicit solver. Corresponding stiffness analysis is performed by use of the LS-DYNA implicit solver. The approximation of the objective and constraint functions is modeled by use of artificial neural network (NN) and search for an optimal design is performed by use of a genetic algorithm (GA). The obtained numerical results are validated against experimental test results. [ABSTRACT FROM AUTHOR]

In the current paper optimal design of the manufacturing technology route has been studied. For finding out the optimal technology route of the large composite plastic products the structure of the technology process has to be cut down into different process segments: vacuum forming technology, technology for post-forming operations, strengthening and assembling. The vacuum forming process has been analyzed with different materials like ABS/PMMA, Polycarbonate and Acrylic Plexiglas. In the glass-fiber reinforcement (polyester resin with randomly oriented short glass fibers) process the reinforcement layer thickness has been analyzed and optimized. The Neural Network meta-modeling technique has been used. The optimization of the plastic sheet and its reinforcement layer thickness has been performed using the surrogate design model. The Finite Element Analysis simulation has performed with optimal thickness values to verify the prediction accuracy of the surrogate model. For optimal selection of technology route the corresponding optimization model has been proposed. Model has based on maximization of total profit, where constraints are the workstation time capacities, material availability and optimal technology structure. A neural network approach and MatLab Neural Network Toolbox has been used. [ABSTRACT FROM AUTHOR]