Crashworthiness optimization of helicopter subfloor based on decomposition and global approximation
This work deals with the development of an optimization procedure under crashworthiness requirements applied to a typical helicopter subfloor. The difficulties due to the nonlinear design space and structural behaviour are overcome by developing an optimization procedure based on decomposition, where the structure to be optimized is converted into a set of smaller and linked substructures. To evaluate the response of each substructure, global approximation strategies, based on neural networks, are used. Size variables (dimensions, thickness) and geometrical variables (element number and position) are considered in order to maximize the global crashworthiness performance. The energy absorbed per unit mass by the subfloor is chosen as objective function and acceleration constraints are considered. Genetic algorithms are used to find the optimal configuration. The optimization allowed an increase in the crush force efficiency of 12% and a decrease in the subfloor mass of 4%. A significant CPU time saving was also obtained.
crashworthiness optimization global approximation neural networks problem decomposition